There is no unanimous consensus on the clinical features to define breakthrough cancer pain (BTcP). The current project aimed to investigate the opinion of a panel of experts on cancer pain on how to define, diagnose, assess, treat and monitor BTcP.n = 90) previously selected from Medical Oncology Services, Radiation Oncology, Palliative Care/Home Care Teams, and Pain Units. The study intended to seek experts’ consensus and to define a set of recommendations for the management of BTcP.A two-round Spanish multi-centre exploratory Delphi study was conducted with medical experts , although not necessarily with opioids (only 30 %); there must be exacerbations (98.9 %); the duration of each episode should last <1 h (70 %); the intensity of pain ≥7 out of 10 (67.8 %); and the number of flares per day should not be less than four. All participants supported the use of the Davies algorithm for the diagnosis. The use of a ‘Patient Diary’ was highly recommended. The optimal treatment should have a rapid onset, a short-acting analgesic effect (1–2 h) and transmucosal nasal or oral administration. It was considered very important to develop protocols for the management of cancer pain.The present Delphi study identified a set of recommendations to define, assess and monitor BTcP. In 1990, Portenoy and Hagen published an article about a specific pain syndrome that is known as “irruptive pain”, or by the term “breakthrough pain”. Breakthrough pain has been defined as a ‘transient exacerbation of pain that occurs either spontaneously, or in addition to a stable and adequately controlled background pain, generally treated with major opioids’ .The requirement of background pain to be controlled allows us to distinguish BTcP from end-dose pain flares and those flares that occurred during the drug analgesics titration of the background pain. To emphasize these differences, Davies et al.  defined A working group from the European Association of Palliative Care suggested, for linguistic reasons, to replace the term “breakthrough pain” with other terms such as “episodic pain” or “transitory pain” . HoweverIn 2012, several Spanish medical societies––Sociedad Española de Oncología Médica (SEOM); Sociedad Española de Oncología Radioterápica (SEOR), Sociedad Española de Cuidados Paliativos (SECPAL) and Sociedad Española de Dolor (SED)––adopted a consensus document in which the term “breakthrough pain” refers to a sudden and transient exacerbation of pain of high intensity and short duration , which appears over the baseline of a stable persistent pain, when this has been reduced to a tolerable level by the fundamental use of strong opioids . This deTo consider that baseline pain is adequately controlled, some authors assume that the average intensity of pain must be less than four on a verbal numerical rating scale (VNRS) or visual analogue scale (VAS) from 0 to 10, and the maximum number of episodes of BTcP should be three per day . HoweverDespite all this knowledge, BTcP is currently under-diagnosed and under-treated. An epidemiological study developed by the International Association for the Study of Pain (IASP) about the features of tumour pain, showed large differences among continental geographical areas in terms of the frequency of diagnosis of BTcP . Even toAround 60–90 % of cancer patients die in pain . RegardiThose facts enclosed in the definition of BTcP as well as procedures for its diagnosis, assessment and monitoring may influence the choice of a treatment and consequently patient outcomes. Hence the importance of obtaining a consensus on these issues from a broad group of experts in cancer pain.The aim of this study was to explore the opinion of an expert panel in cancer pain, regarding the clinical features to define BTcP; to understand the procedures and assessment scales and monitoring of BTcP in clinical practice in Spain; to uncover the discrepancies; and to find areas of consensus to develop recommendations for the management of BTcP.The Delphi method is commonly used to obtain the collective vision of a group of experts on a subject, and is able to extract and clarify the judgement of the group . Its pren = 21), radiation oncology (n = 19), pain units (n = 26) and palliative care/home care (n = 24).A total of 90 experienced and trained experts on cancer pain, homogenously distributed across Spain, were selected from different units: medical oncology  and was aimed to clarify the most controversial issues generated during the first round, to inquire any additional issue raised by the results of the first questions, and to agree on some general recommendations.An online application was developed to administer the questionnaires and to share all information related to the study. Participants provided their responses of both rounds of the survey directly in the online application.n, %) were provided.A descriptive study of the variables was carried out according to their type: for numeric variables, measures of central tendency and dispersion  were applied. For the categorical variables, frequency distribution tables and percentages  was used.t test to analyse the change of the responses between the two rounds. A two-sided 0.05 significance level was set.A pairedwise analysis was carried out by means of a Student’s Half of the panel understood that the patient must be taking analgesics on regular basis to achieve background pain relief, and 84 % stated the importance of an adequate control of cancer pain in the definition of BTcP Fig. a. LikewiIn the first survey, 34 % of participants recognized not to use the Davies algorithm Fig.  mainly bAround 68 % of experts confirmed to use a sort of ‘Patient Diary’. Among the parameters to be collected on the diary, the most voted were date and time of each episode, its duration and intensity, the administered rescue dose, time to/degree of pain relief, and side effects, including the recommendation to contact the doctor if more than three rescues per day were required (together with a contact phone number).To better characterize BTcP, registration of pain analgesics taken by the patient was deemed as the most important factor to be gathered on the clinical history (average Likert score of 6.7 out of 7). Indeed, this item was the most frequently asked to the patient (88.9 %) Table . Other iParticipants responded about several topics to be noted down on the clinical history of each patient and categorized their importance Fig. . Most exIn the first questionnaire, participants were asked about the ideal treatment of BTcP Fig. a. It wasIn the first round, initiation and duration of analgesia, and the route of administration were the most determinant criteria to select a drug for BTcP Table . HoweverIn the first round, and regarding the timeframe for the first follow-up visit, each period was evaluated on a Likert scale of 1–5, where 1 was “in no case” and 5 “in all cases” Fig. . After tThe Delphi technique chosen for this consensus study has been successfully used in other research studies of palliative care  to estabThere is no universally accepted definition of BTcP , 19. SimBecause end-of-dose pain is the result of an inadequate dose of analgesic or a dosing interval that is too long, the analgesic regimen used to treat baseline persistent pain should be reassessed and modified as necessary. This might explain why end-of-dose pain was not considered BTcP in this study.The history of the patient with an exacerbation of cancer pain should include a diagnostic method of BTcP. Literature recommends the use of Davies algorithm Fig.  8], mod, mod8], To enable proper monitoring of BTcP, participants in the study recommend the use of a ‘Patient Diary’. Information to be mainly recorded in such a diary was the date and time of each episode, its duration and intensity, the administered rescue dose, time to relief and degree of relief, side effects, and information about the drug titration phase.Many authors suggest that BTcP should be assessed before the start of a certain therapy and afterwards, at regular intervals until an adequate pain control is achieved . Most paIn our study, the greatest importance is given to the knowledge of the opioid analgesics taken by the patient for pain, separately from those that are prescribed to control BTcP. The number of flares per day or week, their duration and intensity, the degree of adherence to treatment and its efficacy, and the type of breakthrough pain  were other factors stated by the experts. This was aligned to that reported by literature. Previous studies report that a proper assessment of breakthrough pain should include frequency and duration of episodes, intensity and type of pain, precipitating factors, previous medication and effectiveness of rescue therapy .Surprisingly, there is no unanimity about the impact of BTcP on the quality of life of patients. Some studies show the great impact that BTcP has on mood and functional status . BTcP isBreakthrough pain is not a single condition, but an assortment of very different conditions. Professionals identified the importance to develop protocols for the management of cancer pain, including BTcP. Primary care and nursing should be also involved in the preparation of such protocols.Regarding the characteristics of the treatment, participants believe that the ideal therapy of BTcP must meet these conditions: a short-acting effect , the analgesia lasts as longest as 1–2 h, and the route of administration is transmucosal . In the present study, immediate-release fentanyl is chosen by the majority of specialists as the drug of choice to treat BTcP. This is due to its pharmacokinetic properties as well as its rapid onset of action. The selection of one or another presentation and route of administration  will depend primarily on the clinical situation and the personal preferences of the patient. In the literature, the treatment of BTcP involves strategies such as the treatment of cancer disease, modification of the baseline analgesic treatment, non-pharmacological interventions, and an appropriate rescue medication . The ideAccording to the presentation “New approaches to the diagnosis and treatment of breakthrough cancer pain consensus document” at the XIV Simposio de Revisiones en Cáncer (Madrid), the rescue dose is not related to the baseline opioid dosage. Our panel believes it is essential to carry out titration of the rescue medication, which can be done at patient’s home by means of a previously drafted set of instructions, and recording the recommended information in the ‘Patient Diary’ in a particular manner during this phase: number of flares per day, any need to repeat the dose because of insufficient pain relief, and the degree of relief obtained. In this way the efficacy and tolerability of the treatment can be evaluated and any changes in the nature of BTcP can be recognised . We recoRegarding the characteristics that best define BTcP, there was a broad agreement that the baseline pain should be controlled, but not necessarily with opioids; there must be exacerbations; the duration of the episode should be less than an hour, and the intensity of pain greater than 7 out of 10.There was no agreement about whether the number of daily episodes of BTcP has to be less than four to consider that the baseline pain is controlled. The need to treat background pain with opioids was also a matter for controversy.There is consensus in considering that BTcP is not the same as end-of-dose effect.Questions encompassed in the Davies algorithm should be asked to diagnose BTcP.The best tool for assessing and monitoring BTcP is the ‘Patient Diary’, either as a standardized document, or in the form of some generic recommendations on patient outcome records for the referral to the doctor. This should record the date and time of each episode, duration and intensity of each flare, administered rescue dose, time to pain relief, degree of relief and side effects. ‘Patient Diary’ should also include instructions for titration, the recommendation to contact the doctor within the first 48 h of initiating the therapy and/or if more than three rescues per day are required, and a contact phone number. The diagnose of BTcP should be logged in the patient’s clinical record. Protocols for the diagnosis, assessment and monitoring of BTcP are needed and these should take into account the roles of all the professionals involved, including primary care and nursing teams.The optimal drug to treat BTcP should have a rapid onset of action (15 min or less), short-acting effect (≤2 h) and an easy route of administration . Fentanyl, either in its oral or nasal transmucosal form is well established as the best active substrate that fits better this profile.Drug titration can be done at patient’s home. Instructions are advised to be provided, so that the patient gathers the information from the titration phase to be included on the patient diary: number of flares per day, need to repeat the dose because of an insufficient relief from the flare, and degree of relief.


MORE Energy is a mobile health intervention which aims to reduce fatigue and improve health in airline pilots. The primary objective of this process evaluation was to assess the reach, dose delivered, compliance, fidelity, barriers and facilitators, and satisfaction of the intervention. The second objective was to investigate the associations of adherence to the intervention with compliance and with participant satisfaction. Thirdly, we investigated differences between the subgroups within the target population.The intervention consisted of a smartphone application, supported by a website. It provided advice on optimal light exposure, sleep, nutrition, and physical activity, tailored to flight and personal characteristics. The reach of the intervention was determined by comparing the intervention group participants and the airline pilots who did not participate. The dose delivered was defined as the total number of participants that was sent an instruction email. Objective compliance was measured through the Control Management System of the application. To determine the fidelity, an extensive log was kept throughout the intervention period. Subjective compliance, satisfaction, barriers, facilitators, and adherence were assessed using online questionnaires. Associations between the extent to which the participants applied the advice in daily life (adherence), compliance, and satisfaction were analysed as well. Finally, outcomes of participants of different age groups and haul types were compared.n = 251) or the control group (n = 251). Of the intervention group participants, 81 % consulted any advice, while 17 % did this during four weeks or more. Fidelity was 67 %. The participants rated the intervention with a 6.4 (SD 1.6). Adherence was not associated with compliance, but was associated with satisfaction (p ≤ 0.001). Pilots of 35 to 45 year old were significantly more interested in advice regarding physical activity than their colleagues, and short-haul pilots were more interested in advice regarding nutrition compared to long-haul pilots.A total of 2222 pilots were made aware of the study. From this group, 502 pilots met the inclusion criteria and did agree to participate. The reach of the study proved to be 22 % and the dose delivered was 99 %. The included pilots were randomized into the intervention group  contains supplementary material, which is available to authorized users. Due to disruption of the sleep wake pattern and the circadian rhythm, fatigue is inevitable in occupations where individuals are required to work when they normally would be asleep . In the Literature on computerized health education shows that the content of advice should be tailored to the individual needs and should be applicable for all subgroups within a target population , 10. AddThe usage of mobile health  has expanded rapidly during the last decade . AdditioWe, therefore, performed a process evaluation alongside our randomized controlled trial. The primary objective of this process evaluation was to assess the reach, dose delivered, compliance (dose received), fidelity, barriers and facilitators (context), and satisfaction of the MORE Energy intervention. The second objective was to investigate whether the MORE Energy intervention was associated with an improvement in relevant behavior of the participants by exploring the association between compliance to the intervention and the extent to which the pilots adhered, i.e. applied the advice in daily life. We also investigated if adherence was associated with the satisfaction of the pilots. The third objective was to investigate how the intervention suited the different subgroups within the target population. Therefore, outcome differences between pilots of the different age groups and haul types were analysed for the process evaluation items compliance and satisfaction.This process evaluation was carried out alongside the randomized controlled trial on the effectiveness of the MORE Energy intervention that aimed to reduce fatigue in airline pilots. The Medical Ethics Committee of the VU University Medical Center  assessed the study design and procedures, but according to Dutch law, this study proved to be exempt from a medical ethical review.The study population consisted of the pilots of a large internationally operating airline company. The pilots could participate in the study if they were not on sick leave for more than four weeks at the moment of recruitment and if they owned a smartphone or tablet with iOS (iPhone/iPad Operating System) or an Android operating system. After inclusion, the participants were equally randomized into an intervention group, and a control group which received a minimal intervention. Because this process evaluation addresses the MORE Energy intervention, we focus on the participants of the intervention group only.The MORE Energy intervention was developed systematically. First, a literature study was performed in order to gain insight in the latest scientific knowledge about optimal behaviour regarding disruption of the circadian rhythm and fatigue in flight crew. Next, focus groups were held to find out what medium and implementation strategy should be used to optimise compliance to the intervention. The focus groups made clear that the intervention should be easy available, appealing, and to be used by pilots of all ages and job types. Further, the advices should be made flight schedule specific and applicable for both short and long-haul pilots. To match the intervention with the legislation and the policy of the airline company, interviews with key management stakeholders were held as well.Based on the focus groups and interviews, it was decided to develop a mobile application to transfer the advices to the target population. After the development of the MORE Energy app, it was extensively pre-tested by both pilots and researchers. Based on the results of this first evaluation, the intervention was optimised where necessary.The MORE Energy app contained advices on optimal light exposure, sleep, nutrition, and physical activity, tailored to relevant flight  as well as to personal characteristics . The users could choose to consult background information in the glossary menu and the app guided them to a website to read more, or to view and listen to video and audio files concerning the different topics. Participants were encouraged to consider the advices on the app by means of two types of reminders: timed alerts (when the user did not use the app for longer than three weeks) and geofencing alerts . Screenshots of the MORE Energy app can be seen in Additional file The process evaluation items were taken from the Steckler & Linnan framework : reach, Reach is defined as the proportion and representativeness of the intervention group participants in the study, compared to the total group of potential participants . Reach wDose delivered is considered as the total amount of intervention material provided to the participants. In this study, the dose delivered was defined as the total number of participants that was sent an email containing instructions and login details to access the intervention material.Compliance is the dose that is received, and refers to the extent to which participants actively engaged with the intervention. In our study, it was objectively measured through the Control Management System (CMS) of the application. This system stored the number of advices per week requested by each participant through user authentication. Likewise, we used a web-analytic tool  to register and store the total number of page views per participant to the website of the project.The registered number of app advices of four participants proved to be more than 200. Because this was most certainly due to malfunctioning of the CMS, the registered data of these participants was excluded from the objective compliance analyses.The participants were also asked how often they had consulted the advices during the intervention  in the online questionnaire at six months after baseline. Further, participants were asked which type of advice they had predominately used  and which topics they had consulted the most .Access : 15 %Backend (synchronisation of content and flight schedules): 15 %Advice : 40 %Reminders : 15 %Website with background information : 15 %Fidelity is defined as the extent to which the intervention program was implemented as planned, representing the quality and the integrity of the implementation . TherefoThe satisfaction with the intervention was assessed through the online questionnaire at six months after baseline. First, the participants were asked to give an overall grade for MORE Energy (1 to 10). Next, they were asked to rate four statements about the usability of the intervention on a 5-point Likert scale ranging from ‘disagree’ to ‘agree’. Additionally, participants were asked if they would recommend the MORE Energy application to their colleagues, and to appreciate the effectiveness of the intervention through rating three statements on perceived effectiveness on the 5-point Likert scale.Context refers to “the larger physical, social, and political environment that either directly or indirectly affects an intervention program” . PossiblThe extent to which participants applied the MORE Energy advices in daily life was assessed through asking the participants to rate the statement “After reading the advices, I actually applied them as well.” on a 5-point Likert scale ranging from 1 ‘disagree’ to 5 ‘agree’.Regarding the first objective, descriptive analyses were performed. Differences  between participants and non-participants were analysed with t-tests for independent samples and Chi-square tests.For the second objective, associations between compliance and the extent to which the participants applied the advice in daily life (adherence) were analysed by calculating Spearman's (rho) correlation coefficients. Regarding the objective compliance, participants were divided into four groups of equal size related to the amount of compliance. Furthermore, a linear regression analysis was performed to explore the association between the level of adherence (independent variable) and satisfaction with the intervention (dependent variable). Participants who indicated not to have applied the advices in daily life, or who had a neutral opinion towards this question, were used as one reference category in the analysis.To answer the third objective, outcomes for the different age groups  and haul types (short-haul vs. long-haul) on compliance and satisfaction were analysed with t-tests for independent samples, Chi-square tests and one-way ANOVAs. Participants who flew to intercontinental destinations were considered long-haul pilots, while participants who only flew to European destinations were considered short-haul pilots.p < 0.05 was considered to be statistically significant in all analyses. Analyses were conducted with the Statistical Package for Social Sciences (SPSS), version 20.0.A two-tailed significance level of A total of 2222 potential participants were made aware of the project by means of a publicity campaign through the airline company, after which they received an email with a link to the baseline questionnaire. From this group, 522 (23 %) pilots agreed to participate. A total of 20 pilots (<1 %) did not meet the inclusion criteria. Of the remaining 502 pilots, 251 were randomized into the intervention group, and 251 into the control group. At the end of the intervention period, 148 (59 %) of the participants of the intervention group completed the process evaluation questionnaire. Baseline characteristics of the participants and the non-participants are shown in Table We sent emails containing the login details and instructions to 251 participants. One email was bounced because the email address proved not to exist. After three months, one other participant reported to have not received the instruction email. The dose delivered therefore was determined to be 99 % (249/251).It was registered that during the intervention period, 54 of the 251 participants never consulted any advice on the app. Two of these participants indicated that they wanted to drop out of the study. Five of them only consulted the website with the background information. The remaining 47 participants either did not download or use the app or website after receiving the instructions, did not receive or read the email with the instructions, or only used the glossary section of the app (consultation of the glossary was not registered by the CMS).During the six month intervention period, 68 (27 %) participants consulted the advices during one week only, 54 (22 %) consulted them during two weeks, and 32 (13 %) consulted them during three weeks. A total of 43 (17 %) participants consulted the advices on the app during four weeks or more. In total, 1677 advices were requested. The mean number of requested advices per participant was 6.8 (SD 14.0), while the median was 3 advices per participant. If the data of the four participants with outliers was included, the mean number of requested advices would have been 12.6 (SD 55.3).The CMS registered that the advices regarding the preparation for departure from home were requested the most (49 %). The advices concerned with time spent during layover (23 %) and the advices about the preparation for the return flight and arrival home (27 %) were consulted less often.In total, 32 (13 %) participants went to the website with background information. The mean number of page views of these participants was 9.2 (SD 8.6). It was determined that 27 (11 %) participants used both the app and the website. Most of the participants did use the app but never logged on to the website (68 %).Of the 148 participants that answered the process evaluation questionnaire, 62 (42 %) indicated they had never really used the MORE Energy advices, 39 participants (26 %) indicated that they had used the advices a few times, and 46 (31 %) reported to have used the advices occasionally. One participant reported to have used the advices before and during every flight. Next, of the 86 participants that had used the advices, most of them indicated that they had consulted the advices regarding layovers (70 %). Next, 49 % indicated to have consulted the advices regarding the return home, and 36 % indicated to have consulted the advices concerned with preparation before departure. Further, most of these participants pointed out that they consulted the advices concerned with sleeping behaviour (62 %) and nutrition (72 %). The advices regarding exposure to light (28 %) and physical activity (23 %) were consulted less often.After two weeks the second version of app became available for iOS: after downloading the update, participants could no longer consult all types of advices and iPhone5 users could not get access to the updated version of the app.∘ This version could not be installed automatically. Participants had to delete the previous version of the app before being able to install the new one.∘ After installation of third version, reminder alerts malfunctioned. Researchers found out this problem had most probably occurred in the Android app from the start of the intervention as well.After two months the third version of app became available for iOS to solve the problems above:Through the six month intervention period the implementation of the intervention was predominantly affected by the following . On average, the participants rated the MORE Energy intervention with a 6.4 (SD 1.6).n = 5), the advices were not applicable in daily life (n = 4), the content was already known (n = 3), or the app had too much technical problems (n = 2).The 86 pilots that indicated to have used the advices were asked what their reasons were not to consult the advices more often. The most selected reason was that the content of the advice was already known to them (58 %). Furthermore, 44 % of the participants indicated that they did not need to consult the advices anymore after a few times. Less selected reasons were technical problems with the app (12 %) and lack of usability (7 %). Out of the additional reasons reported by 24 participants, three main themes could be composed. First, nine participants reported that the advices could not be applied in daily life because that would conflict with their social obligations, both at home and during duty. Predominantly participants with young children and short-haul pilots pointed out this problem. Four participants indicated that they had simply forgotten to consult the app, or that they did not receive an alert to remind them. Similar barriers were addressed by the 19 participants who reported that they would not recommend the MORE Energy app to their colleagues; the advices were too common or not innovative enough  somewhat agreed, and 14 (16 %) agreed with the adherence statement that they applied the advices after consulting them. Further, 25 (29 %) participants somewhat disagreed or had a ‘neutral’ opinion towards the statement.p = 0.71) and 0.30 (p = 0.004), respectively.Spearman’s rho correlation between the objectively and subjectively measured compliance and adherence was 0.04 (p ≤ 0.001).Table The objective compliance of the subgroups was comparable with compliance in the total group of participants. As can be seen in Table p = 0.06). Further, significantly more 35 to 45 year old pilots were interested in advice regarding physical activity than their younger and older colleagues .Results on subjective compliance show that 53 % of the pilots younger than 35 years indicated to have never consulted the advices. Forty percent of the oldest group of pilots indicated that they used the advices sometimes or always. All age groups indicated they consulted the advices about the time spent during layover the most (63 to 78 %), followed by advices concerned with the return flight (46 to 56 %), and the advices before departure from home (28 to 43 %). With regard to the content of the advices, the youngest group of pilots was more concerned with advice regarding sleep , while the oldest group was less concerned with advice regarding nutrition compared to their colleagues .Although layover advice was not available for short-haul pilots, subjective compliance results show that both groups indicated to have consulted this type of advice the most. Next, 50 % of the short-haul pilots consulted the advices with regard to departure from home, while 53 % of the long-haul pilots consulted the advices regarding the return flight. Advice regarding nutrition was consulted significantly more by short-haul compared to long-haul pilots . Further, 70 % of the short-haul pilots would recommend the advices to their colleagues, while 87 % of the long-haul pilots would do that (p = 0.06).Comparing the two haul types, it can be seen that 55 % of the short-haul pilots reported that the advices were easy to apply, compared to 43 % of the long-haul pilots. However, 40 % of the short-haul pilots considered the advices also useful, compared to 61 % of the long-haul pilots .Our results showed a distinction between the objectively and subjectively measured compliance regarding the type of advices. Despite the registered data displayed that the advice concerned with departure from home was consulted most often, the participants themselves indicated that they used the advice concerned with layovers the most. It might be possible that the participants thought that they were asked r = 0.041). This might indicate that although participants were interested to see what advice the app would provide regarding their upcoming flight schedule, the content did not pursue them to change their behavior. However, once applied, the advices might have been useful: participants that did indicate to have applied the advices in daily life rated the intervention significantly higher compared to the participants who did not apply them.Despite the moderate compliance scores, a majority of the users (65 %) was convinced that the intervention was able to fulfill its purpose, preventing fatigue and improving health of pilots. Also, 78 % of the participants would recommend the intervention to their colleagues. In this perspective, the 6.4 (range 1 to 10) appreciation score for the MORE Energy intervention as a whole, is somewhat low. On the other hand, a majority of the pilots (54 %) did not agree with the statement that the advices were easy to apply in daily life. This lack of applicability of the flight schedule specific advices was also shown in the barriers and facilitators section. Participants indicated that applying the advices would conflict with their social life at home (e.g. young children) or during duty (e.g. habits during layovers). Furthermore, the correlation between registered compliance and adherence proved to be very low  patterns of the more experienced colleagues. The apparent contradicting high percentage of the oldest group of pilots (85 %) that would recommend MORE Energy to their colleagues may be in accordance: these pilots do not need the advice for themselves but they think it might be useful for their less experienced colleagues.Regarding the participants of the two haul types, no significant differences in objective compliance existed either. The relatively large number of short-haul pilots that participated in the study did find the advices easy to apply, but found them not very useful. Consequently, short-haul pilots tended to be less satisfied with the intervention compared to the long-haul pilots. Although the operations of the two haul types differ substantially, short-haul schedules can trigger fatigue as much as intercontinental schedules . HoweverThis process evaluation is one of the first evaluating an mobile health intervention promoting health behaviour. One of the major strengths is that we used a combination of objective and self-reported data to evaluate the implementation of the MORE Energy intervention. The compliance with both the app and the website was registered through user authentication, which is more reliable than self-reported information . NeverthWe achieved a reach of 22 %. Although this is quite high compared to participation rates published in other mobile health studies, the generalizability of the results might be hampered due to selection effects. It is possible that the non-participating pilots did not possess an iOS or Android smartphone or tablet, or were not sufficiently familiar with mobile apps. The comparison of the participants with the non-participants also showed that participants were significantly younger, and that a relatively large number of female pilots participated.Another limitation of this study is that only 59 % of the participants filled out the process evaluation questionnaire. Therefore, selection bias may have occurred, which challenges the reliability and validity of the outcomes. Another limitation of the study is that we could not measure all activities of the users of the mobile app. The number and types of requested advices were registered, but consultation of the background information and time spent on the app was not.The MORE Energy intervention aimed to improve relevant behaviour among airline pilots. Although we asked participants whether they had applied the advices in daily life, their actual change in behaviour could not be objectively measured. Therefore, to maximize the interpretation of our results, it would have been useful if the app had used more built-in features of smartphones to measure behaviour (e.g. timing of sleep using the motion sensor of the mobile device) .The reach of this study shows that airline pilots are willing to participate in an intervention using an app to promote health behaviour. Although guidelines have been proposed to improve the way the outcomes of mobile health interventions are reported , qualitaHigh compliance is important for the success of any intervention intending to modify behaviour, but especially so in web-based interventions since there is no direct contact with the participants . BecauseOur process evaluation gives insight into the different aspects involved in the implementation of the MORE Energy intervention, and will help to improve the interpretation of the results of the trial. The outcomes of the different items showed which parts of the intervention should be improved before offering the intervention to all flight crew throughout the airline company. First, the app should pursue users more to change relevant behavior, despite the consequences for their social responsibilities. Further, the content of the advice should be better applicable for both experienced and inexperienced employees, involved in both short and long-haul schedules. The airline company involved can assist the subsequent implementation of the improved app by integrating it with flight crew scheduling, by giving sustained attention to the topic within the present flight crew members, and by introducing the tool to newly hired employees . After tThe process evaluation of MORE Energy showed that this mobile health intervention was well received, resulting in an adequate reach and a high dose delivered. Although more than 80 % of the participants did use the intervention, most of them were not compliant throughout the intervention period. The intervention could not be delivered as intended and perceived satisfaction was moderate. Further, the combination of compliance and satisfaction scores indicates that the content and applicability of the advices should be improved to appeal all subgroups first, before making the app available for the other flight crew members within the airline company. After this improvement, MORE Energy might be adapted and implemented as a fatigue management tool for other employees and companies as well.


The Western Ontario Osteoarthritis of the Shoulder index (WOOS) has been introduced as a disease-specific quality of life measurement in patients with glenohumeral arthritis. The aim of the present study was to perform a cross-cultural adaptation of the English version of the WOOS to Italian and to assess its validity, reliability and responsiveness in patients with glenohumeral joint osteoarthritis treated conservatively.The adaptation process was carried out following the simplified Guillemin criteria. The English version was translated into Italian by two bilingual orthopaedic surgeons and then translated back into English by two different bilingual orthopaedic surgeons. The original version was compared with the back-translation. The questionnaire was prospectively administered to 30 patients with glenohumeral osteoarthritis at baseline and again after 5 days for retest reliability. After 6 months of conservative treatment, the responsiveness of the questionnaire was assessed in a subsample of 20 patients. The level of statistical significance was set at 0.05.P < 0.001). Pearson’s correlation coefficient between the WOOS and disability of the arm, shoulder and hand (DASH) preoperatively was 0.73 (P < 0.01) and the correlation between the changes of score for the WOOS and DASH was 0.75 (P < 0.01). There were no floor or ceiling effects. Responsiveness, calculated by standardized response mean, was 1.1 and effect size was 1.3.The interclass correlation coefficient between test and retest of the WOOS was 0.99  contains supplementary material, which is available to authorized users. Patient-reported outcomes are used to assess the severity of pathology and evaluate the outcomes of both conservative and surgical treatments. Most of these questionnaires are created and developed in English-speaking regions and tested on the cultural traditions in these areas. A simple translation of these scoring systems into different languages and cultures is not sufficient. These outcome tools must be validated with a process of translation and adaptation before being used in practice , 2. ThisThe WOOS index is a patient-administrated, disease-specific questionnaire for measurement of the quality of life of patients with osteoarthritis of the shoulder . It inveThe final version of the questionnaire was then administered to a selected population. The three aspects mentioned, validity, reliability and responsiveness, were investigated. Validity represents the meaningfulness, appropriateness and utility of a measurement. Reliability is the ability to provide the same result in stable subjects and adequate levels of measurement variability with repeated administration of a measurement tool. Finally, the responsiveness is the ability of a questionnaire to reflect significant clinical change in the subject’s state after treatment . Floor aThirty-two patients  affected by glenohumeral joint osteoarthritis were prospectively evaluated for enrolment in the present study. Each patient was required to be a candidate for conservative treatment of early stage glenohumeral joint osteoarthritis in order to be included. Two patients with fibromyalgia were excluded at the time of enrolment, since the diagnosis may have affected patient perception of the local pathology. Thirty patients were deemed eligible and enrolled in the study . Mean age at the time of first evaluation was 65 years (range 62–73 years). All patients were assessed with physical examination and standard radiographic evaluation consisting of true anterior–posterior views of the shoulder with the arm in internal, neutral and external rotation. The diagnosis of glenohumeral joint osteoarthritis was confirmed radiographically in all patients (stage 1 in 21 patients and stage 2 in 9 patients according to the classification introduced by Samilson and Prieto). All patients were asked to complete the WOOS and DASH questionnaires in the presence of an orthopaedic resident. The time necessary to complete each one of the questionnaires and any difficulty encountered in answering a question was recorded. To reduce the risk of short-term clinical change, no treatment was provided to these patients over a 5-day interval. To perform test–retest evaluation and test the reliability of the questionnaire, patients were asked to complete the same questionnaires 5 days later, assuming that the clinical situation and severity of symptoms had not changed during this short interval. Twenty patients agreed to undergo a protocol of conservative treatment consisting of stretching exercises, strengthening and active exercises over a period of 6 months. At the end of the program, the same score sheets were administered to these patients. This allowed calculation of the responsiveness of the questionnaire. In addition, the distribution of scores and the ceiling and floor effects were calculated by examining the item responses.Statistical analysis was performed using SPSS 11.5 for Windows. The Shapiro–Wilk test was used to assess normality. Correlation between WOOS and DASH was assessed with a parametric test (Pearson’s correlation) and the test–retest reliability was assessed with interclass correlation coefficient (ICC) for the total score and for the four domains. Absolute reliability was determined by estimating the standard error of measurement SEM = SD × √(1 − ICC), where SD is the standard deviation, and the minimum detectable difference MDD = 1.96 × √2 × SEM. A Bland–Altman plot shows the mean difference in test and retest values of WOOS against the mean of these two measures , and the correlation between the score at the end of the conservative treatment was 0.75 (P < 0.01)   . AlthougIn 2004, approximately 4 % of the total joint prostheses involved the glenohumeral joint . MoreoveThe present study aimed to adapt the WOOS questionnaire into Italian and to assess its validity and reliability. In addition, the responsiveness to conservative treatment was assessed. The WOOS strongly correlated with the DASH score, which serves as a gold standard, indicating good validity. The test/retest reliability was very high, indicating that the score was consistent over a short period of time. Finally, an additional aim of the study was to assess the influence of conservative treatment on the perception the patients had of their shoulder problem. The responsiveness to conservative treatment was good, indicating that the treatment positively influenced patient perception. The results of the present study were comparable with those of previous studies , 15. HowThe present study does have some limitations. The most important one is the lack of a power analysis. To reduce the risk of potential biases, we referred to similar studies available in the literature to determine the sample size needed. One of the strengths of the study is that this is the first time the WOOS index has ever been translated into Italian and applied. Furthermore, this was a very homogeneous patient population consisting of glenohumeral joint osteoarthritis and all patients were treated conservatively with a standardized protocol.Currently no Italian validated version of the WOOS index is available. The present study confirms that the scoring system has high correlation with the DASH score. The test–retest reliability was also high. In addition, the Italian WOOS index showed good responsiveness, indicating that it is positively influenced by conservative treatment. The scoring system also demonstrated no substantial ceiling or floor effects. The Italian version of the WOOS index can be reliably used in Italian patients with glenohumeral osteoarthritis.Supplementary material (DOC 131 kb)Below is the link to the electronic supplementary material.


Penetration depth of ultraviolet, visible light and infrared radiation in biological tissue has not previously been adequately measured. Risk assessment of typical intense pulsed light and laser intensities, spectral characteristics and the subsequent chemical, physiological and psychological effects of such outputs on vital organs as consequence of inappropriate output use are examined. This technical note focuses on wavelength, illumination geometry and skin tone and their effect on the energy density (fluence) distribution within tissue. Monte Carlo modelling is one of the most widely used stochastic methods for the modelling of light transport in turbid biological media such as human skin. Using custom Monte Carlo simulation software of a multi-layered skin model, fluence distributions are produced for various non-ionising radiation combinations. Fluence distributions were analysed using Matlab mathematical software. Penetration depth increases with increasing wavelength with a maximum penetration depth of 5378 μm calculated. The calculations show that a 10-mm beam width produces a fluence level at target depths of 1–3 mm equal to 73–88% (depending on depth) of the fluence level at the same depths produced by an infinitely wide beam of equal incident fluence. Meaning little additional penetration is achieved with larger spot sizes. Fluence distribution within tissue and thus the treatment efficacy depends upon the illumination geometry and wavelength. To optimise therapeutic techniques, light-tissue interactions must be thoroughly understood and can be greatly supported by the use of mathematical modelling techniques. Thus, it seems reasonable that skin has not evolved as a mere sun block but as a sun screen.Human skin is the interface between man and his environment. One of the environmental factors it has to deal with is ultraviolet (UV) radiation. Ultraviolet radiation may cause negative effects such as erythema, skin ageing and skin cancer. The upper layer of skin, the epidermis, acts as a natural UV filter and may thicken or develop a stronger pigmentation as an adaption to excess UV exposure. On the other hand, UV radiation induces photo production of previtamin DRed light penetrates deeper than blue light . The reaIntense pulsed light (IPL) systems emit light in the wavelength range 400–1200 nm . For wavThe wavelength of a therapeutic source therefore has a double importance, namely to ensure absorption of the incident photons in the target chromophores and to be able to do so at the depths at which these chromophores exist. The waveband in which the wavelength of the incident photons is located determines not only which part of the cell is the target but also the primary photo action. Wavelength is thus probably the single most important consideration in phototherapy, because without absorption, there can be no reaction.μs (λ) (cm−1). Once absorbed, the radiation is predominantly converted non-radiatively (i.e. without luminescence) into heat by the absorbing chromophore molecules. When there are pigmented tissue structures present that are more strongly absorbing at the laser wavelength than the surrounding tissue, e.g. hair shafts, the photons propagating randomly within the tissue will tend to be absorbed selectively by the pigmented structures. Thus, given enough deposited energy, selective photothermolysis of the pigmented structures will occur. Absorption by the pigmented structures or the surrounding tissue is characterised by their respective wavelength-dependent absorption coefficients, μa (λ) (cm−1).For normally incident radiation, this regular reflectance is on the order of 4–7% . The remA question that often appears throughout the literature asks: To what depth does optical light penetrate in skin tissue? This question is of importance when targeting treatment areas, optimising treatments, reducing risks and ensuring that the optical radiation does not reach vital organs and the foetus during pregnancy which may lead to complications. This computational investigation shows the effect of incident wavelength and beam width on penetration of human skin.2) at a known distance from skin. For this investigation, only the Monte Carlo section of photon distribution is used.The 2-D mathematical simulation described here was previously utilised for a study modelling blood vessels , but wasThe calculation of the energy distribution was achieved by using a Monte Carlo process. This computer simulation allows observation of comparative data that cannot be performed in skin. The Monte Carlo simulation of photons is a numerical calculation repeated random sampling to obtain numerical results by probability distribution to compute the radiative transport in scattering and absorbing media.μa) provide energy conversion of the photon to the cell, the scattering coefficient (μs) provides the angle of deflection between tissue cell interaction and the whole anisotropy factor (g) of each material at the specific wavelength is considered whereby light is forward scattered in tissue. These respective values were taken from the literature [In the computations of photon pathways, the absorption coefficients  is computed. The scattering coefficient (μs) is measured from experimental techniques originating from Mie scattering due to collagen fibres and from Rayleigh scattering due to small tissue structures, respectively [A custom Monte Carlo simulation package was created by the School of Applied Computing, University of Wales Trinity Saint David, UK, and implemented on a personal computer. Within this Monte Carlo simulation, the absorption coefficient of melanin , is characterised by the Henyey-Greenstein phase function, and since this phase function is forwardly biased, θ will be randomly influenced to reflect this characteristic. Applying the probability density function for the random number R to the above equation and solving for cos(θ) lead the following expression , which is equal to 1. A photon starts at a boundary position with the tissue interface with a step size, anisotropy angle of rotation and a deflection angle. At each interaction, the photon delivers a portion of its energy, pre-set to values determined of tissue optical properties. The loss in energy at each of the on-going interaction sites is determined by the weight that the photon deposits. The change in weight is defined by the following equation –26.\docuW is below a threshold. In this simulation, the photons are terminated when one hundredth of the original weight remained after multiple interactions. Then after this photon is deposited in its final position, a new photon is released and the process is repeated. A sufficient number of photons are required to generate an absorption energy density matrix for the defined tissue configuration for absorption of the IPL power output [The photons are terminated when the value of Δr output , 25, 27.r output , 25. TheH is the volumetric distribution of energy calculated in the Monte Carlo simulation and stored in number array, y and z are the radial and axial coordinates, respectively.Where In order to obtain a relationship between the penetration depth and wavelength, Monte Carlo simulations were carried out for wavelengths in the range 300–750 nm in 50 nm increments. The default beam width of 30 mm was also used. Photon distributions were then extracted from the Monte Carlo model and input into a custom Matlab programme for data manipulation and more effective data analysis.9 photons with an epidermal melanin concentration of 4.3% (skin type 2) [In order to obtain a relationship between the penetration depth of light and the beam width of the treatment device used, Monte Carlo simulations were carried out for beam widths in the range of 1 to 40 mm. The simulations used 1 × 10 type 2)  on the tFor each of the beam widths used, a default IPL spectra was used Fig. . Photon e and 1/e2 for a clear and clean graphical representation of the photo-distribution matrix. The figures also show the beam divergence as the light passes through the skin model.Simulations were carried out for a range of beam widths in the range 1 to 40 mm, shown in Fig. Monte Carlo simulations were carried out for the whole spectral range offered by the TODDY package; 300–750 nm in increments of 50 nm. Figure It can be seen that for increasing wavelengths, the 1% contour line penetrates deeper into the tissue as expected. In the penetration depth of 1%, the intensity is reached at 5378 μm (5.4 mm) with a wavelength of 750 nm. This is in agreement with literature which states the penetration of optical light systems reaching to a depth of 4–6 mm . HoweverFigure Figure A key contributor to the penetration depth is the treatment area or spot size employed by the device. Spot size has important clinical implications due to its effect on penetration and light dispersion in tissue. With increasing spot size, there is a reduction in the amount of lateral scattering; this results in greater penetration for larger spot sizes. As a result, lower energy densities can be applied when using larger spot sizes to achieve the same penetration depth for treatment. Variation in spot size is also important depending on the condition being treated, if the treatment region is over a large area then a larger spot size is used and for isolated small lesions in blood vessels for instance, a smaller spot size would be recommended resulting in increased intensity at the target. A beam width of 4–6 mm is usually used to penetrate to the mid-dermal and deeper layers of skin where the hair follicles and blood vessels are situated. It has also been found that although the penetration depth increases, there is a point at which the beam width has no further effect on the penetration depth and this is expected to be in the region of 5–12 mm in beam width , 28, 29.There is a noticeable increase in the penetration depth when the beam width is increased from 1 up to 5 mm before maintaining a constant penetration depth of approximately 10 mm when the intensity is reduced to 1% regardless of the increase in beam width Fig. .Fig. 7CaThe trend shows that a critical point is reached for a beam width of 10 mm at which a further increase in the beam width of the treatment device used does not affect the penetration of the light in tissue. A smaller beam width is associated with increased scattering, and as the beam width is increased, the photon propagation becomes increasingly forward projected up to that critical point where the scattering in the medium saturates. This can be graphically shown in Fig. It was found in the literature that the critical point appears between 5 and 12 mm . There iBeam widths for IPL treatment devices are usually quoted as spot sizes in the range 6 to 4.8 mm , where tBased simply on this 2-D model and the assuming that spot sizes are symmetrical, the fluence levels need not be adjusted for beam widths greater than 10 mm when attempting to reach a specific depth in tissue, and hence, spot sizes for various devices greater than this only have the added benefits of greater area for irradiance and so a reduction in surface heating and also the benefit of a greater beam width to treat a larger volume in the skin.The Monte Carlo model used is a 2-D model and as such the spot size can only be adjusted in terms of a beam width. Of course, this 2-D model does not give the complete picture of light penetration into the tissue since a typical device may utilise a spatial profile which is not ‘homogeneous’, although it is hoped that the spatial profile remain consistent throughout the medium and does not follow the Gaussian intensity distribution which is employed by laser systems -33.In summary, it has been found from Monte Carlo simulations that an increase in penetration depth can be achieved using longer wavelengths of light and using a spot size which is of at least 10 mm in width. Maximum penetration depths using the IPL system were found to be 5 mm using the 1% criterion and 0.37 mm using the 13.5% criterion. Although from this data and the lack of literature referring to the penetration depth, it is not possible to identify a therapeutic depth of penetration. It can however be suggested that if a maximum penetration depth of 5 mm is achieved using the IPL (for skin type 2) with a reduction in the intensity to the extreme of 1% maximum intensity, then it is safe to assume that the IPL does not have much of an effect at depth greater than 5 mm and so there would be remote risk of damage to tissues beneath the skin and indeed no damage to organs or a foetus which rests beneath the skin, adipose and muscular tissue. However, this model just looks at the penetration depth of light and not at the heat it produces on interacting with the tissue. Thus, it would be useful to produce a spatial heat diffusion model to identify the temperature at the maximum penetration depth and also to identify the temperature rise at therapy associated locations such as the hair follicle and blood vessels.It should be noted that the intensities reported in this section are not as a percentage of the incident intensity but as a percentage of the maximum deposited photon energy; the radiation which has escaped the sample is not included in this intensity. It would thus be useful for future investigations to identify the percentage of light which has escaped the sample and from this, deduce the absorption intensities as a fraction of the intensity produced by the device and not just as a fraction of that maximum amount which is absorbed in the skin. Therefore, the actual penetration depths would be less than those found.Other further investigation could include identifying the relationship between wavelength and penetration depth for wavelengths greater than 750 nm, since the Monte Carlo simulation package only looks at wavelengths in the range 300–750 nm. Use of smaller increments would also allow more accurate representation of the wavelength-dependent attenuation profiles of the chromophores to be identified.It should be acknowledged also that this model does not take into account the compression of skin when the device is placed on it. This would reduce the thickness of skin but at the same time the attenuation coefficients change . HoweverThis work addresses the risk assessment of laser and IPL devices that at these wavelengths and radiant exposures, photons are unable to reach vital organs as these results show a maximum penetration depth of 5 mm of 1% incident light. Therefore, these devices do not pose a photothermal or photochemical health risk to vital internal organs or foetus’s.Fluence distribution within tissue and thus the treatment efficacy depends upon the illumination geometry and wavelength. To optimise therapeutic techniques, light-tissue interactions must be thoroughly understood and can be greatly supported by the use of mathematical modelling techniques. The TODDY simulation provides the relationship of photon distribution with wavelength of epidermis-dermis-epidermis backscatter in our model.This study illustrates that on increasing the wavelength of light used in skin therapy, there is a corresponding increase in the penetration depth. Simulation of various beam widths has presented the increase in the penetration depth when the beam width is increased from 1 up to 5 mm before maintaining a constant penetration depth of approximately 10 mm when the intensity is reduced to 1% intensity regardless of the increase in beam width.


Using a direct measure of scattered light, it was found that commercial sugar solutions scatter light predominantly in a forward direction. The scattering at angles less than 30° was as much as one hundred times that at right angles to the incident beam.−1cm−1 at 436 mµ. The scattering of commercial sugar solutions is compared with that of highly purified sucrose.It was found that the light scattering by commercial sugar solutions is inversely dependent on wavelength to a power of between 2 and 3, and that severe multiple scattering occurs when the turbidity of the solution is larger than 2×10A method is discussed that will enable a good approximation of the turbidity of commercial sugar solutions to be made from a single forward scattering measurement at an angle of about 20° with respect to the incident light beam. A correction for scattered light in transmission measurements of these solutions is also introduced. Even though commercial sugar solutions have long been recognized as being somewhat turbid, there has never been a thorough study of their light-scattering behavior. Recently, however, light scattering by commercial sugar liquors has been receiving increased attention. It is a very sensitive measure of colloidal impurities, and the latter greatly influence the visual appearance of products such as beverages containing sugar.Light scattering by highly purified sucrose solutions has been previously reported , 2, 3.3 Most of the previous work on the scattering of light by commercial sugar liquors has been done with transmission measurements , 5, 6, 7Direct measurements of scattered light, independent of any simultaneous absorption of light, can be made. Thus the correction for turbidity to be applied to transmission measurements can be evaluated directly. This direct measurement of scattered light has been used to conduct a systematic study of light scattering by commercial sugar solutions.Only the optical factors involved in light scattering are considered in this paper. No attempt has been made to determine the chemical nature of the scattering particles. It is most probable that the scattering particles also absorb light and that the dissolved absorbing molecules also scatter light. However, the optical measurements discern only the overall scattering and absorption.Light scattering will be the general term used to signify the broad aspects of the phenomenon, while turbidity will specifically refer to the amount of light scattered per unit path length as defined in either of the equivalent equations,I is the irradiance of transmitted light, I0 is the irradiance of incident light, b is the path length in cm, T is the internal transmittance, and τ is the turbidity in cm−1. These equations apply only to systems which scatter light with no absorption.To avoid confusion, the following terminology will be used. c is the concentration of the sugar in grams per milliter and a is the absorption index.In systems that absorb light with no scattering, the Lambert-Beer law is applicable and can be written as follows:a* is the attenuation index.When the system both absorbs and scatters light, then one writes −logTbc=s, as follows:For systems such as sugar solutions, which both absorb and scatter light, the attenuation is assumed to equal the sum of absorption and scattering. In terms of the attenuation, absorption, and scattering indices this can be written:Re is the Rayleigh ratio, expressed as:r is the distance between the scattering volume, V, and the observer, and iθ is the intensity of scattered light.In all of the above relations, the turbidity is expressed in terms of light lost from the transmitted beam. However, turbidity may also be evaluated by a direct measurement of all light scattered in all directions:The Rayleigh ratio is a fundamental parameter describing light scattering by any medium. It is essentially the ratio of scattered to incident light at a particular angle of observation. This is the quantity that is actually determined when scattering measurements are made.In practice, the geometrical factors involved play a very important part, and a number of corrections must be made. These corrections have been adequately treated elsewhere , 10, 11 µ. The instrument was modified by decreasing the size of the slits in the incident and receiver optical systems in order to improve the angular resolution to about 1.5°. A cylindrical cell was used and the scattered light was detected by a high-sensitivity photomultiplier tube (1P21), which revolved about the cell from 0 to 145°, allowing angular scattering measurements to be made. The output of the phototube was amplified and recorded at a chart speed of 6 inches per minute. The recording greatly facilitated the “averaging out” of small fluctuations.The instrument used to measure the scattered light was a slightly modified microphotometer.The instrument was calibrated with Ludox,The dependence of light scattering on the angle of observation for some typical commercial sugar solutions is shown in The significant difference between the scattering envelopes of purified sucrose solution and a typical commercial sugar can be seen more graphically when plotted in polar coordinates as in Scattering envelopes for a large number of commercial sugar solutions, covering a range of quality from impure raw sugars to the most highly purified sugar solutions, all have the shape of curve as in To study the effects of refractive index on scattering by commercial liquors, a number of measurements on artificially controlled systems were made.In the first experiment, the concentration of the scattering particles was held constant, and only the refractive index of the solution was changed. This was clone by adding a small constant amount of a raw sugar solution to varying proportions of highly purified sugar and water. The small scattering due to the highly purified sucrose-water mixture, considered as the solvent, was subtracted from the total scattering to obtain that due to raw sugar alone. In When the linear dimensions of the scattering particles are less than about articles .µ. A log-log plot of turbidity as a function of wavelength resulted in straight lines the slopes of which were the wavelength exponents. The wavelength exponent for commercial sugar solutions varied between 2 and 3, corresponding to a particle size comparable to the wavelength, in agreement with the particle size deduced from the shape of the scattering envelope.The dependence of scattering on wavelength for some commercial sugar solutions was determined at wavelengths of 365, 436, and 546 mTwo of the major difficulties encountered in the measurement of light scattered by raw sugar solutions are multiple scattering and high absorption.Multiple scattering occurs when the solution is so turbid that the light scattered by one particle is rescattered before it leaves the cell. The result is an abnormal increase in scattered light at wide angles. There is no simple quantitative interpretation for multiple scattering, and the turbidities measured in the usual way for such systems are only “apparent” turbidities.The effect of multiple scattering is shown vividly in −1 at 436 mµ are reached.It is at once evident that to make valid scattering measurements on raw sugar solutions, it is necessary to dilute these solutions to a concentration range where multiple scattering does not occur. After a correction for the solvent scattering (purified sugar solution), it is possible to extrapolate to the original raw sugar concentration and obtain a value for the scattering as if multiple scattering did not occur. It was found that most commercial sugar solutions do not show severe multiple scattering until turbidity values larger than about 0.2 cmLight scattered by highly colored solutions can be evaluated by applying a suitable correction for the light lost by absorption. It has been shown  that if The dilution method mentioned above therefore serves a two-fold purpose, it eliminates multiple scattering and reduces the amount of absorption present, thus enabling valid scattering measurements to be made on raw sugar solutions.τ and R90. As was previously noted in θR at various angles of observation.Turbidity, which is the total scattering integrated over all angles, is evaluated by integrating Rθ is obtained when the angle of observation, θ, is approximately 20°. The very poor correlation obtained when θ is 90° shows that right angle scattering measurements are of little value in determining turbidity of commercial sugar liquors.The best correlation between turbidity and αθ is the intercept at Rθ = 1. The value of αθ depends on θ as shown in α90 is about 70, which can be compared with 16.75 for a Rayleigh scatterer. The choice of 20° for the angle of observation is subject to some latitude. However, the actual angle must be precisely known so that the appropriate value of αθ can be chosen from Since It is evident from To characterize the overall scattering of commercial sugar liquors completely, it is necessary to make angular scattering measurements. Since the scattering envelopes of most commercial sugar solutions have approximately the same shape, a good approximation of the total turbidity may be made from a single scattering measurement.A method is proposed that will enable a separation of absorption and scattering to be made from a single transmission and a single scattering measurement.


The program was written using the Microsoft Visual Basic.net framework and has a user‐friendly front‐end window with the following features: (1) Apart from using the well‐known polynomial curve‐fitting method for the interpolation and extrapolation of relative output factors (ROFs), an exponential curve‐fitting method was used to obtain better results. (2) A new algorithm was used to acquire the radius in each angular segment in the irregular electron field during the sector integration. (3) A comprehensive graphical user interface running on the Microsoft Windows operating system was used. (4) Importing irregular electron cutout field images to the calculator program was simplified by using only a commercial optical scanner. (5) Interlocks were provided when the input patient treatment parameters could not be handled by the calculator database accurately. (6) A patient treatment record could be printed out as an electronic file or hard copy and transferred to the patient database. The data acquisition mainly required ROF measurements using various circular cutouts for all the available electron energies and applicators for our Varian 21 EX linear accelerator. To verify and implement the calculator, the measured results using our specific designed irregular and clinical cutouts were compared to those predicted by the calculator. Both agreed well with an error of PACS number(s): 87.53.Fs; 87.53.Hv; 87.66.‐a Obviously, this patient‐specific measurement consumes a lot of resources and man‐hours in the physics department. The dose per MU can be calculated by the relative output factor (ROF) for the electron beam. ROF is defined as the ratio of the dose rate in water at a reference point with a custom cutout to the dose rate under the beam calibration condition. The reference point can be either the depth of maximum dose (dm) or a reference depth (dref) defined by the AAPM TG‐51 protocol.10×10cm2 applicator and cutout at SSD=100cm to obtain 1 cGy/MU with an acceptable uncertainty of ±2%.SSD=100cm.Electron radiotherapy is used to treat superficial lesions and tumors at shallow depths under the skin. However, the dose per monitor unit (MU) is difficult to predict due to the variation in electron scattering with a variety of linear accelerators, beam energies, source‐to‐surface distances (SSDs), and beam collimation systems.–4 As the lateral buildup ratio,10×10cm2). However, the work of the AAPM TG‐70 protocol is still in progress.To avoid time‐consuming patient‐specific ROF measurements, much work has been done in ROF prediction based on different algorithms such as the Gaussian pencil beam model plus collimator scattering,,8 thMost of the commercial radiation treatment‐planning systems (RTPSs) can calculate the electron MU based on the above algorithms; however, an in‐house electron MU calculator is desired as a QA tool for the RTPSs, as well as for predicting the MU for an emergency treatment without a plan from the RTPS. The calculator program should be reliable, user‐friendly, accurate, and compatible with the most common personal computer operating system—Microsoft Windows—so that all radiation oncology staff will find it easy to use.>2cm), the ROF of an irregular field can be accurately predicted with an error of ±2% compared to the measurement.By using the polynomial curve‐fitting method, or even better, the exponential curve‐fitting method, in the clinical cutout size range :D0 is the absolute calibrated dose (1cGy/MU) at SSD=100cm and dref in water according to the AAPM TG‐51 protocol. The correction factor C corrects the difference between the percentage depth doses for dref and dm, which is the depth used in planning and prescribing the patients in our center. IDL is the isodose line of the prescription. SSDeff is the effective SSD, d0 is the depth of treatment, and g is the air gap, which is the difference between the regular SSD of 100 cm and the treatment SSD. In d0, and IDL are decided by the oncologist. The values of D0,C, and SSDeff are predetermined by the physicist for the LINAC with all the available electron energies. The value of g is measured by the radiotherapists during the setup and/or simulation of the patient before the treatment. The ROF depends on the shape of the irregular electron field and varies with beam energy and applicator size. It should be noted that for the Varian 21 EX LINAC, the distance between the machine isocenter and the bottom surface of the applicator is 5 cm. When the treatment SSD is equal to 100 cm , the inverse square law term (IDL/100) in the denominator of The electron MU in this paper is calculated using the effective SSD technique–16:n is the number of angular segments divided into an irregular field with angles of 360°/n. ROFi is the ROF for a circular field with the radius equal to the distance measured from the field central axis to the edge in each individual angular segment. This model can be applied to off‐axis points or cutouts with the radius vector crossing a blocked field at the depth of dref. The part of radius vector crossing the blocked field can be subtracted from the original radius vector at the center. The resulting vector will then be used to calculate the ROF. To calculate the ROF for an irregular field, a database of ROFs for circular fields of varying sizes, electron beam energies, and applicator sizes should be predetermined. In this paper, various circular cutouts were fabricated for all five applicators, and measurements were taken to determine the ROFs for the five electron beam energies. The measured ROFs at the depth of dref were then plotted against the cutout radii corresponding to various combinations of energies and applicators, so that ROFs for any other cutout sizes could be obtained through interpolation or extrapolation using curve‐fitting methods and the plots.For the irregular field, the ROF is calculated using the sector‐integration formula:X, Y) is the ROF of a rectangular cutout with side lengths of X and Y. ROF and ROF are ROFs of square cutouts with side lengths of X and Y, respectively. It should be noted that For calculating the ROF of a square or rectangular cutout, the following well‐known formula was usedThe Microsoft Visual Basic.net framework version 1.0 was used to develop the electron MU calculator program. The program works on Microsoft Windows and contains a front‐end window, routines for sector integration and MU calculation, an interface for importing cutout images, and a database for measurements and curve fitting. The front‐end window, as shown in x‐axis was used as a static vector. The distance between the field central axis and the edge along the positive x‐axis was measured as radius ri for each angular segment step by step as shown in ri compared to the conventional algorithm, which rotates the central axis vector. Increasing the number of angular segments in this manner does not increase the accuracy of the ROF calculation except in cases where the shape is highly irregular.For the sector‐integration routine, a new algorithm was used to find the radius of each angular segment in the irregular field: Instead of rotating a vector directed from the field central axis to the static field edge to measure the radius for each angular segment, the irregular field was rotated in the opposite direction, and the positive s vector.,–20C,dm,dref, and SSDeff, which depend only on the beam energy selected. The second table stores the fitting curve parameters of 25 combinations (5 applicators and 5 energies) for the plotting of ROFs against the radii of circular fields using the exponential and polynomial method. This table was used for predicting the ROF using the interpolation and extrapolation technique. The third table stores a large collection of ROFs for various combinations of square sizes, cone sizes, and electron energies; linear interpolation between points is then performed when calculating the ROF of a square or rectangular field. The database is password‐protected so that only users with authority, such as the treatment‐planning resource physicist, are allowed to change the content.The integration parameters are stored in a Microsoft Access database, which is loaded during program startup. The database contains three tables: The first table stores the parameters used in C,dm,dref, and SSDeff were measured using a scanning water tank system . A waterproof high‐doped p‐type silicon diode  was used to measure both the beam profiles and percentage depth doses at the central beam axis. The thickness of the silicon chip is 0.5 mm, and the diameter of the active area is 2 mm. The values of dm and dref for 4 MeV, 6 MeV, 9 MeV, 12 MeV, and 16 MeV were measured with a standard 10×10cm2 cutout and a 10×10cm2 applicator at SSD=100cm. The SSDeff values for the five energies and applicators were measured according to the procedure in Ref. 15. The values of SSDeff, which vary with the electron field size and beam energy, are shown in dm and dref, which vary with energy for the standard 10×10cm2 applicator and cutout, are shown in The values of SSD=100cm. For small cutouts (radius <2cm), radiographic film (Kodak XV) and solid water phantom slabs were used to verify the measurements. The ROFs for the square cutouts were measured using a similar procedure. All ROFs were measured at the depth of dref in this study. Since ROF is an output ratio, the uncertainty contributed by the dosimeter should be very small. The uncertainty in the measurement was mainly contributed by the experimental setup and the positional error of the circular cutout at the center of the applicator frame.To measure the content of the second table for the database in Section II.B, ROFs of various circular cutouts for the five electron energies were measured using the Varian 21 EX LINAC. Circular cutouts with different sizes for the five applicators were fabricated; their radii are shown in (–24) used in the calculator program contained six fitting coefficients :b1,b2, and b3). MATLAB version 7.0 was used for the curve fitting.Using the measured ROFs for various circular cutouts, the ROFs were plotted against the radii of cutouts at each applicator size for specific electron energies. Twenty‐five graphs for all combinations of the five electron beam energies and applicators were therefore plotted. Since each graph only had five to seven data points, it was necessary to interpolate or extrapolate so that ROFs for any electron field could be accurately predicted. In eMUc, two different kinds of curve fitting, polynomial and exponential, were used. The user can select between these two methods in order to carry out the MU calculation according to different clinical situations. The linear polynomial method<±2%) before starting the program clinically.When the data acquisition and ROF curve fitting were finished and the results were input into the database, the calculator program was ready to be commissioned for clinical use. Specific irregular cutouts were designed to verify the predicted ROFs. Cutouts as shown in 10×10cm2 applicator with electron energies of 4 MeV, 6 MeV, 9 MeV, 12 MeV, and 16 MeV, respectively; 20×20cm2 applicator. Both figures show the measured ROFs with fitting curves using the polynomial (broken line) and exponential (solid line) method as mentioned in Section II.D. Due to the limited space in this paper, similar plotting for the other three applicators is not shown. ±1mm) when the radius of the cutout is smaller than 1 cm at low electron energies such as 4 MeV and 6 MeV. The polynomial method is commonly used to fit the ROF curve. However, it is noted that the polynomial fitting curves usually “shift” up for large cutout radii as shown in ±0.5% in the clinical cutout size range. Moreover, an interlock was imposed in the program when the cutout radius is larger than the polynomial method can accurately predict. It is interesting to note that in theory, a zero dose  should be expected at zero radius in In OF curve.,–236×6cm2 applicator, and cutouts the same as ±2%. Similarly, many clinical measurements and predictions by eMUc were compared and their differences were also within ±2%. The differences of the predicted ROFs between both methods are small and within ±0.5%. However, the exponential fitting method is suggested when the distance between the irregular field edge and central axis is large, and the field edge extends very near to the corner of the applicator insert. In this case, the radius of the segment circle is large, and the exponential method has a better fitting and interpolation result, as shown in dmax was measured using a Farmer chamber or radiographic film when the applicator size was small. The dose corresponding to 100 MUs at dmax was then predicted by eMUc using the polynomial and exponential fitting methods. The percentage differences between the predicted and measured dose are shown in the table, and it can be seen that they agree with each other within ±2%. In our experience, it took about one week to prepare all the cutouts for different applicators in the commissioning, another two weeks for the ROF measurement, and one more week for the verification.A new feature of the program is the ability to import the shape of the electron field image into the calculator. The user only needs to scan the drawing/photocopy of the irregular cutout with a length scale using a commercial optical scanner. The scanned image can be converted to any graphical format, such as JPEG, BITMAP, and TIFF. The program can read this image file directly and display it in the screen of the front‐end window as shown in Another feature of the calculator is the option to print out the calculated MU result as an electronic file or in a hard copy. When the “print” option is selected from the “file” menu, the user is prompted for treatment information that was not necessary for the MU calculation, such as the patient's name and ID number, the oncologist's name, and any other comments that the user wishes to include. An electronic file will then be generated in Microsoft Word with this information in addition to the calculated MU and all the related treatment parameters. This file can be printed out either as a hard copy to be kept in a binder or it can be transferred to an electronic patient record database for storage.dmax and the percentage isodose line covering for the target. Although for the commissioning of eMUc it is possible to measure the ROF at every reduced dmax for small circular cutouts, the whole measurement is very time‐consuming. In addition, radiation oncologists sometimes like to prescribe the dose at only one dmax  for consistency and convenience. In this situation, it is necessary to ensure the following: (1) The dosimetrist and the radiation oncologist should understand that all the ROFs used in eMUc are measured at dmax for the standard 10×10cm2 cutout, and (2) the physicist should discuss with the radiation oncologist when the change of dmax and percentage isodose could potentially affect the treatment for the patient. If necessary, ROF measurements should be carried out for each particular patient, and the MU value calculated by eMUc should only be used as a reference.It is well known that for some small cutouts, there is a significant reduction in Pinnacle3. When a plan for electron radiotherapy is completed in the system, all patient‐planning parameters and information can be transferred to eMUc, which acts as a QA tool for the predicted treatment MU. For future work regarding the calculation algorithm, applicator factors could be separated from the measured doses. If this has been verified for the LINAC, the model could be simplified to a single setup measurement for one applicator size. Moreover, the range of the polynomial fit could be reduced because the measured data indicated that ROFs were unity when the cutout radii were beyond 3 cm. All works are in progress.For future work regarding the program, eMUc has the potential to link to a LINAC treatment delivery system such as VARiS  so that the calculated MU can be transferred directly for the treatment delivery. The calculator program can also link to a treatment‐planning system such as ±2% compared to the measurements. It is concluded that such a calculator can provide a convenient electron MU calculation platform for the dosimetrists, radiotherapists, and physicists in electron radiotherapy. Future potential developments such as connecting the calculator program to the RTPS as a QA tool are in progress.A new electron MU calculator program, eMUc, was developed based on the sector‐integration algorithm. It was written using Microsoft's Visual Basic.net framework and has a user‐friendly front‐end window. A new algorithm for measuring the radius of each angular segment in an irregular cutout field for the sector‐integration routine as well as an exponential curve‐fitting method for obtaining accurate interpolation or extrapolation results were suggested. The well‐known polynomial curve‐fitting method is still used as an option in the program, although such a method does not perform well when the irregular clinical cutout size is comparable to the area of the applicator insert. The calculator program has a comprehensive image import interface, so that the scanned image file of the cutout can easily be transferred to the calculator program. The user can then use the computer mouse to outline the irregular shape of the field. This saves a lot of time compared to using the film digitizer, which is not usually available in many filmless/paperless centers to digitize the cutout drawing. An electronic file can easily be generated with a record of the patient information, the calculated MU, and the treatment parameters after the calculation. This file can either be forwarded to a patient database or printed out in hard copy. Verification between the predicted and measured results is done by comparing the ROFs measured with different shapes of irregular cutouts, energies, and applicators to those predicted by the program. Moreover, many irregular clinical cutouts are used in the verification. The accuracy of the calculator program is found to be within The authors would like to thank Scott Newman and Beverly Bradley for their initial effort in working with this project. All staff contributing to the measurements for the database are acknowledged in the Grand River Regional Cancer Center. The authors thank very much the editor and reviewers for their helpful suggestions, which improved the quality and presentation of this work.