Recently developed direct-acting antiviral (DAA) treatments for hepatitis C virus (HCV) have been groundbreaking for their high efficacy across disease genotypes and lack of severe side effects. This study uses a cost-of-illness (COI) approach to estimate the net value conferred by this class of drugs using the cost and efficacy of one of these novel drug combinations, sofosbuvir and velpatasvir (SOF/VEL), recently licensed for generic manufacture in India. This study considers COI of lifetime earnings lost by patients and potential secondarily infected individuals due to disability and premature death from HCV infection. Expected net benefits of treatment are substantial for non-cirrhotic (NC) and compensated cirrhotic (CC) patients . Increased earnings are not sufficient to fully offset cost of treatment for decompensated cirrhotic individuals but treatment may still be justified on the basis of the intrinsic value of health improvements and other treatment benefits. Hepatitis C virus (HCV) is a major global health problem affecting between 120 million and 200 million people worldwide .India holds a substantial portion of the global HCV burden. The number of HCV carriers in India is estimated to be between 3 and 9 million people, with localized prevalence of HCV antibodies reaching as high as 5.2% in some studies . While tFor decades, HCV infection was a broadly known, burdensome illness without effective and well-tolerated treatment options. Previously, pegylated interferon (PEG-INF) or non-pegylated interferon delivered in combination with ribavirin (RBV) were the most common HCV treatments. However, the overall efficacy of this treatment course in achieving sustained virological response (SVR) is only between 47% and 63% . The lowHowever, several new treatments developed in recent years, known as direct-acting antivirals (DAAs), have greatly improved the curability of HCV infection. These drugs, which include sofosbuvir, simeprevir, and daclatasvir, feature much higher rates of virological clearance and far better tolerability than previous treatment options . The newOne of these novel drug combinations, sofosbuvir (400mg) and velpatasvir (100mg) (SOF/VEL) is assessed as representative of the incremental value offered by the new class of DAAs. This study focuses on SOF/VEL specifically because a Nielsen survey of physicians indicated SOF/VEL to be the preferred treatment option of all the DAAs available at the time of the study. This single-tablet regimen, was recently licensed for generic manufacture in India. The combination is particularly valuable for having above 95% efficacy for each disease genotype ,14, and Cost-benefit analysis is particularly useful for determining the net benefits of a given health intervention because it represents costs and outcomes of treatment in comparable monetary units. Generally, costs are fairly easy to monetize, often represented as the sum of the prices of goods and services needed to administer a given intervention. However, many benefits of health interventions, such as decreased morbidity or mortality, are not explicitly traded on economic markets. As such, definitive monetary values for these benefits cannot simply be observed; instead, a deliberate approach must be taken to infer their value from empirical information, normative judgements, or some combination of both.Among the most versatile and broadly applied methods of determining the value of treatment is the cost-of-illness (COI) approach, which values an intervention according to the estimated economic burden of the disease it treats. By measuring the burden of disease to society, COI studies can play an important role in informing policymakers about the relative importance of different health issues and which interventions offer the most impact for investment. However, those utilizing COI results must pay heed to the methodologies used in each study to ensure they understand exactly which costs these analyses attempt to measure. Failure to do so may lead to misinterpretation of the relative and absolute values of various interventions.The costs examined in COI studies can generally be categorized into three broad groups: direct costs, indirect costs, and intangible costs. Direct costs of illness comprise all expenses individuals, families, health systems, and societies incur as the result of an illness. These include expenditures on diagnosis, treatment, and other healthcare goods and services, as well as nonmedical expenditures necessitated by illness, such as the cost of transportation to medical facilities or relocating the household. Indirect costs include any productivity lost due to illness-related morbidity or mortality . This isThis study focuses specifically on the indirect costs HCV imposes on market activity and hence is a conservative estimate of the cost of illness. The indirect costs include the disease’s impact on the expected lifetime productivity of primary infected individuals  and any other individuals to whom they may transmit the disease.Analyses do not consider the direct costs of HCV infection if individuals are not treated with SOF/VEL, as individuals are unlikely to undergo liver transplant or dialysis (both of which are prohibitively expensive for most Indians), or receive other, less-effective HCV medication. Other treatment costs for easing discomfort in the late stages of the disease are assumed to be negligible. Intangible costs are also excluded from analyses because of the ambiguities and uncertainties involved in assigning monetary value to these various outcomes. Excluding these costs allows for results that depend less on arbitrary—and possibly controversial—decisions on value setting.In accordance with these considerations, the model presented in this paper estimates the individual-level net benefits to market productivity resulting from treatment with SOF/VEL for both primary and secondarily infected individuals. The focus on secondarily infected individuals seeks to capture the benefits associated with the interruption of further HCV transmission, considering the average rate of transmission, the remaining life expectancy of the primarily infected individual, and the expected impact of HCV infection on the lifetime earnings trajectory of each individual to whom the illness would be transmitted. This analysis is particularly valuable for considering economic impacts at the national level from a societal perspective. We contrast our approach to that presented in Aggarwal et al. , which dThe process for estimating these benefits is divided into four stages: (i) estimating age-earnings trajectories for Indian adults with average health, (ii) calculating risk of HCV-related disability and premature death if not treated, (iii) estimating the value of earnings preserved by curing HCV infection, and (iv) applying the value of curing HCV to estimate the net value conferred by SOF/VEL treatment.The earnings profile and employment status of an Indian adult with average health provide a basis for the expected value of each year of earnings lost due to HCV infection. Throughout this analysis, individuals with average health are used to represent individuals who do not have HCV. These two populations are considered equivalent because HCV-positive Indians make up less than 1.2% of the total population, and therefore have a negligible impact on the population average values. The parameters of these models are estimated using data from the second wave of the Indian Human Development Survey (IHDS) . The IHDAny individual (age 15 or older) who earned wage or salary income, or who participated in income-generating household enterprise activities  over the last year is considered to be working. The remaining population is considered to be nonworking. A binary indicator of work status (based on the aforementioned criteria) is used as a dependent variable in a probit regression that includes the following control variables: age, squared-age, sex, education level, marital status, number of members of household, and state of residence.These regressors are chosen because of their standard usage in the labor economics literature and because they are included in both the IHDS data and the Nielsen HCV patient questionnaire conducted in India in fall 2016 (N = 300).  S1 Table in the appendix in The individual earnings variable used in the analysis is constructed as the sum of (1) annual earnings from wages and salaries, (2) annual income from agricultural self-employment activities, and (3) annual income from nonagricultural self-employment activities.  Income from agricultural and nonagricultural self-employment activities is provided at the household level in the IHDS. The following formula is used to estimate each household member’s individual earnings from these agricultural and nonagricultural activities:e = annual individual earnings from the self-employment activity,h = hours of labor the individual contributed to the self-employment activity over the last year,H = total hours of labor all household members contributed to the self-employment activity over the last year, andI = total household income from the self-employment activity.This formula assumes that the productivity of an hour of labor is equal among household members. It also assumes that there is no complementarity or congestion between household members labor .A Poisson model is then used to regress this combined earnings figure against the same independent variables used in the employment regression. In repeated trials of half-sample cross-validation, the Poisson model produced far more accurate earnings predictions than the typically used log-linear model. Furthermore, robust standard error (SE) estimates are used to ensure that the SEs are consistently estimated. For a detailed discussion of the appropriateness of applying the Poisson regression to predict nonnegative variables, refer to Santos Silva & Tenreyro  and WoolThe coefficients that these probit and Poisson models generate can be used to estimate the likelihood of working and average earnings conditional on working for an individual with given characteristics and average health status. Multiplying these two predictions yields expected earnings. Multiplying these predictions to yield expected earnings relies on the assumption that employment and earnings conditional on employment are probabilistically independent. This may introduce some bias insofar as employment status may be correlated with potential earnings. However, use of a “seemingly unrelated regression” method would not improve the predictions because the predictor matrixes are identical across both regressions .diagnosed with HCV in India. diagnosed population are expected to be much higher than those of treating the average member of the HCV-infected population, due to the positive correlation between diagnosis and level of education . If HCV screening and diagnosis were to become more widespread , the characteristics of the diagnosed population would be expected to shift closer to those of the general Indian population. In this case, the results presented in this paper would overestimate the average value conferred to patients to the extent that the current HCV-diagnosed population has higher productivity than the diagnosed population in the future period. By contrast, secondarily infected individuals are assumed to reflect the general Indian population (as represented in the IHDS) and their COI estimates face no risk of bias due to changes in patterns of diagnosis.This study uses separate data from the Nielsen HCV patient survey to assess the sociodemographic characteristics and disease status of individuals +) and the same demographic, social, and household characteristics, as the respondent. Given that invasive medical procedures and blood transfusions are typical routes of transmission in India, comparator individuals would be more likely to have a health condition requiring one of these procedures. As such they would likely have somewhat worse health status on average than typical members of the Indian population, with similar sociodemographic characteristics. This suggests that the remaining life earnings of these counterfactual individuals may be somewhat overestimated.Each independent variable utilized in the IHDS regressions described previously is also present in the Nielsen HCV patient questionnaire. Thus, for any Nielsen respondent it is possible to estimate the earnings of a member of the Indian population with average health status .Chronic HCV carriers are typically asymptomatic for many years, with substantial disability usually occurring in the late stages of the disease. The model assumes that individuals experience no disability until they develop decompensated cirrhosis or liver cancer (hepatocellular carcinoma or HCC), corresponding to the assumptions made in Wong et al. . Thus foCalculations of this risk use age- and sex-specific disease transition rates and HCC mortality from Razavi et al.  as well t = 0) with a hypothetical million-person cohort. The members of this initial cohort are homogeneous with respect to age, sex, and stage of disease progression . No individuals in the patient dataset was recorded as having HCC at the time of interview. As such, HCC is not listed as an initial disease state, but individuals may still transition into this state from compensated cirrhosis. The possibility of transition from decompensated cirrhosis to HCC is ignored because both are treated as equivalent states of disability in terms of labor productivity . In each successive year  the number of individuals advancing to the next disease stage is calculated using the previously described adjusted transition rates. The number of individuals dying from decompensated cirrhosis and HCC  is also calculated using the decompensated cirrhosis and HCC death rates provided in D’Amico  to a given year after the time of interview (t). Average transmission rate is calculated simply as the estimated number of new HCV infections divided by the estimated total viremic population, as provided in Saraswat et al. [To calculate the herd benefits  of curing HCV, the average annual transmission rate of HCV in India  except their age, which is set 20 years younger than the individual who infected them. This approach is intended to create a group of secondarily infected individuals that reflects overall population characteristics but with the age structure of the patient sample. The 20-year age reduction is intended to approximate the substantial time lag that typically occurs between the time of infection and the first diagnosis with HCV. For each of these years, the expected years of life disabled (YLDs) and years of life lost (YLLs) are calculated for a hypothetical secondarily infected individual in the same region as the primary infected individual. Given that diagnosis is associated with socio-economic status (whereas this is not necessarily the case with infection) it is assumed that the population of HCV The value of the YLDs and YLLs are summed across all years of the secondarily infected individual’s life up to age 100 . The lifetime total values of averted YLDs and YLLs are multiplied by the expected number of individuals infected by the patient in a given year. These values are then summed across all years of the primary infected individual’s life. The equations for calculating the herd benefits of averted disability and premature death are provided below:Xdis)Benefits of averted disability for secondarily infected individuals (Xdeath)Benefits of averted premature death for secondarily infected individuals ,ϵi = the estimated earnings of the secondarily infected individual i years after he or she was infected ,i,i, andi.For individuals who are decompensated cirrhotic at the time of interview, we assume that 29.4% are in their first year of decompensation. Although the time when surveyed individuals first developed decompensated cirrhosis is unknown, the composition of first-years would converge on 29.4% given the relative mortality rates of 0.4 for first-year and 0.25 for non-first-year decompensated cirrhosis  if we asThe net value of SOF/VEL is a function of the value of curing HCV infection, the efficacy of treatment, and the cost of treatment.T) can be calculated by multiplying the value of curing HCV (C) determined earlier by the probability of being cured after two rounds of treatment, orF1 and F2 equal the efficacy of the first and second round of treatments, respectively. The efficacy data are the results from ASTRAL-1, ASTRAL-3, and ASTRAL-4 clinical trials. Treatment included 12 weeks of SOF/VEL administration for non-cirrhotic and compensated cirrhotic patients, and 12 weeks of SOF/VEL plus ribavirin for decompensated cirrhotic patients. Although these efficacy figures are used to simulate patient outcomes, efficacy in real-world usage is likely somewhat lower than efficacy in carefully controlled clinical trial conditions.Treatment guidelines suggest that HCV carriers who fail their first round of treatment with SOF/VEL should generally be administered a second round of treatment ,36. AssuP1) and second round of treatment (P2). Drug price estimates were taken from Dandekar & Raghavan [Raghavan . All othT), treatment costs (P1 and P2), and the efficacy of the first round of treatment (F1) are then used to estimate net value of treatment (Z) as follows:Expected treatment value  suggests that curing the average chronic HCV-carrying patient  would preserve 36,83,290 INR in earnings see .The largest expected treatment benefits are conferred to compensated cirrhotic men  yields net benefits for non-cirrhotic and compensated cirrhotic individuals. While this net benefit is larger for men than for women, the net positives are very large in either case. However, the benefits of averted future infection are not enough to offset the cost of treatment for decompensated cirrhotic men or women. A 12-week supply of medication would need be sold for 3,024 INR (US$ 47) or less in order for the cost of treatment to be offset by the productivity-related herd benefits of treating decompensated cirrhotic individuals.Sensitivity analyses explore the impact of changing assumptions about the income growth the Indian economy is expected to experience in the coming years, the multiplier from reported to actual income, and the cost of the medication. These sensitivity analyses reveal that the costs of treating non-cirrhotic and compensated cirrhotic individuals are dwarfed by the benefits of treatment, even under the most conservative assumptions examined. Under the high value, low cost assumptions, treating decompensated cirrhotic individuals with SOF/VEL is determined to be cost-beneficial on the basis of herd effects alone.Additional estimates are produced applying the parameters utilized in the baseline specification of Aggarwal et al.  i.e., t. Under tThe average net benefits of SOF/VEL treatment are used to estimate the total economic impact of treating 10% of the HCV-positive population of India . This value is calculated by multiplying the average net benefits of treatment by the treatment population size, 600,000, 10% of 6 million HCV-viremic individuals . FollowiHowever, some of the additional healthy adults who would remain in the labor force if treated would likely displace the employment of other workers  or that these additional workers would put downward pressure on wages. In the extreme case, the additional healthy workers would only hold employment positions that would otherwise be filled by other members of the Indian labor force and the net macroeconomic benefits of treatment would be null (or negative if the increased supply of labor reduced equilibrium wages).The macroeconomic impact of treating 10% of India’s HCV-positive population would fall somewhere between these extreme scenarios. Here it is important to consider that the additional living, healthy, and employed individuals would utilize domestic goods and services. This increased demand for goods and services leads to an increase in demand for labor in India, creating additional employment opportunities. Determining the exact ratio of healthy life years preserved to years of employment added to the Indian economy is a complex macroeconomic modeling task beyond the scope of this paper. Despite these caveats, the upper-bound estimate of this aggregate impact gives an idea of the scope of returns to treatment possible on a national scale.The analyses demonstrate that the benefits of increased future productivity for non-cirrhotic and compensated cirrhotic individuals easily justify the cost of treatment with SOF/VEL, even under conservative assumptions about these benefits. Previous research has examined the impact of SOF/VEL treatment on averting future costs of treating late stage symptoms of HCV infection, and shows treatment with SOF/VEL to be cost-saving within five to 12 years . HoweverWhile the cost of treating decompensated cirrhotic individuals is not offset by gains to future market productivity, this does not imply that these individuals should not receive treatment.First, these analyses only consider the impact of treating HCV without undergoing liver transplantation. While liver transplantation is prohibitively expensive for the vast majority of Indians, the tremendous gains to extending healthy life expectancy offered by liver transplantation and SOF/VEL together could possibly contribute enough of a productivity boost to offset this cost over the life course.Another, more important, limitation is that the analyses included in this paper only estimate the additional market productivity preserved by treating HCV infection with SOF/VEL. This is just one component of the benefits of maintaining or restoring health. Curing HCV infection can also help maintain unpaid productive activities, such as caring for children, doing household work, or providing support to other adults. Although HCV is rarely symptomatic in children (because of the time taken for liver function to degrade), the disease’s impact on adults can interfere with their children’s education and development. Shocks to parental health that reduce their earnings may limit the household’s access to nutritious foods necessary for healthy physical and cognitive development or may necessitate that children leave school and work to provide another source of income . As suchOn top of these concrete costs are the aspects of the disease burden that are not as tangibly connected to monetary value: the discomfort, pain, and anxiety caused by the illness and the extent to which it prevents individuals from enjoying leisure and engaging in activities they find fulfilling. The value of treatment also includes the intrinsic value of years of life that would be lost to HCV infection without treatment.per se, or any other positive results of a given treatment.Estimates of the value of HCV treatment that attempt to encompass all of these components by using the statistical value of disability-adjusted life years lost place the value of treatment for decompensated cirrhotic individuals well above the threshold necessary to justify the cost of treatment . HoweverFurthermore, neither the approach taken in this paper nor the VSLY-approach account for the distributional impacts of a large-scale program to increase access to SOF/VEL treatment. Providing low-income HCV carriers with access to treatment they otherwise could not afford would address economic inequality by improving lifetime earnings and savings among poor households. Here, the source of funding and characteristics of the treatment recipients would determine the extent to which public provision would be redistributional.Although this paper’s calculations capture only part of the benefits of treating HCV, the findings are uniquely valuable for quantifying a clearly defined element of this value in an empirically determined manner. These findings have the additional advantage of being tailored to the specific socioeconomic characteristics of the population diagnosed with HCV in India. As such, they offer a compelling argument that HCV treatment will reap very large market returns for most of the national HCV-positive population. These market returns should serve as one of many motivating factors supporting increased access to and utilization of DAA treatment across India.S1 File(DOCX)Click here for additional data file.


Herpes zoster (HZ) and herpes zoster ophthalmicus (HZO) are the result of reactivation of varicella-zoster virus (VZV) from a dormant condition. Although HZ symptoms typically subside after a few weeks, HZO and postherpetic neuralgia (PHN) can persist at least 90 days after the appearance of the HZ rash. Presently, there is no gold standard for a disease-modifying therapy for postherpetic neuralgia and the current treatment is focused on early intervention and management of symptoms and dermatological complications. In the present case, a 74-year-old Caucasian male initially developed severe right-sided eye pain and headache. He was diagnosed with HZO and treated with acyclovir, but later developed swelling over the right eye and skin rash over the right side of the forehead and face. He presented to the office after the acute manifestation of the infection disappeared, but the headache and scalp hypersensitivity persisted and increased. Osteopathic manipulative treatment (OMT) included correction of cranial strains, inhibition, myofascial release, balanced ligamentous tension, and facilitated positional release. In one week, the patient reported a reduction in pain from 10/10 to 2/10. Two weeks later, he reported complete resolution of his initial symptoms. There are a limited number of cases that illustrate the benefit of OMT in diminishing pain and associated symptoms in different types of neuralgias. OMT ensures the restoration of normal anatomical structure and associated function through correcting somatic dysfunction, normalization of blood supply, muscle tone, and lymphatic drainage, therefore, providing pain relief. Better documentation of case reports and more research in this area would greatly benefit the medical community. The present case demonstrates the successful treatment of PHN with OMT. OMT can be successfully used as an adjunct therapy in cases of HZ and PHN. Herpes zoster (HZ) is a result of the reactivation of dormant varicella-zoster virus (VZV). HZ causes a rash in a unilateral dermatomal distribution and symptoms typically subside in a few weeks. Herpes simplex virus type  is definThe risk of VZV reactivation as well as developing the associated complications increase in the elderly and immunocompromised individuals ,4. NearlOsteopathic manipulative therapy (OMT) provides means for the restoration of normal anatomical structure and therefore function. There have been several cases that illustrate the benefits of OMT in diminishing a patient's pain and associated symptoms in different types of neuralgias. In the current report, we describe the case of a patient who presented with severe right-sided eye pain and headache. He was diagnosed as having PHN following HZO and was treated using OMT.A 74-year-old Caucasian male developed severe right-sided eye pain and headache after experiencing a stressful event two days prior. The patient consulted with his physician and was diagnosed with HZO on April 1, 2019. The patient was prescribed an antiviral, oral acyclovir 800mg five times a day for 10 days. However, the right-sided eye pain and headache did not subside and over the next seven days, swelling of the right eye developed. Additionally, a skin rash developed over the right side of the forehead and face. The patient was treated with a topical steroid ointment for the skin rash, blepharitis (inflammation of the upper eyelid), and conjunctivitis with steroid eye drops. The patient's past medical history is significant for well-controlled benign prostatic hyperplasia (BPH) and psoriasis with the last flare-up in 2015. He denied any past surgical history or recent trauma and has an unremarkable family history. The vaccination history is unknown and there is no evidence of him receiving the HZ vaccine. The patient presented to our office six weeks after his initial symptoms, on May 16, 2019, complaining of headache and skin hypersensitivity to touch that persisted after the acute manifestations of infection disappeared. It deprived him of sleep at least for two weeks since putting his head on the pillow was excruciatingly painful. He also complained of a tingling sensation in his right arm. The patient denied any visual disturbances and did not have an ophthalmologic consultation  was conducted on the initial visit to reveal an extreme skin sensitivity to touch in the right greater occipital nerve distribution, increased tone in the right anterior cervical muscles: sternocleidomastoid, scalenes, and platysma; posterior cervical muscles: erector spinae, splenius capitis, semispinalis capitis, upper trapezius right>left; the right rhomboids, and pectoralis major and minor muscles. The first rib on the right was found to be in an exhaled position. The motion of the cervical spine and sternum in sagittal and coronal planes were restricted secondary to muscle hypertonicity and cervical somatic dysfunction. The patient's cranial examination presented with right occipital condyle compression, externally rotated right temporal bone, and the right side-bending/rotation strain of sphenobasilar synchondrosis (SBS).On the initial visit, the physician used myofascial release and reciprocal inhibition to treat the hypertonic muscles and the cranial dysfunctions were treated via exaggeration. Balanced ligamentous tension (BLT) was used to restore the motion of the sternum and the first rib was treated using the facilitated positional release (FPR) technique. The patient was also instructed to do stretching and isometric exercises for the cervical and upper thoracic muscles. For more information on the techniques used, please refer to the section below.The patient failed to appear for the first follow-up visit scheduled for June 3rd, 2019. However, he reported over the phone that his pain intensity decreased from 10/10 on his initial visit to 2/10. On the second follow-up visit two weeks later, he reported a complete resolution of the initial symptoms. On OSE, there were significant improvements in the range of motion for the cervical spine as well as the muscle tone in the affected areas. The previous somatic dysfunctions were also resolved  and fascia  restrictions. It helps to restore the functional balance of all tissues in the musculoskeletal system .Reciprocal Inhibition is a technique that uses the reflex mechanism of reciprocal inhibition. In other words, when the antagonist muscles are contracted, the signals are conveyed to the spinal cord, and then through the reciprocal inhibition reflex arc, the agonist muscle is forced to relax .The exaggeration technique used in treating the cranial somatic dysfunctions uses the inherent forces in the body to eventually increase the movement toward the ease and back to the original balance position. It is done by moving the dysfunction toward ease and adding an activating force when the ease barrier is met . The BLT technique uses the inherent forces in the body, such as a circulatory, lymphatic, or primary respiratory mechanism to balance the tension among ligaments supporting a joint. The physician introduces a force to position the patient so that a fulcrum may be set. This fulcrum, paired with the subsequent lever action of the tissues (ligaments), combines with fluid dynamics and other factors to produce a change in the dysfunctional state .FPR is a patient-passive technique with the focus on reducing abnormal muscle hypertonicity and restoring lost motion to a restricted articulation. The physician would place the body component into a neutral position, minimizing tissue and joint tension in all planes, and then add an activating force (compression or torsion) .PHN can be potentially debilitating and impair the patient's ability to perform activities of daily living (ADL) , 7. PatiIn some cases ,10, the Surgical approach offers superficial epidermal surgical removal of a recurrent herpes simplex lesion, which prevents reinoculation of that epidermal site by the virus-laden sensory neuron .OMT as performed in the present case can greatly reduce pain and limitation in range of motion in patients with PHN. Providing pain relief to a patient through OMT decreases the need for medications and the associated side effects. It may also allow the patient to avoid surgery. Several cases have been published that illustrate the benefit of OMT in diminishing a patient's pain and associated symptoms in different types of neuralgias. Hallaq and Harris  reportedThe presented case has demonstrated the successful treatment of PHN with OMT. There are no available PHN cases in the literature and in general, there is a lack of case studies where OMT is used in the management of neuralgias. OMT ensures the restoration of normal anatomical structure and therefore function through correcting somatic dysfunction, providing optimal conditions for body to heal itself, normalization of blood supply, peripheral nervous system regulation, muscle tone and lymphatic drainage therefore providing pain relief and reducing the need for additional medications. OMT can be successfully used as an adjunct therapy in cases of herpes zoster and postherpetic neuralgia.


To ascertain if virtual reality exposure therapy (VRET) is an effective add-on tool in the treatment of Panic Disorder (PD).The exposure to virtual stimuli has been studied as a useful treatment for PD. However, the studies with PD are still scarce and use dissimilar protocols, with effectiveness varying according to the protocol applied.Eight PD patients received VRET as an add-on treatment to pharmacotherapy. The treatment protocol consisted of eight sessions. The first session is for the patient to understand the treatment and to answer the questionnaires. The second and third sessions were to prepare the patients for exposures with breathing training using diaphragmatic breathing and others breathing techniques to manage anxiety. From the fourth to eighth sessions, the patients followed a hierarchy of tasks during virtual reality exposure. Clinicians rated the Clinical Global Impression Scale (CGI) and the Panic Disorder Severity Scale (PDSS). The patients rated the Diagnostic Symptom Questionnaire (DSQ); the Mobility Inventory (MI), the Anxiety Sensibility Index (ASI-R), the Beck Depression Inventory (BDI), the Beck Anxiety Inventory (BAI) and the WHOQOL-BREF before and after the protocol. After all exposures, the Igroup Presence Questionnaire (IPQ) was applied to measure the sense of presence experienced in the virtual environment. The virtual environment simulated the subway of Rio de Janeiro.There were no statistically significant improvements in the CGI-S, PDSS, BAI, MI or WHOQOL. There was a significant improvement in the BDI scores (P = 0.033). There was a trend towards improvement of anxiety measured by the ASI-R (P = 0.084) and of panic symptoms measured by the DSQ (P = 0.081) scores. There was also a significant improvement of sense of presence  through the exposure sessions.Our study demonstrated that VRET as an add-on to pharmacological therapy could benefit PD patients. Despite the lack of significant differences in the means, the dispersion of PDSS and BAI scores were smaller after treatment compared to before treatment, suggesting that patients with more severe anxiety, panic and agoraphobia symptoms benefited more of the VRET protocol so, at the end of the treatment, differences were found in important measures of panic. Randomized controlled clinical trials are warranted to confirm the efficacy of VRET.This study was funded by the Brazilian National Council for Scientific Development (Cnpq). The authors report no conflicts of interest.


In the last decade, the analysis of the medical images has evolved significantly, applications and tools capable to extract quantitative characteristics of the images beyond the discrimination capacity of the investigator’s eye being developed. The applications of this new research field, called radiomics, presented an exponential growth with direct implications in the diagnosis and prediction of response to therapy. Triple negative breast cancer (TNBC) is an aggressive breast cancer subtype with a severe prognosis, despite the aggressive multimodal treatments applied according to the guidelines. Radiomics has already proven the ability to differentiate TNBC from fibroadenoma. Radiomics features extracted from digital mammography may also distinguish between TNBC and non-TNBC. Recent research has identified three distinct subtypes of TNBC using IRM breast images voxel-level radiomics features . The correlation of these TNBC subtypes with the clinical response to neoadjuvant therapy may lead to the identification of biomarkers in order to guide the clinical decision. Furthermore, the variation of some radiomics features in the neoadjuvant settings provides a tool for the rapid evaluation of treatment efficacy. The association of radiomics features with already identified biomarkers can generate complex predictive and prognostic models. Standardization of image acquisition and also of radiomics feature extraction is required to validate this method in clinical practice. Medical imaging is viewed as one of the top developments that have changed cancer care, as it has fundamentally changed the manner in which oncology physicians measure, manage, diagnose and treat cancer disease. Medical images have progressed substantially in recent decades, being a key player with an increasing role in the diagnosis and initial cancer evaluation, but also in the follow-up of the oncological disease. As the resolution of the images increased, a new science called radiomics was developed based on the computerized analysis of the data extracted from different types of medical images. Transforming high volumes of medical images into data that can be correlated with the prognosis and also can be used to predict the tumor response to treatment opens the horizons of using radiomics in the routine clinical setting. The concept is relatively new and the number of scientific papers describing applications of radiomics in medical practice has increased steadily since 2012, the year in which this concept was first proposed. The most commonly used imaging techniques for extracting features, in order to correlate them with clinical data, are computed tomography (CT), ultrasonography (US), magnetic resonance imaging (MRI) and positron emission tomography (PET-CT). Recently, the development of the molecular and genetic analysis of tumors has made possible the development of a new research direction based on correlating the data obtained from medical images with gene mutations, thus opening the way for a non-invasive evaluation of tumor genomic features. This new domain, characterized by a major development in recent years, based on the medical images linking to the tumor genomic and molecular profile, has been named “radiogenomics”. Being the second leading cause of cancer mortality worldwide, although advances in molecular biology have stratified breast cancer into prognostic molecular classes, the triple negative subtype is notable for its aggressiveness with a relatively limited therapeutic spectrum. An overall 4-year survival of approximately 77% for TNBC is lower than the OS of other breast cancer subtypes ranging from 82.7 to 92.5%. Radiomics is an essential player in the race to improve the management of TNBC from the identification of new biomarkers to therapeutic strategies, in the general context of the precision medicine concept implementation, in order to improve the prognosis of this relatively orphan disease in terms of less therapeutic progress in recent decades ,4.® atlas is a valuable tool for quantifying mammograms, US and MRI for breast cancer. Imaging Biomarker Standardization Initiative (IBSI) proposes since 2016 attempts to standardize radiomics features in order to be implemented in daily clinical practice. For a number of 169 radiomic features considered reproducible, it is estimated the verification and calibration of the different software [In contrast to the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) lexicon, first developed in 1993 to standardize communication between specialists involved in the diagnosis and treatment of breast cancer, radiomics offers us as quantification tools a series of features, some more intuitive  others more abstract and harder to interpret for the clinician . Currently, the 5th edition of the BI-RADSsoftware .The association of the radiomic features with molecular, genetic and clinical data and their correlation with information regarding the prognosis and the evolution of the oncological disease opens the ways of creating predictive and prognostic models with high accuracy in order to improve the diagnostic and treatment performances in the era of precision medicine. Although the concept of computer-aided diagnosis (CAD) was first reported in 1963, intensive use of CAD has been applied in medical imaging since the last decade of the 20th century. Limited at that time by the computer processing power and also by the reduced data storage capacity, the extraction of data from medical images developed rapidly by increasing the graphic processing and storage capacity of a huge quantity of images. Most radiomics and radiogenomics studies include a limited number of patients, but clinical trials enrolling large cohorts of patients are needed to validate these models in the near future. In this context, it is estimated that both The Cancer Genome Atlas and The Cancer Imaging Archive will play an essential role in radiomics and radiogenomics research in order to validate models with clinical applicability for a precision approach in diagnostic and treatment of cancer ,12,13,14A systematic review analyzing the current radiogenomics data revealed the highest number of studies having as study subject high grade gliomas (35 articles) followed by breast cancer, as a topic of interest in 10 published studies. It is possible that brain tumors are the preferred subjects of radiomic or radiogenomic studies due to the possibility of the tumors’ segmentation which offers a higher capacity of algorithm standardization. Functional imaging methods with diffusion magnetic resonance imaging (DWI) and positron emission tomography (PET-CT) have demonstrated the best ability to correlate radiomics features with the tumor phenotype ,16,17,18The first of the four stages of the radiomic workflow is data acquisition. For this purpose, it is essential to identify a lot of homogeneous features in the study group. The best method for the region of interest (ROI) delineation is also a controversial topic. Too low-resolution ROIs will be affected by image noise, but the delimitation methods vary in the literature, being also a source of uncertainty. The recommended segmented volume varies depending on the imaging method, a value of 5 cmc being recommended as a cutoff value in the case of CT images and 45 cmc in the case of PET-CT imaging. The homogeneity of the acquired images can be influenced by the pixel size, slide spacing, kernel reconstruction algorithm and also by the movement management capability. There is also uncertainty regarding the acquisition times if the contrast agent is used ,20,21,22ROI segmentation is the second stage of radiomics that leads to the generation of reproducible images parts proposed for radiomic analysis. Inspired by the manual radiotherapy planning, delineation or segmentation is subject to the variability and physician subjectivity regarding the limits of the tumor tissue and the correct identification of the tumor microenvironment, drawing the barrier between healthy tissue and the tumor being a challenge even in the age of high-resolution medical imaging. Recently, semi-automatic or automatic ROI delimitation algorithms have been developed the potential to reduce errors through inter-observer variability, thus increasing the uniformity of plain images or volumetric delineation. If a single slide is chosen as an option compared to segmenting the entire tumor volume, manual segmentation is more precise but some information that characterizes the entire tumor is thus lost. The delimitation of a single slide and the selection of a tangent circle at the inner edge of the tumor delimited on that slide is also agreed upon in some radiomic studies. The use of low-pass and band-pass filters has demonstrated the possibility to reduce the variability of the evaluated medical images by reducing the number of gray levels. All these improvements in image acquisition and processing have the final goal of obtaining generalizable and highly accurate radiomic models. Stage 3 of the radiomic analysis can be considered as the extraction, processing and reduction of features, so that a finite number of radiomic features are selected, correlated with the purpose of each proposed study ,23,24.In the paper “Radiomics: Image has More than Pictures”, the author mentions that the development of information technology has reached the level of progress in which from medical images can be extracted hundreds of variables related to size, shape, texture, in order to be included in the databases for radiomic models creations (the fourth stage of radiomics) .Agnostic features, based on mathematical formulas, are first order intensity hystograms, including features related to voxels: mean, median, energy, entropy, kurtosis, skewness. Other features are related to the shape, volume, surface, characteristics of the sphericity. Among the features related to texture, we mention “Haralick features” which refers to the matrix of gray levels. The variation of a radiomic feature is also evaluated as a potential biomarker of response to therapy, Boldrini et al. for example, considering that this variation called “delta radiomics” may predict response to neoadjuvant therapy in colorectal cancer .Currently, there are approximately 170 features that are analyzed in the creation of radiomic models and several open-source/free software has been created, being capable of extracting features from two-dimensional or reconstructed 3D images. IBEX (Image Biomarker Explorer) and MaZda are examples of computer applications that are able to extract and select significant features from different types of medical images ,27.A simplified workflow of radiomics can be divided into two big main steps, the training stage and the applications. A first step that represents the training phase of the workflow aims to associate radiomic characteristics with already known medical data. A higher number of features are initially extracted from diagnostic images via an instrument called radiomics engine. These extracted features are further analyzed in the second platform, called prediction engine, using the machine learning algorithms. The output of the prediction engine transforms the high dimensional feature space of radiomics to a much simpler classification space where the clinical hypothesis of the dataset may be easily assessed. The second step shows how this algorithm can be applied for the prediction of the result on a previously unevaluated medical case. Regarding the methods of analysis based on machine learning, unsupervised machine learning classifies the radiomic features without taking into account information obtained from previous possible correlations of those characteristics with clinical parameters. In this case, the algorithm selects the features based on two data sets (a training and a test data set). In the case of supervised machine learning, the choice of characteristics with statistical semnification will be based on results also validated in the literature. Limiting the number of features in this case can increase the predictive power of the radiomic model, also reducing the need for a large number of subjects in the training set. If an unsupervised machine learning algorithm is chosen, the biggest source of uncertainty is caused by the inhomogeneity of the data obtained from previous research studies due to the lack of standardization. For supervised machine learning, an unsolved problem remains the size and uniformity of the lots for the radiomic models training ,28,29,30Recently the tendency is to use deep learning algorithms that differ completely from the supervised and unsupervised machine learning radiomics analysis. These algorithms direct medical imaging to a multi-layer network similar to a neural network with an ability to reduce the number of features. Subsequently, these features are introduced into a supervised algorithm that produces the predictive model with clinical application ,30.TNBC represents about 15–20% of all breast cancers, but the large number of metastatic deaths in this category makes it necessary to understand its subtypes in order to identify effective therapeutic strategies. Being a subtype of cancer that does not benefit from endocrine or anti-HER2 therapy, anthracyclines and taxanes neoadjuvant chemotherapy (NAC) remains the basic treatment. The use of platinum-based chemotherapy is based on the mechanism of action related to DNA damage and is associated with improved pathological complete response (pCR). In the context of medical imagining development, the possibilities of NAC response evaluation have been improved. Thus, the use of NAC as a surrogate biomarker of chemo-sensitivity becomes possible. TNBC pCR after NAC is considered to be associated with superior survival and residual disease after NAC is associated with an unfavorable prognosis. Analyzing gene expression revealed that intrinsic basal-like subtype is the most common triple negative cancer, this subtype being associated with approximately 70% of TNBC cases. Analyzing the genetic profile on 21 data sets consisting of 3247 cases Lehman et al. considers TNBC as divided TNBC into 7 subtypes: 2 basal-like subtypes (Bl1 and BL2), 1 mesenchymal type (M), one immunomodulatory type (IM), 1 mesenchymal stem type (MSI), 1 luminal receptor subtype (LAR) and one type characterized by androgen receptor (AR) signaling. These new subtypes were also confirmed and mentioned in another analysis by Mesuda et al. Although there are predictive differences in the response to NAC and prognostic variations between these groups, this classification cannot be considered as the only factor that modulates the aggressiveness of TNBC. The present BRCA1 mutation is associated with DNA sensitivity to platinum-based chemotherapy or to poly (ADP-ribose) polymerase (PARP) inhibitors due to homologous recombination (HRD) deficiency. Another positive prognostic factor is the presence of Tumor-Infiltrating Lymphocytes (TILs) > 50% for the immunomodulatory type, lymphocyte infiltrate being considered the TNBC pattern with the best prognosis in the absence of any treatments. Furthermore, the presence of TILs in the tumor after NAC is associated with a more favorable evolution. The LAR subtype is enriched in AR and all cases of LARs exhibit a mutation in the kinase domain of PIK3CA, exhibiting a high sensitivity to PIK3CA inhibitors ,32,33,34Analyzing TNBC Lehmann subtypes, Santonja et al. demonstrates that the LAR subtype is the least proliferative and manifests the highest chemoresistance but this fact is not a negative prognostic factor if it is associated with AR-positives. The results regarding the prognosis of the LAR subtype, however, remain controversial, being associated with both the most favorable and the most unfavorable prognosis in different clinical trials. As evidenced by the Phase II trials, the TNBC subset with positive AR will benefit from antiandrogens treatment ,36.The BL1 subtype is characterized by sensitivity to chemotherapy, including platinum agents. Even if the results of the phase II studies are controversial, the homologous recombination deficiency (HRD) has been associated with a higher response to platinum agents. The BL2 subtype is reached in angiogenic factors, so it may respond to treatment with vascular endothelial growth factor receptor (VEGFRs) inhibitors, Orantinib, an anti-angiogenic agent that targets other receptors in this subtype, demonstrating a favorable response in combination with docetaxel in cancer cases of metastatic breast showing anthracycline resistance. Subtype BL2 has the lowest pCR after neoadjuvant chemotherapy ,37,38.The triple negative breast cancer represents one of the most interesting fields of interest in research, considering the lack of therapeutic resources that will lead to a significant improvement of the prognosis of this subtype of the disease ,40.TNBC is a heterogeneous disease with numerous subtypes involved in prognosis and response to different types of therapies. Recent research concerns have taken into consideration the evaluation of the subtypes that benefit from platinum-based chemotherapy and for which standard anthracycline and taxane-based chemotherapy offers a maximal response. Both PARP inhibitors in cases with mutant BRCA and androgen receptor inhibitors, treatment with sacituzumab govitecan (an antibody-drug conjugate) and PI3K/AKT and PD-L1 inhibitors are among the topics of interest. Sacituzumab Govitecan, a metabolite of irinotecan, has shown promising results in the ASCEND Phase III trial, with response rates of 33% in TNBC patients treated intensively. Even if PARP inhibitors have already shown efficacy in the case that germline BRCA mutation is detected, the OLYMPIA trial will elucidate the role of PARP inhibitors in BRCA mutant tumors and stratify patients who will benefit from this treatment. Immunotherapy is becoming an increasingly important component of therapeutic associations with PARP inhibitors. Based on the idea that PARP inhibitors in combination with checkpoint inhibitors modulate response to tumor microenvironment therapy, the therapeutic associations between immunotherapy and PARP inhibitors are intensively studied. The KEYNOTE-022 trial evaluates the association of the efficacy of the addition of pembrolizumab to standard non-addictive chemotherapy based on platinum and taxanes. Combination with veliparib, a PARP inhibitor compared to chemotherapy, did not benefit the pCR rate, but carboplatin AUC6 demonstrated superiority in pCR in the BrigTness trial. However, these strategies remain options in the recurrent or metastatic settings, and chemotherapy still remains the basis of systemic treatment in TNBC ,42,43,44Several promising new treatment options are undergoing active evaluation in many clinical trials. Among these strategies such as PARP, MEK, AKT pathways inhibition and the association of checkpoint inhibitors with chemotherapy, the most promising research method include radiomic analysis. In this context, non-invasive identification of treatment response predictors for TNBC identified from medical images becomes a priority. Identifying valid and accessible biomarkers to predict the benefit of each therapeutic strategy is one of the directions with the greatest impact in the treatment of TNBC to which radiomics can make a valuable contribution ,46.Experimental preclinical models can accelerate new molecular target identification, thus improving therapeutic efficacy. Patient-derived xenografts (PDX), due to their genomic and transcriptomic fidelity to the tumors from which they are derived, are able to improve preclinical testing of target drug combinations in translational models. Despite previous development of breast PDX and TNBC models, those derived from patients with demonstrated triple negative breast tumors are lacking.3, by the PET-CT image parameters acquisition using 18F-fluorodeoxyglucose (18F-FDG) at 45–60 min post-injection. The analysis of the results also aims the standardization of the data acquisition and features extraction in order to correctly identify the five subtypes of TNBC using solid and reproducible radiomic models [The use of hybrid imaging in radiomic analysis was applied on a PDX model by TNBC in order to implement this method in clinical practice. With the help of preclinical models developed on mice, concepts based on radiomics that can be implemented in daily clinical practice will be proposed. The limited utility of tumor cell lines established in refining preclinical models in the context of new knowledge related to tumor heterogeneity has made it necessary to use transplantable tumor xenografts, PDX models being superior for this purpose. A study that analyzed gene expression of 93 TNBC in order to correlate it with the five subtypes of TNBC aimed to evaluate the reproducibility of radiomic models in PET-CT imaging in preclinical settings. The method included evaluation of tumors with volumes varying between 100 and 450 mmc models ,48.Breast cancer is the most commonly diagnosed cancer among women and the second leading cause of cancer death. In an ERA when medical imaging is increasingly used for diagnostic and evaluation of response to oncological therapy, identifying prognostic and predictive biomarkers of post-therapeutic evolution is becoming increasingly important .The development of radiomics, which can extract quantitative characteristics from the volume of interest (VOI) delineated from medical images including shape/size, intensity and texture, has also benefited from translational research in breast cancer. In the case of breast cancer, radiomic analysis demonstrated the ability to differentiate malignant tumors from benign tumors, to identify molecular subtypes, to predict certain radioresistance and chemoresistance factors, to predict malignancy and to anticipate early the response to neoadjuvant chemotherapy (NAC) .Radiomic analysis was initially validated in lung cancers, but the need for an accurate diagnosis with the reduction of false positive US, mammography, digital breast tomosynthesis (DBT) and MRI examinations are methods desirable in breast cancer radiomics research. An increased predictive performance was demonstrated using tumor entropy as a feature extracted from MRI imaging and DBT, a new technology with promising results especially in the case of women with dense breasts. Implications of radiomics for breast cancer screening are major given the anxiety effect of a potential cancer diagnosis and a useless biopsy .Avanzo et al. performed a systematic review focused on the use of artificial intelligence (AI) in medical imaging, based on scientific articles published in Italy. The authors also assessed the areas of interest in which AI was used. In a second phase of the analysis, the AI4MP working group dedicated to artificial intelligence from the Italian Association of Physics in Medicine (AIFM) also performed an analysis of the results from the literature. Excluding reviews and articles published outside the 2015–2020 period, the authors identified 122 publications in Pubmed and 46 studies in the working group. Cancer was the subject of 25% of AI studies and MRI was the most commonly used diagnostic method for radiomics. The authors note a significant increase in interest regarding AI in medical imaging, especially after 2018 .The Italian MAGIC-5 trial aims to implement a database that facilitates the diagnosis of a CAD algorithm, based on the digitization of mammography images. Within the project, 3369 images obtained from 967 patients were digitized. The classification of images was based on the type of lesion, morphology and pathology of the breast, also developing a graphical interface to facilitate image analysis and their use as a basis for radiomic analysis or classification using neural networks, but also for epidemiological studies. Given the large amount of data collected in screening projects from different geographical areas, expanding and interconnecting the network will be a challenge for the future .In an attempt to eliminate the operator-dependent factor that affects the diagnostic capacity of Contrast-Enhanced Spectral Mammography (CESM), Fanizzi et al. propose a CAD, based on the features extraction from low-energy and recombined images. The study used 48 ROIs obtained from 53 patients, evaluated by previously trained Random Forest type algorithms. The authors select only significant radiomic features for the building of the diagnostic model. The radiomic algorithm demonstrates an improved diagnostic capacity by 8% compared to the human subjective examiner, the specificity and selectivity being 87.5% and 91.7%, respectively. Massafra et al. analyzed 58 ROIs from 53 patients extracting 464 radiomic features, including both characteristics obtained from original ROIs and Haar decomposition image gradient. With a specificity of 88.37% and a selectivity of 100%, the authors demonstrate the ability of the radiomic model to discriminate between benign and malignant tumors. In this case, the Principal Component Analysis (PCA) was used to reduce the dimensions in the classification scheme ,53,54.Radiomics was also proposed as a method for early evaluation of the oncological neoadjuvant therapy results, with background parenchymal enhancement (BPE) parameter from breast MRI images being evaluated for the predictive potential. Thus, the authors want to evaluate the ability of BPE to become an imaging biomarker with a predictive role of the response to therapy in breast cancer. The study benefited from the experience of three expert imagist physicians who evaluated MRI images obtained from 80 patients before and after the completion of chemotherapy, but also at 3 months after surgery. BPE reduction was significantly associated with the administration of the first anthracycline/taxane-based chemotherapy cycle, being more significant than in the case of anti-HER2 therapy. Another factor associated with BPE reduction after initiating neoadjuvant therapy was tumor size. Analyzing the BPE obtained from breast MRI images, La Forgia and collaborators highlight the potential of the method to predict early the response to therapy but also mention the potential of including radiomic analysis in the algorithm for early prediction of response to neoadjuvant therapy in breast cancer .Medical imaging is essential both in diagnosis and staging and in treatment planning and monitoring during the course of the disease. At this time all imaging methods involved in the management of breast cancer are associated with radiomic analysis. In an analysis that synthesizes data regarding the use of radiomics in breast cancer focused on MRI, mammography and DBT, Lee and collaborators identify a majority (16 studies) from a total of the 25 radiomic studies considered representative for breast cancer. Four studies used features extracted from the US, four were associated with mammography and one with DBT. The number of features extracted varied greatly . Entropy, textural and gray level matrix features are the most commonly used radiomic features. The radiomic score (rad-score) and the radiomic nomograms are mentioned in two and three studies, respectively. Of note are the studies of Braman et al. who approach the identification of radiometric features extracted from peritumoral DCE-MRI to predict the response to NAC and anti-HER2 + target therapy for the HER2 + subtype. Four of the twenty-five studies aim to predict the response to therapy and five studies aim to predict therapeutic failure by lymph node metastasis (three studies) and local recurrence (two studies). Radiomic and Rad-score nomograms were more commonly used in predictive models than in diagnostic ones ,57,58.The use of CT imaging in radiomic analysis related to breast cancer is associated with a relatively small number of studies, probably justified by the limited value of CT in diagnosis and the superior sensitivity of MRI and PET/CT in the detection of lymph node metastases. However, Yang’s study demonstrates 89.1% and 88.5% accuracy in assessing lymph node metastases in the test, respectively, of the validation cohort in a radiomic study using CT imaging. Piñeiro-Fiel evaluates 20 publications that propose the use of PET-associated radiomics in breast cancer, most of them (75%) extracting images from PET images alone, and the rest of the studies being dedicated to hybrid imaging (PET-MRI (20%) and PET-CT (5%)). The study by Antunovic et al. proposes PET-CT radiomics for the prediction of pCR after NAC for patients with locally advanced breast cancer. The analysis also identifies HER2 + and TNBC subtypes as being associated with an unfavorable response. Roy et al. proposes a radiomic analysis on patient-derived tumor xenografts (PDX) to optimize the radiomic signature so as to obtain a robust FDG-PET signature in order to predict response to therapy. In contrast to MRI, DBT and mammography studies, in this case of PET radiomics, only 20% of the studies aim at diagnosis and tumor staging. Most cases in which PET radiomics is proposed for the management of breast cancer (45%) are associated with the prognostic correlation of extracted features or feature sets ,60,61.An association method study investigated the role of optoacoustic imaging combined with gray-scale ultrasound (OA/US) for molecular breast cancer subtypes detection. Using the Kruskal–Wallis test, US and OA/US the molecular subtypes of breast cancer were identified. With the support of two methods—OA analysis combined with the US grayscale, the difference between luminal subtypes and TNBC and HER2 was evaluated. The same favorable results in differentiating between the TNBC and HER2 positive breast cancer were obtained in a retrospective analysis by Dogan and collaborated on a lot of 532 cases of breast cancers in 519 patients with molecular markers available ,63.Radiomic signatures extracted from contrast-enhanced magnetic resonance imaging (EC-MRI) also demonstrated the possibility of evaluating the status of breast cancer receptors in a study of 143 breast cancer patients for assessing breast cancer receptor status and subtypes. Tumors were manually segmented and subsequently the radiomic analysis included features such as first-order histogram co-occurrence matrix, run-length matrix, absolute gradient and tumor geometry. Significant radiomic features were selected and the patients were divided into a training set and a validation set. The radiomic analysis proved an accuracy of 79.4% for the differentiation of the luminal A and luminal B subtypes. For the luminal B differentiation from TNBC the accuracy of the method was 77.1%. The authors conclude that breast CE-MRI imaging may be the basis of radiomic analysis in order to detect the molecular subtypes of this type of cancer .Another study aims to determine the value of the surrounding tumors parenchyma enchancement included in the analysis, simultaneously with tumor analysis of DCE-NMR images. Identifying images obtained from 84 women diagnosed with 88 invasive breast carcinomas, the authors proposed the evaluation of the images by both an expert imagist physician and by radiomics analysis. In total, 85 features extracted from the tumor and from the surrounding parenchyma were analyzed. A reduced number of radiomic features were selected as significant and a predictive model based on support vector machines was created. The radiomic features extracted from the tumor region images as the only method of evaluation proved inferiority compared to the case where the parenchyma enchancement characteristics were also analyzed. Among the most useful features for predicting TNBC were the textures and heterogeneity of background parenchymal enhancement .To test the power of a radiomic model in making a differential diagnosis between TNBC and non-TNBC breast cancer using preoperative CT, a retrospective study was proposed that included 200 non-TNBC patients and 100 TNBC patients. Of these, 180 cases were used in the discovery cohort and 120 in the validation group. Five radiomic features were identified as predictive to discriminate the TNBC subtype from non-TNBC. The mean predictive value for TNBC was identified as 0.881 and 0.851 in the discovery case group and in the validation group, respectively. The study demonstrates the ability of a radiomics signature based on preoperative CT imaging to identify TNBC from other molecular subtypes of breast cancer. Using a radiomic signature based on 15 quantitative features extracted from DCE-MRI images of breast cancer, Ma and collaborators were able to make a differential diagnosis of TNBC/non-TNBC. In this study, ROIs were automatically segmented by a deep learning algorithm and subsequently validated by two radiologists ,67.Based on radiomic features extracted from images from 120 breast cancer patients and manually delineated tumors (90 non-TNBC and 30 TNBC), Zhang et al. were able to identify TNBC and differentiate it from other types of breast cancer by identifying four radiomic features  that are different between TNBC and non-TNBC breast cancers. Triple negative tumors are more round and regular (less concave), with increased gray density and low skewness .Differential diagnosis of TNBC with fibroadenoma is sometimes difficult, TNBC often presents in breast ultrasound a benign morphology. A study that aims to use the US for differential diagnosis between TNBC and fibroadenoma by radiomic analysis included 715 fibroadenomas, 186 TNBC, all cases pathologically confirmed. In total, 730 features were extracted from acquired images . Radiomic analysis highlights favorable results, even for lesions in the three or four BI-RADS category, probably considered benign or suspected to be malignant by expert imaging physicians. In the future, after overcoming the problems related to standardization, radiomic analysis is expected to reduce the number of biopsies for false-positive imaging diagnoses .Another study that aims to evaluate radiomics analysis in the differential diagnosis uses images from 169 tumors (84 benign fibroadenomas and 85 TNBC tumors). After tumor segmentation using the level-set method, radiomic texture features are analyzed. Both conventional morphology and multiresolution gray-scale invariant texture feature were evaluated in the study. Computer-assisted diagnostics (CAD) uses best-fitting ellipse, gray-level co-occurrence matrices and the ranklet transform methods. The authors concluded that the use of radiometric texture features extracted by ranklet transformatiom can be successfully used in differential diagnosis between fibroadenomas and TNBC .Another research direction in TNBC radiomics is the evaluation of the method’s ability to analyze intratumoral and peritumoral regions using DCE-NMR, in order to predict the complete pathological response (pCR) to NAC. For this purpose, 117 patients who received NAC, were included in the study that analyzed the intratumoral and peritumoral regions of DCE-NMR scans in T1 sequence. After VOI segmentation, 99 radiomic textural features were subsequently extracted. The training set included 78 images aiming at the training of multiple machine learning classifiers, in order to predict the probability of pCR for other newly diagnosed patients. The evaluation lot included 39 patients. In a second stage of the study data related to HR status and HER status were included.The results highlighted the concept that a set of combined intratumoral and peritumoral radiomic features lead to superior results, the HR+, HER2, non-pCR subtypes being characterized by higher peritumoral heterogeneity during initial contrast enhancement. TNBC and HER2 + tumors are associated with an enhancement pattern within the peritumoral regions for the therapy non-responder cases. The authors concluded that independently of the classifier choice the radiomics analysis of the DCE-NMR images demonstrates the possibility of predicting the response to NAC before the treatment whether or not we know the status of the receptors .Until the study of Koh et al., dynamic contrast-enhanced radiographic (DCE) MRI analysis of the entire tumor  is not known to have been used to evaluate the prognosis of TNBC. This study aims not only to identify the prognostic power of the radiomic model proposed, but also to validate it for various types of MRI scanners. Data were extracted from 231 cases of TNBC ranging in age from 23 to 88 years. Out of a total of 3995 radiomic features through 10 fold cross validation for LASSO, 32 features were finally selected and a radiomic score (Rad-score) was generated. It should be noted that seven features were selected from the gray level co-occurrence matrix (GLCM), 24 from gray level run length matrix (GLRLM) and 1 from histogram analysis. The size of the pathological invasion, lymphovascular invasion, number of metastatic axillary nodules and type of surgery are features identified as predictive in the clinical model. The Rad-score and the clinical model were more accurate in predicting the clinical model than the clinical model alone, but external validation on other MRI scanners did not confirm the superiority of the radiomic over the clinical model .A multicenter study based on radiomic features extracted from the US that included 486 TNBC cases proposed the validation of a nomogram that included a radiomic Rad-score and clinicopathological criteria to predict DFS after surgery. Elevated values of the proposed Rad-score from greyscale ultrasound features were correlated with worse outcomes. The nomogram had superior predictive power to the clinicopathological marrow and the number-based prediction of metastatic lymph nodes. The authors conclude that the addition of clinicopathological data to the radiomic model increases the power of prediction compared to any of the independently evaluated models .Early recurrence after NAC in TNBC was successfully predicted by the radiomic model based on pre- and post-NAC MRI imaging. Including 147 patients divided into the training set (104 cases) and the test set (43 cases) and a deep learning algorithm for automatic tumor segmentation from contrast enhanced MRI images, the study proposed 3 radiomic models  and a model with clinical parameters. Recurrence 3 years after NAC was accurately accurate when using both pre- and post-chemotherapy features .The correlation between radiomic features and the level of Tumor-Infiltrating Lymfcite (TILs) identified in patients diagnosed with TNBC proposed by Yu and colleagues aims to identify the early identification (from mammography images) of predictors of response to chemotherapy and immunotherapy in TNBC. 204 features including morphological, textural, and greyscale features were extracted from tumors delineated on mammogram images and statistically correlated with tumor TILs. A cutoff value of 50% was used to evaluate the “low” and “high” values of the TILs. The study identified 6 significant radiomic features  between “low TILs” and “high” TILs. The prognostic and predictive value is given by the concept that tumors with “high” TILs are associated with a higher rate of complete pathological response and higher survival rates .The main radiomics studies involving both different non-medical imaging methods and different clinical endpoints have been summarized and presented in a table .Radiomics, a relatively new but promising translational research field, adds value to precision oncology, with TNBC already benefiting from the results. Differentiation between fibroadenoma and TNBC, identification of molecular subtypes from US, MRI and other medical imaging and early prediction of response to NAC is already validated applications of radiomics. Future research in radiomics with major clinical applications would target sensitivity to platinum-based chemotherapy, target therapies and immunotherapy response prediction, in order to improve the prognosis of this aggressive breast cancer subtype. Thus, we estimate that radiomics will become a key player in the precision oncology of TNBC. The correlation between radiomics markers, response to different therapeutic protocols, prognosis and molecular subtypes of TNBC, radiomics will offer the perspective of treatment personalization with minimal costs. Already having clinical results regarding the benefit of combination platinum-based chemotherapy-PARP inhibitors—immune checkpoint inhibitors, radiomics models can provide predictive biomarkers of therapeutic response in order to stratify the oncological therapy and to offer in each case of TNBC the best therapeutic option. Deep learning algorithms tend to replace the classic supervised and unsupervised radiomics, but radiomics is easier to implement and we estimate that the method will still play an important role in translational cancer research. In the ERA of “big data” we expect the rapid initiation of studies that will translate radiomics into the current clinical oncology practice of TNBC. If radiomics combining standard screening and diagnostic methods seems to be more focused on differential diagnosis and staging, MRI, PET and hybrid PET-CT and PET-MRI in association with radiomics score and nomograms tend to be key players in precision diagnosis, contributing to the stratification of patients and the identification of potential candidates for each therapeutic agent, being key elements in future precision TNBC therapy. Radiomic analysis, especially by MRI and mammography, is estimated to improve the specificity and maintain a high rate of diagnostic sensitivity, thus reducing the necessary biopsies, but will also open new horizons in the precise selection of patient groups, candidates for the omission of surgery after complete response to NAC.


Different aggregate gradations of asphalt concrete possess dissimilar skeleton structures, leading to diverse macroscopic and mechanical characteristics. Acoustic emission (AE) technology can realize real-time monitoring of the whole damage evolution process of materials. The objective of the present investigation was to demonstrate the fracture characteristics of asphalt concrete with three types of aggregate gradations, including dense-graded asphalt concrete (AC), stone mastic asphalt (SMA), and open-graded friction course (OGFC) under indirect tensile load on account of the acoustic emission (AE) technique. The Marshall compaction method was used to prepare specimens, and the indirect tensile test (IDT) and AE monitoring were conducted simultaneously at different temperatures. The corresponding AE parameters containing energy, cumulative energy, count, and cumulative count were adopted to characterize the fracture process of asphalt concrete with different aggregate gradations. The impact of temperature on the damage characteristics of asphalt concrete was also assessed. Test results indicated that the AE parameters could effectively classify the damage stages of asphalt concrete, and specimens with different aggregate gradations exhibited different AE characteristics during failure processes. The combination of AE parameters and cumulative AE parameters can accurately characterize the damage characteristics of asphalt concrete. SMA specimens possessed the best overall performance among these three types of asphalt concrete in terms of the variations in energy and cumulative energy at different temperatures. The findings obtained in this study can provide a practical AE-based evaluation approach for demonstrating the fracture mechanism of asphalt concrete with different aggregate gradations. Asphalt concrete is a heterogeneous material consisting of multiple components, which can be divided into dense-graded asphalt concrete (AC), stone mastic asphalt (SMA), and open-graded friction course (OGFC), according to the varied compositions of gradation . These tThe mechanical performance of asphalt concrete is usually characterized by a resilient modulus, flow number, and indirect tensile strength ,4. ConveHowever, limited work has been undertaken to validate the applicability of AE technology to characterize the damage mechanisms of asphalt concrete . Arnold Previous research has only focused on one type of aggregate gradation to evaluate the AE characteristics of asphalt concrete during the failure process, where the effects of aggregate gradations on fracture characteristics of asphalt concrete with AE parameters have been neglected. The aggregate gradation has a significant impact on the mechanical properties of asphalt concrete ,27. MoreIn this study, specimens with three aggregate gradations containing AC, SMA, and OGFC were prepared in line with the Marshall compaction method. Indirect tensile tests (IDT) and AE tests were conducted simultaneously to explore the impact of aggregate gradations on the AE parameters, including energy, cumulative energy, count, and cumulative count during the damage process. Moreover, the temperature effect on asphalt concrete with different aggregate gradations was also demonstrated based on AE parameters.The aggregates and filler were both derived from limestone, and the specific indicators are listed in Asphalt concrete with three types of aggregate gradations containing AC, SMA, and OGFC was prepared, and the maximum nominal size of each type of aggregate gradation was 13 mm. IDT was conducted with a universal testing machine shown in  producedFirst, the SR150M ceramic AE sensor with frequency bands ranging from 60 kHz to 400 kHz and a resonant frequency of 150 kHz was immobilized on the side of the specimen by adhesive tape and coupled with grease. The pencil lead break was then carried out to ensure a favorable coupling condition between the sensor and specimen, after which the load was applied to the specimen and the AE parameters containing the energy and count during the fracture process were recorded by the AE instrument. The whole process is schematically presented in The fracture behavior of the three types of asphalt concrete was characterized by AE parameters containing energy, count, amplitude, rise time, and duration. It has been reported that all these parameters exhibited similar variations during the damage process of asphalt concrete . In thistF is the real-time load and mF is the maximum load.Three types of asphalt concrete with different gradations, including AC, SMA, and OGFC, were prepared. The nominal maximum size of an aggregate with different gradations was 13 mm, and the corresponding temperature of the IDT was set to 25 °C. AE parameters, including energy and count, were used to characterize the fracture behavior of specimens with different aggregate gradations. The fracture process of asphalt concrete can be split into several stages in terms of the variations in the AE parameters. The loads were uniformly transformed into load levels that intuitively characterized the correlation between mechanical and AE parameters. The value of load level can be calculated by Equation (1).The AE energy distribution of AC specimens is presented in As seen in From a structural point of view, the traditional continuous dense-grade asphalt mixture is the suspend-dense structure, whose strength mainly derives from the cohesive force of the asphalt binder to aggregates. The asphalt concrete was subjected to a tensile force under indirect tensile load. In the initial stage, the asphalt binder and aggregate exhibited favorable cohesion and strong integrity, the cracking activities were not vigorous, and the phenomenon that the AE energy and count was at a relatively low level during the first three stages also confirmed this statement. When the load exceeded the tensile strength of specimens, final brittle fracture emerged, and the drastic increase in the AE energy and count in the final stage also authenticated this analysis.As shown in The cumulative count distribution of SMA specimens is observed in SMA specimens belong to the discontinuous gradation in grading types, and the gaps of the skeleton composed of coarse aggregates are filled with fine aggregates and asphalt binders in reasonable proportions, leading to the formation of the stable structure with an excellent packing effect. The internal friction and cohesion emerged to resist the displacement of asphalt concrete when the load was applied. The significant difference in AE characteristics between SMA and AC specimens lied in that the energy and count of SMA specimens were more uniform than those of AC specimens, and there was no drastic increase in AE parameters compared with AC specimens throughout the IDT process, which is attributed to the stable skeleton-dense structure.As seen in As shown in OGFC specimens belong to the continuous open gradation in gradation type, and it is a skeleton-void structure with large air voids, where the structure is composed of a large number of course aggregates and a small number of fine aggregates. The voids between the skeleton cannot be adequately filled by fine aggregates, which leads to the inability to form a strong interlocking effect between the particles. The strength of OGFC specimens mainly relies on the cohesive force between the binder and aggregates. The air voids of OGFC specimens are relatively large, and the contact state between particles is stone-to-stone, making the OGFC specimens prone to stress concentration in the IDT process. The cracks occurred and released a considerable quantity of AE energy when the stress concentration accumulated to a critical extent. Thus, the energy and count mutation points of OGFC specimens were intermittently distributed throughout the IDT process.The combined analysis of AE parameters and cumulative AE parameters enables the accurate classification of the fracture process in asphalt concrete. These three types of asphalt concrete exhibited different fracture characteristics during the failure process owing to their dissimilar skeletal structures. The internal damage of AC specimens developed slowly in the early loading stages but accumulated sharply in the final stage until they were completely destroyed. The SMA specimens displayed a steady development of internal damage under loading until the final fracture. The OGFC specimens were accompanied by localized damage throughout the failure process due to stress concentration.t is the loading time and ot is the overall loading time.Energy and cumulative energy were employed to assess the influence of testing temperature on the damage characteristics of specimens. The IDT and AE tests were conducted simultaneously at the temperatures of −10 °C and 25 °C, respectively. Time data were converted into time levels to characterize the variation in AE parameters visually with temperature. The value of the time level can be calculated by Equation (2).As seen in As mentioned above, the AC specimens possess the suspend-dense structure, whose strength mainly derives from the cohesive force of asphalt binder to aggregates. The change in temperature leads to the variety of cohesion between binders and aggregates, which affects the mechanical performance of specimens. Thus, the change in temperature significantly affects the AE parameters of asphalt concrete during its failure process.The cumulative energy distribution is presented in The strength of SMA specimens mainly derives from internal friction and cohesion. The change in temperature affects the cohesion of SMA specimens to a certain extent, but SMA specimens rely more on the internal friction of the skeleton-embedded structure to bear the load. Thus, the variation in energy and cumulative energy versus time is less affected by temperature.The energy distribution of OGFC specimens is illustrated in The strength of OGFC specimens mainly relies on the cohesive force between binders and aggregates. The change in temperature leads to the change in cohesion between the binder and aggregates, causing the fluctuation in mechanical properties. Thus, the temperature shows a significant impact on the AE parameters of OGFC specimens during the IDT process.The AE technique provides a new method to estimate the temperature stability of asphalt concrete. Combining the variations in AE parameters of these three types of asphalt concrete at different temperatures, it can be seen that the AE activities at −10 °C were more intense and the internal damage of asphalt concrete developed later compared to 25 °C. In addition, the SMA specimens exhibited the best temperature stability based on the AE parameter analysis. Compared with the traditional mechanical parameters, the AE parameters were more sensitive to the internal damage of asphalt concrete, which could help us understand the fracture mechanisms of asphalt concrete comprehensively.Asphalt concrete with different aggregate gradations exhibited different fracture characteristics based on AE monitoring, and the comprehensive analysis of AE parameters and cumulative AE parameters can realize accurate identification of the damage process of asphalt concrete.The damage fracture of AC, SMA, and OGFC specimens can be divided into four, three, and four stages due to AE parameters, respectively. As for AC specimens, the fracture characteristics were manifested by the sudden fracture due to insufficient cohesion under critical load. The fracture process of SMA specimens was characterized by the stable propagation of cracks owing to the stable skeleton-dense structure. Due to the high voids content, the fracture characteristics of OGFC specimens were represented as the local failure caused by the stress concentration related to the skeleton-void structure throughout the IDT process.The energy and cumulative energy of AC, SMA, and OGFC specimens varied with temperature, and the SMA specimens displayed the best overall performance among these three kinds of asphalt concrete in terms of the distribution of AE parameters at different temperatures.In this study, the fracture characteristics of asphalt concrete with three aggregate gradations, including AC, SMA, and OGFC, under IDT using the AE technique were demonstrated, and the temperature effects of asphalt concrete characterized by AE parameters were also discussed. The most relevant conclusions are:


Understanding the type of immigration flow that maximises the expected economic benefits in the destination countries is one of the main debated topics both in the economic literature and in policy agendas worldwide. In recent years, governments have developed regulations of migration flows by adopting some form of selective immigration policy based on either human capital criteria or skill needs. Admission policies in the destination countries are likely to affect the direction and magnitude of selection as well as the socio-economic performance of immigrants. However, the relationship between quality-selective policy and immigrants’ skill composition remains largely unexplored. This paper aims to survey the existing literature on how selective-immigration policies shape the characteristics of immigrants from the receiving-country perspective. First, it introduces the main route of admissions and the theoretical models to understand how the direction of selection works; second, it discusses the theoretical models; third, it reviews the empirical works. A final concluding section briefly points out the actual findings and future avenues of work. The importance of the nexus between policies and migration outcomes has gained increasing attention both in the economic literature and in global policy agendas. Concerns about the impact of immigration raise questions on what determines the size and the composition of immigrant inflows. Immigrants are indeed expected to positively contribute to economic growth by supplementing skills in relatively short supply and enhancing the labour force. Understanding the type of immigrants that maximises these expected economic benefits is one of the main debated topics. Figure The rise in international migration to developed countries has been marked by unprecedented institutional and technological changes, such as ageing, new skills needs and growing specialisation in human capital and digital-intensive activities. These current shifts have remarkably affected the migration patterns in terms of both demographic and skill trends. Between 2000 and 2016, the number of highly educated immigrants increased throughout the OECD countries by around 20 million OECD, . The demEconomic literature has devoted attention to the selection and sorting of migrants across countries, considering migration as the result of spatial differences in the net returns to factor supply and the response to labour market disequilibrium  pay higher taxes, (ii) require fewer social services, and (iii) integrate faster than unskilled immigrants Borjas, . MoreoveThere are substantial differences across receiving countries in selecting skill-based immigrants. Traditionally, there are two main approaches for skill-based admissions: supply-led systems and demand-driven policies. A third approach is rising recently to meet the need to select immigrants for their education and skills as well as for their ability to fill specific labour market’s needs , such as (n) is to decrease migration costs (C) at all schooling levels  for individual i is Self-selection is central to understanding how a policy influences the skill composition of the migration flow. Belot and Hatton , for insQ) is defined as the ratio of high (Q). Instead, Bellettini and Ceroni  consequences their policies may generate. An important question could address how the impact of new shocks, e.g. Brexit or the Covid-19 pandemic, has put under pressure the “traditional” selective systems.


Over the past decade, the Advanced Practice Provider (APP) role has expanded into various care settings. The literature confirms that APPs contribute positively to the ICU setting, where better patient outcomes are noted, and they are seen as a safe adjunct to the ICU team. The VA recognizes the need for a more significant presence, and practice-based variations are considered crucial as restructuring goals are established. In 2014, Edkins et al. recognized the need for APPs in the burn setting as the number of residents declined. They stressed appropriate utilization and ongoing educational opportunities to develop the role in burns further.This project was conducted by establishing a protocol within our burn referral call system to adequately and efficiently ensure accurate data is accumulated and leveraged to make staffing decisions. Implementation of the protocol began in January of 2018 and is well established. The primary purpose of the protocol is to efficiently store and transfer patient data to make informed decisions across both clinical and administrative departments. The Customer Relationship Management (CRM) System, Salesforce, was the primary software to implement and maintain this process.For three years, a total of 42,460 referral calls came through our burn call system. The number of patient calls that required admission to a regional burn center totaled 15,293. 70% of total patient referral calls came during the hours of Noon-Midnight; similarly, 72% of admission patient calls came during Noon-Midnight. Hourly trends were similar for both total patient call volume and admission patient referral call volume as they both had the highest number of referral calls between the hours of Noon-Midnight. The majority (32%) of total patient referral calls came in during earlier days of the week (Monday and Tuesday), while the majority (30%) of admission patient referral calls came in during the later days of the week (Friday or Saturday).Our study demonstrates the benefits of implementing a collaborative protocol that allows sharing data and information across all facets of a burn center. Opportunities for additional studies include implementing similar protocols for administrative staffing and analysis of patient outcomes to see how staffing utilization has affected patient care.