Pulmonary anomalous venous return (PAPVR) is defined as a congenital anomaly in which at least one but not all of the pulmonary veins abnormally drain into a systemic vein or directly into the right atrium. Signs and symptoms related to this condition are due to the hemodynamic abnormalities secondary to left-to-right shunt and the possible presence of other associated cardiac anomalies . Therefore, depending on the extent of the shunt, the clinical presentation of PAPVR is variable, ranging from asymptomatic patients to patients affected by severe heart failure with right-sided volume overload. PAPVR with a clinically significant shunt should be referred for surgical correction with different techniques depending on the presence of associated cardiac anomalies.We are presenting a case of partial anomalous venous return (PAPVR) in a 66-year-old man who underwent surgery 26 years ago to correct an anomalous venous connection between the right superior pulmonary vein (RSPV) and the superior vena cava (SVC) through a veno-atrial baffle. The patient was admitted to the emergency department due to atrial tachycardia. Trans-thoracic echocardiography (TTE) showed a dilated right ventricle (RV) with mild RV systolic dysfunction and pulmonary hypertension. Cardiac magnetic resonance (CMR) further confirmed the findings described by TTE and also demonstrated areas of fibrosis replacement in the hinge points. Cardiac computed tomography (CCT) was able to accurately depict and evaluate the surgically created veno-atrial baffle and also showed an anomalous connection between the left superior pulmonary vein (LSPV) and the brachiocephalic vein (BCV) through a vertical vein. The patient was successfully treated with radiofrequency ablation for his arrhythmia. Pulmonary anomalous venous return (PAPVR) is a congenital anomaly in which at least one but not all pulmonary veins abnormally drain into a systemic vein or directly into right atrium . PAPVR iThe clinical presentation of this condition is strictly dependent on the entity of the left-to-right shunt due to the anomalous pulmonary flow return and possible associated cardiac malformations . In cases in which the shunt is not clinically significant Qp/Qs<50%), the patients can be asymptomatic until adulthood 0%, the p. ConversCases of PAPVRs with a clinically significant left-to right shunt  should be referred for surgical correction. Patients who developed pulmonary arterial hypertension (PAH) should be carefully evaluated prior to surgery since the correction might prove ineffective in this peculiar class of patients and it could be even harmful for patients untreated for PAH due to the risk of acute right heart failure following the procedure .A 66-year-old man was admitted to our Emergency Department complaining of palpitations. Twenty-six years previously, the patient had undergone surgery for partial anomalous venous return (PAPVR). The operative report showed the patient had an anomalous venous connection between the right superior pulmonary vein (RSPV) and the superior vena cava (SVC) 3 cm from the cavo-atrial junction, with right atrial (RA) and right ventricular (RV) dilation. No further anomalies were described regarding pulmonary venous drainage or other congenital malformations responsible for left-to-right shunt. PAPVR was corrected by creating a veno-atrial baffle connecting RSPV to left atrium (LA). There was no mention regarding the surgery on the SVC.On admission, the electrocardiogram (ECG) showed atrial tachycardia  with a heart rate of 120 bpm. Transthoracic echocardiography (TTE) showed RV and RA enlargement, mild RV systolic dysfunction (approximately 45-50% ejection fraction with tricuspid annular plane excursion of 16 mm) , mild puAfter unsuccessful pharmacological cardioversion with amiodarone, electrical cardioversion was attempted. Transient sinus bradycardia was achieved but was followed by early arrhythmia relapse. Therefore, an electrophysiologic (EP) study and catheter ablation of the arrhythmia was planned.Cardiac magnetic resonance (CMR) and cardiac computed tomography (CCT) were performed before ablation since the patient did not have any previous imaging records.At first, the patient underwent CMR. Cine balanced-steady state free precession (b-SSFP) sequences were performed on multiple planes in order to evaluate heart volumes, function and anatomical features. Phase-contrast (PC) sequences were performed on the ascending aorta and main pulmonary artery in order to estimate a left-to-right shunt. Phase-sensitive inversion recovery (PSIR) sequences were performed to detect areas of late gadolinium enhancement (LGE).2) and systolic dysfunction (Ejection fraction: 47%). Left ventricle (LV) volumes and function were in normal ranges, although a diastolic flattening of inter-ventricular septum was observed, most likely due to increased right ventricle filling pressure  with a retrospective ECG-gated acquisition protocol. The scans were performed during intravenous injection of iodinated contrast medium  with a flow rate of 5 ml/s and a saline bolus chaser of 40 ml. Images were further reconstructed using a dedicated workstation and performing 3D reconstructions.CCT scan confirmed anomalous drainage of RSPV in SVC. We observed the left superior pulmonary vein (LSPV) draining into the brachiocephalic vein (BCV) through a vertical vein Figure . The bafFollowing CCT scan, the patient underwent an ablation procedure. 3D electroanatomic mapping  during tachycardia revealed a centrifugal atrial activation pattern with earliest, low amplitude and fractionated electrograms on the interatrial septum, at the level of the inferior border of the baffle’s ostium. Pacing manoeuvres were consistent with micro-reentrant atrial tachycardia. Radiofrequency was delivered at the target zone with immediate termination of the tachycardia. A cluster of consolidating ablation lesions were delivered at the location. No further atrial tachycardia was induced with burst pacing after ablation. No arrhythmia recurrences were observed during a four-month follow-up.We present a case of supra-cardiac bilateral single-branch PAPVR with RSPV and LSPV anomalous drainage in SVC and BCV, respectively. Right-sided anomalous connections are the most common (90% of PAPVR) and often associated with sinus venosus type atrial septal defects (80% of cases), while cases like ours, characterized by intact interatrial septum represent approximately 3% of cases . The conRegarding the clinical features of our case, AT might have been the consequence of the surgical procedure the patient underwent previously. This surgical technique, as also other techniques performed to correct other congenital conditions  may be associated with the late occurrence of atrial arrhythmias ,12.As expected, our patient showed signs of PAH secondary to a clinically significant left-to-right shunt, as shown by TTE, CMR and CT.TTE is the first-line diagnostic technique in these patients according to the latest European Society of Cardiology (ESC) guidelines . This teCMR proved useful not only in confirming the findings showed by TTE, precisely calculating the Qp/Qs, but also for performing myocardial characterization. The Qp/Qs ratio is considered to be more accurate than that calculated by TTE, since it is well established that CMR is able to provide a more precise quantification. This is especially useful in the preoperative evaluation of patients affected by PAPVR. CMR images also demonstrated areas of fibrotic replacement in the RV insertion points, likely due to chronic volume overload, but the prognostic value of this finding is still uncertain . Beside Finally, CCT allowed to detect the LPSV draining to BCV, that was unknown at first, also precisely depicting the veno-atrial baffle course and patency. Moreover, this technique also allowed to reconstruct 3D volume rendering images, further helping to understand thoroughly the anatomy of the patient.Our case highlights the way that TTE, CMR and CCT proved useful in the preoperative evaluation of a patient affected by a rare type of PAPVR, each study providing different and valuable information. In patients with grown-up congenital heart (GUCH), this provides proper evaluation of the surgical procedure and any late complications.


Airway complications after lung transplantation are a major cause of morbidity and mortality. Bronchial dehiscence presents within a month of lung transplantation and is typically diagnosed radiographically as a sentinel gas pocket at the anastomotic site and confirmed with bronchoscopy. A 66-year-old man with idiopathic pulmonary fibrosis who underwent a right lung transplantation 4 weeks prior developed chest pain with palpable crepitus over his right chest wall. A chest X-ray revealed subcutaneous emphysema and a small right-sided pneumothorax. Computed tomography (CT) of the thorax without contrast revealed a gas pocket at the anastomotic site in the mediastinum as well as interstitial emphysema around the proximal bronchi of the right lung that had worsened when compared to CT from 11 days prior. A review of prior CT demonstrated interstitial emphysema without evidence of a sentinel gas pocket. These findings suggest that interstitial emphysema was the initial radiographic manifestation of the bronchial anastomotic site dehiscence. Interstitial emphysema is typically self-limiting, but severe cases can lead to major complications. Interstitial emphysema outside of the immediate postoperative period should be recognized as a possible early radiographic sign of bronchial dehiscence in lung transplant patients with vigilant monitoring of potential complications and strong consideration for early bronchoscopic investigation. Bronchial anastomotic site dehiscence typically occurs 2-4 weeks after lung transplantation and occurs in 1-10% of patients . The mosStaphylococcus aureus of the donor lung; other cultures were negative. The patient was to receive tacrolimus, mycophenolate, and prednisone for immunosuppression and nebulized amphotericin and intravenous valganciclovir for fungal and cytomegalovirus prophylaxis. No primary graft dysfunction was reported in the first 72 hours after surgery. CT without contrast was obtained on postoperative day 5 to evaluate a right lung basilar opacity, which showed extensive ground-glass opacities in the transplanted right lung, concerning reperfusion edema versus acute rejection. The patient was given diuretics, and glucocorticoid dosing was increased from prednisone 5 mg daily to methylprednisolone 40 mg intravenously twice a day. His postoperative course was further complicated by hypoxemia, for which a CT angiography was performed and showed a small distal pulmonary embolism in the right lower lobe, decreased ground-glass opacities in the right lung, and increased patchy basilar platelike peribronchial opacities for which rejection could not be ruled out. The patient received three days of pulse glucocorticoid dosing of methylprednisolone 250 mg IV daily, which was subsequently decreased. Persistent abnormalities on chest radiography and continued hypoxemia led to additional imaging. CT of the thorax on postoperative day 15 showed right allograft opacities, for which glucocorticoids were continued out of concern for rejection. Subsequent bronchoscopy on postoperative day 17 showed an abnormal area of eschar around the anastomotic site with a pale yellow-brown mucosa suggestive of ischemia. Cultures from the bronchoscopy were negative. A transbronchial biopsy of the right lower lobe was performed, and pathology showed organizing pneumonia without evidence of rejection. Donor-specific antibody serology did not suggest antibody-mediated rejection. Steroids were continued and tapered in an attempt to balance treating his organizing pneumonia while hoping to avoid the complications given the presence of anastomotic eschar on bronchoscopy.A 66-year-old male with chronic hypoxemic respiratory failure secondary to advanced interstitial pulmonary fibrosis, coronary artery disease, pulmonary hypertension, systemic lupus erythematosus, hypertension, and obesity presented for a single right lung transplantation which was performed with end-to-end anastomosis. His operation was uneventful with no significant major intraoperative complications or use of extracorporeal membrane oxygenation. He was extubated within 24 hours posttransplant after an airway and anastomosis inspection via flexible bronchoscopy was unremarkable. The patient was treated with antibiotics for methicillin-sensitive On postoperative day 26, the patient developed chest pain. Vital signs were as follows: temperature was 36.9 degrees Celsius, blood pressure was 108/61 mmHg, heart rate was 67 beats per minute, respiratory rate was 20 breaths per minute, and oxygen saturation was 97% on 20 liters of high-flow nasal cannula with fraction of inspired oxygen of 60%. On physical exam, the patient had rhonchi at the right base and right-sided subcutaneous emphysema on the anterior chest with no respiratory distress or accessory muscle use. A portable anterior-posterior chest X-ray showed right-sided subcutaneous emphysema with a small right-sided pneumothorax . CT of tInterstitial emphysema is defined as air dissecting into the interstitial space surrounding the bronchovascular bundles , 8. This2O [Abnormal airway pressures can cause rupture of alveolar walls and subsequent transport of air from ruptured alveoli to the mediastinum via pulmonary vessels, leading to a pneumothorax and pneumomediastinum . Physiol2O , 12. AgeMild interstitial emphysema is self-limiting. Severe interstitial emphysema can lead to complications including compression atelectasis, pneumomediastinum, pneumothorax, and hemodynamic effects from compression of the pulmonary vasculature , 12. ManInterstitial emphysema on the CT thorax 11 days prior to the patient developing symptoms may have been evidence of an atypical radiographic presentation of bronchial anastomotic site dehiscence, which was later confirmed with the classic CT finding of a sentinel gas pocket. While interstitial emphysema can occur postoperatively and is self-limiting, persistent interstitial emphysema and subcutaneous emphysema warrant closer monitoring for possible bronchial anastomotic site dehiscence. Our patient had risk factors for bronchial anastomotic site dehiscence including right-sided anastomosis, microbial contamination of the donor lung, and high glucocorticoid dosing due to initial concerns for possible rejection.Our patient received an end-to-end anastomosis. End-to-end anastomoses are associated with a lower risk of bronchial anastomotic complications as compared to telescoped anastomoses in patients who received single lung transplantation, with bronchial dehiscence seen in 25% of telescoped bronchial anastomoses compared to 2% of end-to-end bronchial anastomoses . In a teBronchial dehiscence should be suspected in patients with subcutaneous emphysema, worsening shortness of breath, pneumothorax, and infection within the first month of lung transplantation . A chestRecognition of interstitial emphysema outside of the immediate postoperative period on a chest X-ray and/or CT imaging as a sign of early bronchial dehiscence should prompt closer monitoring with serial exams, chest imaging, and bronchoscopy. Early diagnosis and treatment can prevent further complications.


Foscarnet  is the standard treatment of ganciclovir-resistant cytomegalovirus (CMV) infections or when administration of ganciclovir is not possible. It acts as an inhibitor of DNA polymerase and retroviral reverse transcriptase of all herpes viruses. Adverse effects are numerous and include nephrotoxicity and electrolyte disorders such as hypocalcemia.,Foscarnet has been reported to induce reversible acute kidney injury (AKI), kidney tubular necrosis, distal tubular acidosis, and nephrogenic diabetes insipidus.,,,,Foscarnet-induced kidney injury has been largely attributed to tubulointerstitial damage,Until now, the relative contribution of phosphonoformate crystal deposition to foscarnet-induced nephrotoxicity has remained uncertain because patients receiving the antiviral drug suffer from severe concurrent pathologies and are often treated with other nephrotoxic drugs. Another reason for said uncertainty is that other drugs potentially leading to crystalline obstruction, such as acyclovir and indinavir, have been associated with presence of crystals in urine, whereas such was not the case for foscarnet.In this article, we describe for the first time phosphonoformate crystalluria observed in 6 cases treated with foscarnet . These cReports of 6 patients treated with foscarnet and whose urinary sediment revealed presence of phosphonoformate crystals in urinary sediments.in vitro documentation of resistance of CMV to ganciclovir, the patient was switched to foscarnet. Phosphonoformate crystalluria (proven by infrared spectrometry) was observed 14 days after the onset of foscarnet therapy and associated with a nonglomerular hematuria and renal tubular epithelial cells in urine sediment. Progressive elevation of serum creatinine concentration occurred , despite adaptation of foscarnet doses to kidney function. The patient died after probable fungal bronchopneumonia and septicemia while still on foscarnet.A 71-year-old woman diagnosed with acute myeloid leukemia underwent, while in complete remission, a nonmyeloablative allogeneic hematopoietic stem cell transplantation with HLA-compatible unrelated donor. Conditioning regimen consisted in fludarabine and total body irradiation; graft-versus-host disease (GvHD) prophylaxis consisted of mycophenolate mofetil and ciclosporine. Following transplantation, the patient presented multiple complications such as a reactivation of CMV disease . Ganciclovir was administered without effect on the viral load of CMV. Hence, based on A 35-year-old man diagnosed with acute lymphoblastic leukemia achieved a second complete remission following salvage chemotherapy after a first relapse. Stem cell transplantation from an HLA-matched unrelated donor was performed following myeloablative conditioning. CMV serostatus was D−, R−. To prevent GvHD, cyclosporine with a short course of methotrexate was administered. Numerous complications occurred after transplantation, including an human herpesvirus 6 encephalitis. For the latter, ganciclovir was started and replaced after 24 hours by foscarnet because of concerns about known associated myelotoxicity with high doses of ganciclovir. Phosphonoformate crystalluria (proven by infrared spectrometry) was observed 7 days after onset of foscarnet associated with a nonglomerular hematuria but without renal tubular epithelial cells in urine sediment. Because of a stable kidney function, foscarnet administration was maintained at unchanged doses. Despite the human herpesvirus 6 encephalitis resolution, the patient died from acute respiratory failure due to uncontrolled bleeding.A 59-year-old woman diagnosed with acute myeloid leukemia received successfully an allogeneic hematopoietic stem cell transplantation from an HLA-compatible unrelated donor following a reduced-intensity conditioning. The GvHD prophylaxis regimen was mycophenolate mofetil and cyclosporine. In the post-transplantation phase, the patient presented several complications, such as reactivation of CMV disease . Foscarnet was initiated and phosphonoformate crystalluria (proven by infrared spectrometry) was observed 7 days after onset of therapy associated with renal tubular epithelial cells in urine sediment. No hematuria was observed. The patient developed AKI KDIGO stage 1 24 days after foscarnet initiation.). Elevated creatinine persisted despite discontinuation of foscarnet.This patient was a 63-year-old man who underwent liver transplantation for alcohol-induced cirrhosis. Despite anti-CMV  prophylaxis, the patient developed CMV infection against what he first received valganciclovir. The viral load of CMV further increasing, the patient was switched to foscarnet; however, phosphonoformate crystalluria (proven by infrared spectrometry) was observed 1 month after onset of the treatment with foscarnet and was accompanied by glomerular haematuria, leukocyturia, and renal tubular epithelial cells in urine sediment. The patient developed AKI KDIGO stage 1 47 days after onset of the treatment with foscarnet. CMV viral load decreased but remained present under bitherapy  infection. Because of proven This patient was a 70-year-old woman, diagnosed with high-grade myelodysplastic syndrome. After having achieved remission with systemic chemotherapy, she underwent a haploidentical stem cell transplantation. For GvHD prevention, she received post-transplant cyclophosphamide, tacrolimus, and mycophenolate mofetil. CMV serostatus: D−, R+. Despite anti-CMV prophylaxis with letermovir, CMV viral load increased from month 3 on, and a preemptive treatment with valganciclovir was introduced. Given a further increment of the viral load despite this treatment, foscarnet was subsequently started. Phosphonoformate crystalluria (proven by infrared spectrometry) was observed at day 9 after onset of foscarnet associated with a nonglomerular hematuria and renal tubular epithelial cells in urine sediment. The patient developed AKI KDIGO stage 1 at day 14.Phosphonoformate crystals exhibited rectangular and square shapes, sometimes shapes of a thin stick when they were positioned on the edge. They often formed large aggregates. Their sizes varied from 16 to 70 μm . Single −1 (carboxylate domain) and 1169, 1119, and 1082 cm−1 (phosphate domain)  spectra of urinary crystals had typical infrared (IR) bands of foscarnet: 1540 and 1395 cm domain) . These F−1. The band at 991 cm−1 was higher than that at 971 cm−1 in patients 1 and 4, but for patients 3 and 6, band intensity at 971 and 991 were equal. Thus, the proportion of both salts in the mix varied from one patient to another.The 4 urine specimens analyzed by IR spectrometry displayed differences in intensity between bands 971 and 991 cmAmong the 6 patients treated with foscarnet and who presented with phosphonoformate crystalluria, 5 of them further developed a kidney injury . PatientAs serum creatinine level increased, the amount of crystals in urine decreased . The semi-quantitative determination of crystals was defined as: +, 1 per 3 high-power fields; ++, 2–4 per high-power fields; and +++, more than 4 per high-power fields defined in The higher the dose of foscarnet administered, the earlier phosphonoformate crystalluria appeared. The 3 patients  who received doses of more than 10 g per day were also those who had the earliest crystalluria, that is, fewer than 10 days after the onset of treatment. On the other hand, the early onset of AKI was not related to high doses of foscarnet .Reduction of foscarnet doses was not associated with any decline in serum creatinine concentrations. Only withdrawal of treatment after short-term treatment (<20 days) allowed reversibility of kidney impairment .We report the first identification of phosphonoformate crystals in urine of patients treated with foscarnet, and describe the time lag between appearance of crystalluria and AKI known to occur in the context of that therapy.,,,Phosphonoformate crystals in material obtained from kidney biopsies have been described as “short polarized sticks with angular edges.”,in vitro experiments, calcium salt is less soluble in urine than sodium salt of phosphonoformic acid. In this report, we have found a mix of sodium and calcium salts of phosphonoformic acid crystallized in urine. On the other hand, we have not found crystals corresponding to trisodium phosphonoformate. Patients 3 and 6 displayed an equal proportion of sodium and of calcium salts, as opposed to the other 2 patients (1 and 4) for which IR band intensity of calcium salts (991 cm−1) were dominant compared with those of sodium salts (971 cm−1). Patients 3 and 6 were also patients with few episodes of crystalluria and who only developed AKI stage 1 as opposed to other patients . An equal proportion of sodium and calcium salts might have attenuated the trend for phosphonoformic acid to crystallize, and thereby the potential severity of kidney injury. If this were true, the spectrum of the crystals and the salt proportion of both salts at IR of urine sediments might turn out to help and predict the degree of severity of kidney damage.Phosphonoformate may crystallize as calcium salt or as sodium salt.Numerous risk factors of drug crystallization have been recognized so farDuration of treatment seems to have an effect on the reversibility of the kidney damage. Indeed, the 3 patients  with the shortest treatment time presented a rapidly reversible AKI.Infusion of large volumes of isotonic saline, 1.5 to 2.5 liters per day, has been demonstrated to reduce kidney toxicity of foscarnet by decreasing the urinary concentration of the drug.Presence of crystalluria is a sign of supersaturation of urine and does not necessarily imply that associated-AKI is due to crystalline nephropathy. In absence of kidney biopsy, only crystalline casts in urine sediment would suggest such a causal link. Unfortunately, crystalline casts are rarely found in urine. On the other hand, white blood cells, renal tubular epithelial cells, or casts in sediment-associated crystalluria indicate also intrarenal crystal-related injury.Presence of foscarnet (phosphonoformate) crystals in urine may be a predictive factor of crystalline nephropathy. However, 5 of the 6 cases received allogeneic hematopoietic stem cell transplantation and presented with variable degrees of thrombocytopenia preventing kidney biopsy to determine the underlying cause of AKI. The discovery of phosphonoformate crystals in urine allows, in these cases, to strongly suspect foscarnet nephrotoxicity without invasive procedure.•Why is it the first time that phosphonoformate crystalluria is described in patients on foscarnet therapy, whereas phosphonoformate crystals have been known for years to be deposited in various organs of patients treated with that drug.•Where do the crystals actually first form? Is it in the glomerular urinary space or in a specific segment of the kidney tubules? This would need to be reconciled with previous observations of phosphonoformate crystal deposition in the lumen of glomerular capillaries.This observation raises new questions, such as the following.The present report highlights the fact that phosphonoformate crystals in urine of patients treated with foscarnet may be taken as a warning signal of imminent development of AKI induced by the drug. This should trigger preemptive measures, such as hyperhydration, dose down-titration, or consideration of an alternative regimen, although conclusive evidence of the effectiveness of those actions is lacking.All the authors declared no competing interests.


A 45-year-old woman presented with upper abdominal and back pain. A cystic lesion in the pancreas and inflammation around the splenic artery were detected by computed tomography. Although imaging studies were difficult to exclude malignancy, pathological and cytological findings of a fine-needle aspiration showed no signs of malignancy. The patient was, therefore, followed-up for 3 months, during which time the cyst increased in size and developed a cyst-in-cyst structure. She was diagnosed with mucinous cyst neoplasm and underwent distal pancreatectomy. Histologically, the patient was diagnosed as low-grade mucinous cystic adenoma. Soft tissue shadows around the splenic artery were considered to indicate fibrosis and infiltration of inflammatory cells. After distal pancreatectomy, the patient has been uneventful with symptom resolution. This case highlights the potentially atypical presentation of mucinous cystic neoplasms with inflammatory cell infiltration around the splenic artery. Mucinous cystic neoplasms (MCNs) are cystic tumors covered with mucus-producing epithelium, with a characteristic ovarian-like stroma. MCNs are relatively rare tumors, accounting for only 2–5% of exocrine pancreatic tumors and occurring most frequently in the distal pancreas in younger women . MCNs ofMost MCNs are slow growing and asymptomatic . Naveed We report a case of mucinous cystic adenoma (MCA) with inflammatory cell infiltration around the splenic artery which was confirmed by pathology. The present case showed atypical imaging findings at the first examination, including infiltration around the splenic artery located at the back of the unilocular cystic lesion. However, during a 3-month observation period, the lesion showed a cyst-in-cyst appearance, thus supporting a preoperative diagnosis of MCN. Although it was difficult to differentiate this case from malignancy at the first examination, the tumor demonstrated morphological changes throughout 3 months of observation.A 45-year-old woman with no previous illnesses presented to the referring hospital with continuous and intractable upper abdominal and back pain, which was unresolved by pharmacotherapy. Plain computed tomography (CT) showed a cystic lesion in the pancreatic body, and the patient was referred to our institution for further examination.The cystic lesion in the pancreatic body had been noted 6 years previously at another hospital Fig. . However18F-fluorodeoxyglucose (FDG)-positron emission tomography combined with CT scan showed mild 18F-FDG accumulation in the papillary side of the cystic lesion   was performed for the soft tissue lesion on the papillary side of the cystic lesion Fig. a, b, conCT scan 3 months later showed a slight increase in cyst diameter Fig. , and magHistologically, the cyst was fibrous and the internal surface was covered with low-grade atypical columnar epithelium Fig. a, b. EstMCNs usually involve unilocular or multilocular cystic lesions, often in the form of a cyst-in-cyst. The differential diagnosis of cystic lesions includes cystic tumors such as intrapapillary mucinous neoplasm and serous cystic neoplasm, as well as non-neoplastic true cysts, pseudocysts, and cystic degeneration of solid tumors . The typKRAS gene [The main complaint in the present patient was epigastric and back pain, which can be caused by localized inflammation around the splenic artery. In this case, no bleeding was observed, and it was not clear if there was a rapid increase in cyst diameter, either of which can cause pain. Although most MCNs are asymptomatic , Yamao eRAS gene . Tissue MCNs have malignant potential, and surgical resection is usually recommended  and can We experienced an unusual case of resected MCA with atypical features of unilocular cyst and soft tissue shadow around the splenic artery. The soft tissue shadow around the splenic artery was difficult to distinguish from an invasive pancreatic ductal carcinoma with retention cyst or an invasive component of malignant MCN, and was difficult to diagnose as benign, even though the EUS-FNA pathology/cytology findings were negative. We hypothesize that the MCN might have caused local pancreatitis and inflammation around the splenic artery in our case.


Primary central nervous system lymphoma (PCNSL) rarely manifests in immunocompetent patients. In such cases, these lesions may mimic more common intracranial bleeding or tumors. We present the case of an elderly patient who presented with a presumed chronic subdural hematoma (SDH); upon surgical intervention, an occult mass was discovered with no evidence of associated hematoma. Biopsy and immunohistochemistry demonstrated PCNSL. Literature review identified six other cases of PCNSL in immunocompetent adults that were initially suspected to be SDH but were finally diagnosed with PCNSL. Our literature review highlights the rarity these cases and the importance of distinguishing intracranial bleeds from PCNSL, as the latter can be treated with chemoradiation with good clinical outcomes. Primary central nervous system lymphoma (PCNSL) is a rare variant of non-Hodgkin’s lymphoma (NHL), which is restricted to the brain, leptomeninges, cranial nerves, spinal cord, or intraocular compartment without involvement of other organ systems. PCNSL comprises 1%-3% of all central nervous system (CNS) tumors and only 2%-3% of NHL cases . -12. 8-12Although our literature review focuses on immunocompetent patients with PCNSL, we recognize that SCNSL can also present like a subdural bleed in patients with a history of B-cell lymphoma. Gonzalez-Bonet et al. described the case of a 71-year-old male who presented with a two-week history of neurological decline after a fall with head impact . AlthougAnother clinical entity to consider is PCNSL presenting with intracranial hemorrhage, which can obscure the lymphoma tumor on neuroimaging. Barrios et al. described the case of a 40-year-old woman who experienced sudden-onset neurological deterioration and was found to have a SDH from a ruptured dural lymphoma lesion on autopsy, along with multiorgan dissemination of small B-cell lymphoma . AlthougPCNSL in immunocompetent patients remains an uncommon diagnosis. As there is low clinical suspicion for such cases, these lesions can easily mimic more typical entities. We present the rare case of a patient with long-standing PCNSL whose clinical course and imaging studies mimicked SDH for several years. Our patient and six others identified via literature review demonstrate how correct diagnosis and appropriate management of PCNSL can result in good clinical outcomes, especially in those with low-grade B-cell lymphomas. We further consider PCNSL presenting with concomitant intracranial bleed, SCNSL mimicking SDH, and other types of intracranial tumors that PCNSL can mimic. Our findings illustrate the rarity of PCNSL mimicking intracranial bleed and the importance of obtaining histopathological diagnosis in these cases.


Oxygen is essentially required by most eukaryotic organisms as a scavenger to remove harmful electron and hydrogen ions or as a critical substrate to ensure the proper execution of enzymatic reactions. All nucleated cells can sense oxygen concentration and respond to reduced oxygen availability (hypoxia). When oxygen delivery is disrupted or reduced, the organisms will develop numerous adaptive mechanisms to facilitate cells survived in the hypoxic condition. Normally, such hypoxic response will cease when oxygen level is restored. However, the situation becomes complicated if hypoxic stress persists (chronic hypoxia) or cyclic normoxia-hypoxia phenomenon occurs (intermittent hypoxia). A series of chain reaction-like gene expression cascade, termed hypoxia-mediated gene regulatory network, will be initiated under such prolonged or intermittent hypoxic conditions and subsequently leads to alteration of cellular function and/or behaviors. As a result, irreversible processes occur that may cause physiological disorder or even pathological consequences. A growing body of evidence implicates that hypoxia plays critical roles in the pathogenesis of major causes of mortality including cancer, myocardial ischemia, metabolic diseases, and chronic heart and kidney diseases, and in reproductive diseases such as preeclampsia and endometriosis. This review article will summarize current understandings regarding the molecular mechanism of hypoxia in these common and important diseases. In metazoan organisms, the oxygen delivery and cellular adaptation to oxygen deprivation are accelerated through the hypoxic signaling pathway in order to sustain oxygen homeostasis . Lack ofHypoxia is usually considered to have pathological effects; however, it also involves in maintaining normal physiological functions. Taking human as an example, the central and peripheral chemoreceptors sense the reduction of oxygen tension and send signals to respiratory center in medulla and pons, where a series of processes are initiated to increase pulmonary ventilation and cardiac output to maintain normal functions of human body. Oxygen exchange occurs in the alveoli of lung with more than 95% of oxygen diffuses into the capillary vessels via the alveolar-capillary exchange system and then binds to hemoglobin. The oxygenated blood returns to left atrium through pulmonary vein. The heart then pumps out the oxygenated blood from left ventricle to its periphery to maintain the proper function of every single cell. In this minireview, we will not discuss the physiological effects of hypoxia but focus on pathological impacts of hypoxia in several key human diseases including cancer, cardiovascular diseases, chronic kidney diseases, metabolic diseases, preeclampsia, and endometriosis. Understanding the disease pathological process shall help us dissecting the molecular mechanisms of causing the disorders and designing better therapeutic regimens against them.Oxygen is essentially required by most eukaryotic organisms as a scavenger to remove harmful electron and hydrogen ions generated as by-products of mitochondrial oxidative phosphorylation. At the cellular level, adaptation involves a switch of energy metabolism from oxidative phosphorylation to anaerobic glycolysis, which increases glucose uptake, and expression of stress proteins related to cell survival or death . All nucImpaired oxygen delivery and consumption are typical features of hypoxia in tumor microenvironment. The rise of hypoxia first comes from the restriction of oxygen diffusion in avascular primary tumors along with the higher oxygen consumption due to hyperproliferation of cancer cells . CellulaThe physiological diffusion of oxygen in microenvironment soon becomes a limiting factor during tumor growth, which stimulates new blood vessel formation (angiogenesis) to provide essential oxygen and nutrients for further tumor outgrowth. Tumor angiogenesis is tightly regulated by multiple pro- and anti-angiogenic factors. HIFs have been identified as master enhancers for vascular endothelial cell migration and proliferation. As a transcription factor, stabilized HIF-1α/β binds to HRE of target genes and transactivates their expression . Among tMalignant tumors tend to exhibit enhanced anaerobic glycolysis as their energy source. This metabolic shift enables cancer cells adapting to microenvironmental stresses including hypoxia . Under hHypoxia/HIF signaling also regulates cellular behaviors, including migration/invasion, intra−/extra-vasation, colonization and tumorigenesis at distant organs, to drive cancer metastasis. EMT is a common process which enables noninvasive  cancer cells to invade and metastasize . It is now clear that hypoxia enhances the metastatic ability through promoting EMT of cancer cells. Hypoxia/HIF signaling directly facilitates the EMT gene profile to induce the invasiveness of cancer cells  through Cancer stem cells (CSCs) expressing stem cell markers  and transcription factors  have been identified to exhibit undifferentiated (stem cell-like) and tumorigenic properties . HypoxicExosomes released to microenvironment have been known to participate in intercellular communication since these extracellular microvesicles containing functional nucleic acids and proteins  . RecentCurrent knowledge based on the large-scale genomic sequencing projects illustrated that the protein-coding transcriptional output is less than 2% in human genome. For recent 20 years, the roles of non-coding RNAs, such as miRNAs, have been extensively studied and their roles in cancer progression have been well-documented . Here, wAtherosclerosis is a chronic inflammatory disease that can increase the risk of myocardial infarction and stroke. The thickness of arterial wall causes hypoxia in the intima, reduces the perfusion of the tissue, and further stimulates proatherosclerotic processes, like inflammation, lipid synthesis, and angiogenesis [Cardiovascular diseases are the leading cause of mortality worldwide, representing 1 of every 3 deaths in 2018. Hypoxia is one of the common features in the pathophysiology of a variety of cardiovascular disorders . Atherosogenesis .As mentioned above, hypoxia simultaneously activates HIF and NF-κB signaling pathways to regulate numerous biological processes Fig. . It shouHif1-α fails to induce Vegf expression and neoangiogenesis. As a result, acute heart failure occurs due to the lack of enough oxygen being delivered to the rapidly increasing cardiac muscle cells [cardiomyocyte- and endothelial cell-specific Hif1-α knockout mice showed 1-week TAC causes severe heart failure phenotype. Moreover, the myocardial capillary density is decreased in these mice, resulting from markedly increased endothelial cell apoptosis [Hif1-α+/− mice have better cardiac function than wild-type mice. They also found Hif-1 promotes the expression of peroxisome proliferator-activated receptor γ (PPARγ), and activates lipid synthesis by engaging glycerolipid and fatty acid uptake genes, and, in turn, induces cell apoptosis [The functional consequences of HIF-1α in cardiomyopathy had been investigated using transaortic constriction (TAC) murine models to mimic pressure-overload heart failure human disease. A 3-week TAC in the mice with cardiomyocyte-specific deletion of le cells . Anotherpoptosis . These rpoptosis . These chas been linked to cardiac dysfunctions in varied cardiac injury models. For example, in intermittent hypoxia-induced myocardial damage, miR-146a-5p promotes cell death by targeting X-linked inhibitor of apoptosis protein [miRNA diagnostic biomarkers that can be targeted using mimetics or inhibitors to alleviate ischemic cardiovascular diseases are warranted.In addition to the transcriptional regulation by HIF-1α and NF-κB, ischemic/hypoxia also modulates cardiofunction via miRNAs at the posttranscriptional level. Numerous miRNAs had been reported to be up- or down-regulated in patients with myocardial ischemia/reperfusion injury  with lower expression of adipose triglyceride lipase (ATGL) and suppresses lipolysis in white adipocytes [Hif-1α mutant developed severe obesity, insulin resistance, and accumulated enlarged lipid droplets in brown adipose tissue with decreased mitochondrial biogenesis after high-fat diet [Phd2 (for constitutive expression of Hif) are resistant to high-fat diet-induced obesity with fewer lipid droplets in white adipose tissue and increased Ucp1 expression in brown adipose tissue [Phd2 induces adiposity in mice under chow diet (low-fat) [Fih, which are resistant to high-fat diet-induced weight gain and hepatic steatosis [Since hypoxia is shown to inhibit fatty acid β-oxidation as a promoter of obesity and inhibit lipogenesis as a suppressor of obesity, several animal studies based on the overexpression or inhibition of HIFs in adipocytes suggest that HIF activation either promotes or inhibits metabolic diseases. As a promoter of obesity, mice overexpressing Hif-1α in adipocytes have elevated obesity and insulin resistance associated with increased inflammation and fibrosis , 59. Adifat diet , 74, 142ipocytes . These oipocytes , 136. Onfat diet . Anothere tissue , while alow-fat) . Similarteatosis . Taken tteatosis , 136.Hif-knockout mice or through some pharmacological HIF inhibitors. These inconsistent consequences might be also due to the complexity of metabolic regulation with the complicated roles of HIFs that extend further than lipid metabolism. Therefore, the actual functions of HIFs in adipocytes and related metabolic diseases must be carefully interpreted relative to different physiological conditions.In summary, studies investigating the functions of HIFs in adipocytes and other metabolic diseases revealed the conflicting results due to different experimental conditions Fig. . The rolAcute kidney injury (AKI) is notorious for its correlation with the development of chronic kidney disease (CKD). AKI is a rapid failure of kidney function, usually caused by decreased blood flow, toxic exposure, and ureteral obstruction. As the injuries are removed, renal cells undergo repair process. However, some of the AKI patients fail to fully recover. Instead, CKD starts to develop, which is characterized by the progressive loss of the kidney function . Events Vhl−/− mice, which have a stable expression of Hif-1α in kidney, researchers found that these transgenic mice exhibit more severe interstitial fibrosis after conduct 5/6 nephrectomy [Tubular injury may lead to renal microvascular loss, which restricts downstream blood flow from glomerular capillaries and contributes to the development of renal hypoxia. Loss of microvasculature, reduced oxygen dispersion, and metabolic abnormality of cells in the kidney are the main causes of the hypoxic state. The initiation of hypoxia is one of the main causes of AKI, which can increase levels of HIF-1α, followed by the induction of TGF-β signaling. During the process of kidney fibrosis, hypoxia and TGF-β1 signaling are excessively upregulated. AKI can be gradually developed into CKD if TGF-β signaling remains hyperactivated for a period of time. Thus, hyperactivation of TGF-β signaling is responsible for the renal fibrosis and can also be identified as the hallmark of CKD. Hypoxia is common at the beginning of kidney fibrosis, which promotes HIF-1α expression that contributes to both a result and a cause of renal fibrosis. Hyperactivation of myofibroblasts is responsible for kidney fibrosis as they continuously produce collagens, fibronectin, and vimentin, which contribute to tubulointerstitial fibrosis and local tissue hypoxia , 143. Prhrectomy . In conthrectomy . These dPreeclampsia is a severe gestational complication featured by new onset of high blood pressure after 20 weeks of gestation along with signs of proteinuria, abnormally high serum creatinine, or damaged liver function . Its comDefective trophoblast invasion leads to placental hypoxia. The trophoblast invasion is regulated by endocrine gland-derived vascular endothelial growth factor  . EG-VEGFPrimary cilium functions as a sensory hub for transducing environmental chemo- and/or mechano-signaling into the cells for proper development and differentiation. Growing body of evidence supports the important role of primary cilium in maintaining embryo development. Interestingly, hypoxia suppresses primary cilium formation , and eleDespite the role of hypoxia in preeclampsia has been demonstrated for long, the underlying molecular mechanism remains unclear. Trophoblast invasion is triggered by the binding of EG-VEGF to its congenital receptor on the primary cilium, thus inducing downstream ERK signaling for MMPs expression. Disruption of primary cilium inhibits trophoblast invasion even in the presence of EG-VEGF, supporting the importance of cilia-mediated EG-VEGF signaling . BesidesEndometriosis is one of the most common gynecological diseases that reduces life quality and fertility of patients worldwide. It is characterized by the presence of endometrial tissue outside the uterine cavity and the incidence rate of endometriosis is around 8 to 15% in women of the reproductive age . The etiEndometriosis is initiated by retrograde menstruation. The retrograded endometrial tissues need to land on the surface of organs in the peritoneal cavity and implant in order to survive ectopically. Two challenges that the retrograded cells have to face are hypoxic stress and adhesive ability. Recently, two studies reported that hypoxia enhances cell adhesive ability of the endometrial stromal cells by inducing the expression of cell adhesion molecules such as integrin α5, αV, β3, and β5 via TGF-β1/Smad signaling and anthrax toxin receptor 2 (ANTXR2) via HIF-1α-dependent manner , 87. Fur2) and prostaglandin E2 (PGE2) are crucial factors for the development of endometriosis [2  and PGE2  biogenesis are aberrantly expressed in endometriotic stromal cells [2 and PGE2 production but also causes the regression of endometriotic lesion in the mouse model of endometriosis [2 and PGE2 via the assistance of hypoxia to support their growth and development.Previous studies have revealed that both estrogen (Eetriosis , 172 andal cells , 173. Ital cells . Furtheral cells . Finallyal cells . The sametriosis . These dTo sustain the growth of endometriotic lesion in the hostile peritoneal cavity, new blood vessels must be established to provide oxygen and nutrient. Heterograft animal model of endometriosis by implanting human eutopic endometrium into severe combined immunodeficiency mice has identified that hypoxia pretreatment for eutopic endometrium significantly increases the level of VEGF to promote cell proliferation and angiogenesis in vivo . Critica2O2 or low nutrient treatment [Peritoneal cavity is an unfavorable microenvironment for the retrograded endometrial tissues due to lack of blood vessel to supply oxygen and nutrients. The study has reported that the higher level of oxidative stress-induced DNA damage is observed in endometriotic specimen compared to the normal endometrial tissues . Furtherreatment . In summThe mechanisms of cellular response to hypoxia contribute to stress-induced pathophysiological outcomes. Previous studies established the fundamental concept of hypoxia biology, while recent advances in molecular and cellular biology such as non-coding RNA and microvesicle accelerate us to demonstrate a more complete and complex view of the regulatory network under hypoxia. Notably, most of these new findings were found to be closely integrated in the canonical hypoxia pathway, suggesting a fine-tuned cellular machinery with multiple pathways cooperatively, synergistically, or mutual exclusively work together to modulate the transduction of hypoxia signaling. Identification of these new sensors, messengers, and functional modulators not only advances our knowledge of hypoxia biology but also provides insights into the development of potential diagnostic and therapeutic approaches.


A major bottleneck in developing clinically impactful machine learning models is a lack of labeled training data for model supervision. Thus, medical researchers increasingly turn to weaker, noisier sources of supervision, such as leveraging extractions from unstructured text reports to supervise image classification. A key challenge in weak supervision is combining sources of information that may differ in quality and have correlated errors. Recently, a statistical theory of weak supervision called data programming has shown promise in addressing this challenge. Data programming now underpins many deployed machine-learning systems in the technology industry, even for critical applications. We propose a new technique for applying data programming to the problem of cross-modal weak supervision in medicine, wherein weak labels derived from an auxiliary modality  are used to train models over a different target modality . We evaluate our approach on diverse clinical tasks via direct comparison to institution-scale, hand-labeled datasets. We find that our supervision technique increases model performance by up to 6 points area under the receiver operating characteristic curve (ROC-AUC) over baseline methods by improving both coverage and quality of the weak labels. Our approach yields models that on average perform within 1.75 points ROC-AUC of those supervised with physician-years of hand labeling and outperform those supervised with physician-months of hand labeling by 10.25 points ROC-AUC, while using only person-days of developer time and clinician work—a time saving of 96%. Our results suggest that modern weak supervision techniques such as data programming may enable more rapid development and deployment of clinically useful machine-learning models. •We propose cross-modal data programming (XMDP) for machine learning (ML) in medicine•XMDP reduces labeling costs by 96% versus hand labeling on 4 diverse medical ML tasks•Days of XMDP and years of hand labeling often yield similarly performing models•XMDP performance continually improves as more unlabeled data becomes available Machine learning can achieve record-breaking performance on many tasks, but machine learning development is often hindered by insufficient hand-labeled data for model training. This issue is particularly prohibitive in areas such as medical diagnostic analysis, where data are private and require expensive labeling by clinicians.A promising approach to handle this bottleneck is weak supervision, where machine learning models are trained using cheaper, noisier labels. We extend a recent, theoretically grounded weak supervision paradigm—data programming—wherein subject matter expert users write labeling functions to label training data imprecisely rather than hand-labeling data points. We show that our approach allows us to train machine learning models using person-days of effort that previously required person-years of hand labeling. Our methods could enable researchers and practitioners to leverage machine learning models over high-dimensional data  even when labeled training sets are unavailable. Machine learning (ML) models have achieved record-breaking performance on many tasks, but development is often blocked by a lack of large, hand-labeled training datasets for model supervision. We extend data programming—a theoretically grounded technique for supervision using cheaper, noisier labels—to train medical ML models using person-days of effort that previously required person-years of hand labeling. We find that our weakly supervised models perform similarly to their hand-labeled counterparts and that their performance improves as additional unlabeled data becomes available. Similar problems in both industry and academia have recently been addressed using advances in weak supervision, where training data can be rapidly labeled in noisier, higher-level, often programmatic ways rather than manually by experts. The statistical intuition behind these techniques is that a larger volume of noisier training data can sometimes be more effective than a smaller amount of hand-labeled data. Similar ideas have historically driven a rich set of work on topics such as template-based systems for knowledge-base construction,,,A common difficulty in applying weak supervision methods in medicine is that providing even noisy labels can be difficult if only raw image or sensor data are available. In this context, a promising approach is one we call cross-modal weak supervision, where noisy labels are programmatically extracted from an auxiliary modality  and then used to train a model over a target modality . At test time, we would like to obtain a prediction from the target modality but usually do not have access to the auxiliary modality—for instance, the text report has not yet been written when the image is first acquired. Recent research in medical imaging has used cross-modal weak supervision by applying natural language-processing techniques to clinical reports accompanying the images of interest.,,The key technical challenge in applying such weak supervision techniques in practice is combining sources of information that may overlap, conflict, and be arbitrarily correlated in order to provide accurate training labels for a machine learning algorithm. While a variety of previous cross-modal weak supervision approaches have shown promise in medical applications, studies performed to date have generated weak labels from text in ad hoc, application-specific ways. Specific strategies reported in the medical literature range from combining pre-existing disease tagging toolsIn this work, we propose a theoretically grounded, application-agnostic approach to cross-modal weak supervision and apply this technique to diverse, institution-scale hand-labeled clinical datasets to perform the first comprehensive study of cross-modal weak supervision in medicine. Such a study allows us to directly assess both the merits of our proposed approach and the broader translational potential of models trained using cross-modal weak supervision across multiple clinical use cases. We directly compare our cross-modal weak supervision technique with hand labeling along three principal axes: absolute model performance, model performance improvement with additional training data, and the type and amount of labeling resources required. We further evaluate how our supervision approach improves model performance via a series of ablation studies. We make four distinct contributions in the course of this work.,First, we propose a single, uniform approach to cross-modal weak supervision that is theoretically grounded, is applicable across diverse medical-use cases, and exhibits high levels of performance when compared with hand labeling. We base our technique on data programming, an application-agnostic weak supervision technique recently developed and theoretically analyzed by Ratner et al.,,,Second, to support an analysis of cross-modal weak supervision that generalizes across applications, we curate four diverse medical datasets in applications spanning CXR and knee extremity radiograph (EXR) triage, intracranial hemorrhage identification on head CT (HCT), and seizure onset detection on electroencephalography (EEG), each of which has important clinical implications previously described in the literature.Third, we present empirical evidence that models for clinically important applications that have been trained using cross-modal weak supervision can perform similarly to those trained using large hand-labeled datasets while providing several practical advantages. Across applications, we find that models weakly supervised using cross-modal data programming over all available data outperform models trained with physician-months of hand-labeled data by an average of 10.25 points of area under the receiver-operating characteristic curve (ROC-AUC). We additionally find that models trained using cross-modal data programming over all available data achieve on average within 1.75 points ROC-AUC of models trained using hand labels over all available data, which required physician-years to obtain. These results suggest that cross-modal data programming can yield models with similar clinical utility to those trained with hand labels. We further observe that the performance of models trained using cross-modal data programming and hand labeling both improve with additional training data, and often at similar rates. Not only is this behavior consistent with theoretical predictions, but it also emphasizes that weakly supervised model performance can be improved by providing more unlabeled data with no additional clinician effort. Finally, we find that cross-modal data programming required less than 8 h of clinician time per application, which was largely spent defining simple pattern-matching or ontology-lookup heuristics over clinical text reports. In our experiments, models trained with cross-modal data programming achieved statistical equivalence to those trained using hand labels while providing an average 96% saving in labeling time. Our results provide evidence that cross-modal data programming can lower a substantial barrier to machine-learning model development in medicine by reducing the labeling time required from domain experts by orders of magnitude while maintaining high levels of performance.Fourth, our ablation studies demonstrate that modeling steps within cross-modal data programming result in target modality models that perform up to 6 points ROC-AUC better than those trained using majority vote of clinician-provided heuristics, which serves as a proxy for common rule-based approaches to cross-modal weak supervision. Our analysis suggests that these performance improvements are caused by increases in both the coverage and quality of the weak labels with respect to the majority-vote baseline, and that our proposed neural network approach emits weak labels that yield a statistically significant performance improvement for target modality models. We find that these gains are more pronounced on screening tasks such as radiograph triage and marginal on more targeted detection tasks such as hemorrhage or seizure detection on which clinician-provided heuristics are both highly accurate and cover most of the dataset. Thus, we not only demonstrate that the specific cross-modal weak supervision technique proposed in this work can improve performance over strong baselines but also identify the clinical contexts in which each component of our approach may be particularly useful.We first describe technical details of our cross-modal data programming approach. We then provide an overview of the institution-scale, hand-labeled datasets curated for this study and outline our process for applying cross-modal data programming to these use cases using a consistent procedure. We next compare models trained using cross-modal data programming against their hand-labeled counterparts, assessing absolute levels of performance, performance scaling with the amount of training data, and required labeling resources. Finally, we assess the empirical utility of each component of our cross-modal data programming modeling approach via a series of ablation studies and discuss important implications of our results for translational medicine.The data programming method of Ratner et al.In cross-modal data programming , users sGiven The result of this first modeling stage is a set of probabilistic or confidence-weighted training labels The resulting model The cross-modal setting presents an opportunity to improve this basic data-programming pipeline via an additional modeling step that we propose here. Specifically, the probabilistic training labels In this way, we can produce a set of training labels that approximately retains the favorable statistical properties described above but provides useful labels for every element of the training set. The target modality model is then trained exactly as in As illustrated in We propose using cross-modal data programming as an exemplar technique for evaluating the efficacy of training medical machine learning models with cross-modal weak supervision for several compelling reasons. First, data programming naturally extends and improves upon common rule-based methods by using unsupervised statistical modeling techniques to automatically denoise potentially overlapping and conflicting heuristic functions in a way that provides more accurate, probabilistic training labels to deep learning models.We use the theoretically grounded cross-modal data programming approach described above to assess the performance of cross-modal weak supervision in four real-world medical applications  spanningFor each application, we apply the cross-modal data-programming approach described above, which is implemented as an extension to the SnorkelWe use this cross-modal data-programming approach to empirically assess the hypothesis that cross-modal weak supervision methods can reduce the amount of labeling resources required to build useful machine-learning models across diverse clinical settings. We compare the absolute performance of cross-modal data programming with hand-labeled supervision in ,,,We first assess the degree to which models trained with cross-modal data programming and standard model architectures see  can appr,A major trend in the modern clinical world is that large amounts of digitized medical data are increasingly accessible, but important information is often encoded in unstructured forms  that are not suitable for supervising machine-learning models. We therefore evaluate whether cross-modal weak supervision can harness these growing unstructured data resources without requiring additional clinician effort. Specifically, we assess the performance of the target modality model when additional unlabeled data are weakly labeled using cross-modal data programming, but without any modification of the fixed set of clinician-authored LFs. In We also analyze the time and input complexity that were required of clinicians in cross-modal data programming relative to hand-labeling data. On average, 14 LFs comprising on average six lines of code each were developed per application, using a mix of general text patterns , medical text patterns , and structural heuristics , as described in A final hypothesis of this work is that modeling steps within cross-modal data programming are important to providing performance benefits for the target modality model. We evaluate this hypothesis in two steps. First, we assess the quality of weak labels emitted from each step in the modeling pipeline of Performance of each text model on the development set is presented in In In this work, we have performed the first comprehensive study of cross-modal weak supervision in medicine and have empirically assessed the hypothesis that cross-modal weak supervision methods can reduce the amount of labeling resources required to build useful machine learning models across diverse clinical settings. We have analyzed this class of techniques by proposing the cross-modal data programming approach, applying it to clinically relevant applications spanning radiography, CT, and EEG, and performing a direct comparison with large-scale hand labeling. Our results show that cross-modal weak supervision can enable clinicians to rapidly generate large training sets in a matter of hours or days that match or exceed the performance of large, hand-labeled training sets that took months or years of physician time to annotate. We have further provided evidence that weak supervision approaches such as cross-modal data programming can be used to train models that increase in quality as more unlabeled data become available, making efficient use of clinician resources.,Our results also suggest specific situations in which modeling the labeling process can improve the performance of weakly supervised models in medical imaging and monitoring. In the CXR and EXR applications on which generative and discriminative modeling over the text was able to provide more useful sets of labels for target modality model training, clinician LFs tended to be quite accurate but relatively low-coverage. Such a pattern would be expected in screening applications such as radiograph triage wherein the variety of pathologies that can appear on a scan is large.Several limitations should be considered when interpreting the results of this study. First, because we use data sourced from a single hospital, our results do not address cross-institutional model validation. While substantial resources are required to de-identify and make publicly available datasets of the sizes considered here, we hope that continued progress on this front will allow for future work that addresses this important question. Second, although the statistical estimation techniques underlying cross-modal data programming do handle the multi-class setting, this work focuses on well-defined binary tasks. Third, cross-modal data programming is limited to cases wherein an auxiliary modality exists, is readily available, and is amenable to rapid LF specification. Finally, our study assumes the existence of reference neural network architectures for each diagnostic modality; while this is often valid in computer vision, additional resources may be required to create high-performance models for other diagnostic modalities. Addressing each of these points would be a natural and valuable direction for future research.Remaining challenges associated with translating this work to clinical practice mirror those usually faced by machine learning systems for decision support in medicine. In addition to well-documented regulatory hurdles, these include integrating rapid model iteration and data collection workflows into hospitals and care centers, designing robust testing infrastructures to support continual model improvement while guarding against critical failure modes, and training physicians to best make use of these algorithms.The purpose of this study is to assess the hypothesis that cross-modal weak supervision techniques such as cross-modal data programming can enable rapid construction of useful machine learning models across diverse clinical-use cases. Each dataset analyzed here was retrospectively collected from our institution, and Institutional Review Board (IRB) approval was obtained from our institution (Stanford University) in each case. In each dataset, different patients were randomly assigned to training, development, and held-out test sets, and subsets of the training set were chosen via random sampling. The study was blinded in the sense that the study authors were unaware of which patients were in the train, development, and test sets.Text models were trained using the SnorkelDetails of dataset composition, preprocessing routines, training procedures, and neural network architectures for each target modality model are provided below. LFs for each application and an annotated, functional Jupyter notebook tutorial applying the cross-modal data-programming technique to a publicly available CXR dataset are provided in ,As the demand for imaging services increases, automated triage for common diagnostics such as CXRs is expected to become an increasingly important part of radiological workflows.For this task, a radiology fellow wrote 20 LFs over the text in less than 8 h of cumulative clinician time, using a labeled development set of 200 reports. These LFs were implemented in Python with several hours of assistance from a computer science graduate student. These LFs represent a combination of pattern-matching, comparison with known knowledge bases, and domain-specific cues. In the context of chest radiography, the impression and findings sections of the radiology report tend to be the most informative; thus, the majority of LFs considered text within these sections. Once LFs had been generated, tools within the Snorkel software package were used to generate sets of probabilistic training labels.,,Z-score normalized using global mean and standard deviation values computed across the dataset, and replicated over three channels  before injection into the training loop. Each model over 50,000 images took approximately 6 h to train.The image model used for this task was an 18-layer Residual Network (ResNet-18) with a sigmoid nonlinearity on top of a single-neuron final layer, which yields near-state-of-the-art results on this dataset at a modest computational cost.Because each image is associated with a unique report, evaluation is performed on a simple image-by-image basis, using ROC-AUC as the evaluation metric.Musculoskeletal disorders are generally diagnosed from imaging, and their substantial prevalence makes them a natural target for automated triage systems; in this work, we specifically focus on detecting musculoskeletal disorders of the knee from multiple-view radiograph series. We originally obtained a dataset of 3,564 patient exams prospectively labeled as normal or abnormal in the same manner as described for chest radiography, containing a total of 37,633 individual images and 3,564 reports. A single exam can have a variable number of radiographs across different views, as collection protocols are not standard for this type of exam. The dataset was pulled from the PACS system in such a way that it contains a 50:50 distribution of normal and abnormal cases (as indicated by the prospective label). We split the dataset such that images from a randomly sampled 3,008-patient cohort are available for training both fully supervised and weakly supervised models, with images from 200 patients available for cross-validation. We then obtained retrospective labels for each image in a held-out test set of 356 patient exams  where a single radiologist with 9 years of training provided a normal or abnormal label with no time constraints. We used this set of 356 exams for evaluation on a patient-by-patient basis. Examples of knee radiographs can be found in For this task, a single radiology fellow wrote the 18 LFs within 8 h of cumulative clinician time, which were implemented in Python with several hours of assistance from a computer science graduate student using a development set of 200 labeled reports. These LFs use a variety of pattern-matching and semantic cues to identify reports as either normal or abnormal. While there is some overlap between these LFs and those for the CXRs , LFs nonetheless had to be adapted for this specific application. Probabilistic labels were then generated from these LFs using tools in the Snorkel software package.,Z-score normalized using global mean and standard deviation values computed across the dataset, and replicated over three channels  before injection into the training loop. Batch size was set at 60 radiographs, the maximum possible on the single 1080 Ti GPU that was used to train each model. Models over 30,000 training images took approximately 6 h to train. For each exam in the test set, we compute an output score by taking the mean of the image model outputs for all radiographs in the exam following Rajpurkar et al.The image model for this task takes a single radiograph as input and outputs the probability that this radiograph is abnormal. We use a 50-layer Residual Network (ResNet-50) architecture modified to emit a binary classification result on each radiograph in the training set, and leverage ImageNet-pretrained weights for model initialization.The problem of rapid intracranial hemorrhage detection on CT of the head (HCT) represents an important task in clinical radiology to expedite clinical triage and care.The seven LFs for the hemorrhage detection task were written in Python entirely by a single radiology resident in less than 8 h of cumulative development time using a labeled development set of 200 reports. Notably, these LFs programmatically combine many possible expressions for normality or hemorrhage that are drawn from this radiologist's personal experience. Again, probabilistic labels are generated from these LFs using tools in the Snorkel software package.The hemorrhage detection task fits naturally with the framework of MIL because we have a single label per CT scan, each of which contains 32 image slices. Furthermore, if a CT image is labeled as positive, there must exist at least one slice that contains evidence of a hemorrhage. We leverage the attention-based MIL approach recommended by Ilse et al.Z-score normalized using global mean and standard deviation values computed across the dataset. Model training is accomplished using the stochastic gradient descent optimizer in PyTorch with a learning rate that was initially set to a high value of 0.1 and reduced upon plateaus in the validation loss, a momentum of 0.9, and a weight decay value of 0.005. Models over the full dataset were trained for 30 epochs with early stopping, and use an equivalent number of batches for models trained on subsets of the dataset. Batch size was set at 12 CT scans, the maximum possible using the single Tesla P100 GPU that was used to train each model. Training each model on the full set of images took approximately 6 h.Our attention-based MIL model uses a randomly initialized ResNet-18 encoder with an output size of 50. Each slice is downsampled to dimensions of 224 × 224 and Because only 39 of the 340 consensus-labeled examples were positive for hemorrhage, the end-model performance metrics could be sensitive to the random splitting of the test and development datasets. We therefore carry out a cross-validation procedure where we repeat the stratified 50:50 development set/test set split using the 340 gold-labeled data points, and analyze average model performance over five trials with different random seeds, where one of the seeded operations was the development set/test set split.One of the most common tasks performed using EEG is epileptic seizure detection, where an epileptologist examines large amounts of time-series data to determine whether the repeated, uncontrolled electrical discharges suggestive of seizure activity have occurred. Our EEG dataset comprises 36,644 pediatric EEG signals from our institution along with 9,496 EEG reports. Each EEG report can reference multiple signals, and each signal can be referenced by multiple EEG reports. Each signal is annotated by an EEG technician with onset times of possible seizures, which we treat as full hand-labeled supervision for a machine-learning model for seizure detection. To ensure consistency across exams, each of which could have a unique sensor alignment, we use only signals from the 19 electrodes in the standard 10-20 International EEG configuration, which forms a subset of the electrodes deployed to every patient at our institution. Voltage readings from each channel are sampled at 200 Hz. We approach the seizure-onset detection problem as a clip-level classification problem over 12-s clips of the full time series. Our model maps an input The 11 LFs used to determine whether a given EEG clip contains seizure onset were written collaboratively by a clinical neurologist and a postdoctoral computer scientist over the course of less than 8 cumulative hours of dedicated time using a labeled development set of 200 reports. These LFs simultaneously leverage the structure of the EEG report along with unstructured information contained in the raw text, which can often cover several paragraphs. The Snorkel software package is then used to create probabilistic labels for each report.Because these reports refer to entire signals rather than to specific clips, a small hand-labeled EEG clip dataset for cross-validation and end-model evaluation was created by a pediatric clinical neurologist with 10 years of experience. This dataset contains 350 12-s clips representative of seizure onset; 100 of these positive examples are allocated to a development set for cross-validating the end model and 250 are allocated to the test set for final evaluation. Sets used for both cross-validation and evaluation were made to contain an 80% fraction of clips without seizure onset by randomly sampling clips from signals in each set confirmed to contain no evidence of seizure. We use a densely connected Inception architecture inspired by Roy et al.−6 and reduced by a factor of 0.1 upon plateaus in the validation loss, and a dropout probability of 0.2 was applied to the last layer. We train models on the full dataset for 30 epochs with early stopping and use an equivalent number of batches for models trained on subsets of the dataset. Plentiful negative examples were undersampled such that the train set contained 50% positive examples. Batch size was set at ten EEG signals, the maximum possible using the single Tesla P100 GPU that was used to train each model. Training each model on the full set of signals took approximately 12 h.Model training is accomplished using the Adam optimizer in PyTorch, learning rate was initially set to a value of 1 × 10α) threshold of 0.05 was used for all reported tests. All ROC-AUC values were computed using the entire test sets described above. Confidence intervals reported in plots are standard 95% confidence intervals assuming a normally distributed population.All statistical tests performed in this work are two-tailed DeLong non-parametric tests


Spasticity is common in long-term care settings (affecting up to one in three residents), yet it remains under-treated despite safe and effective, Food and Drug Administration (FDA)-approved therapies. One barrier to treatment may be lack of awareness of available therapies for long-term care residents living with spasticity. A standardized spasticity treatment awareness and interest interview was conducted with 18 nursing home residents and 11 veterans’ home residents in this cross-sectional study. Veterans’ home residents were also asked about potential barriers to receiving spasticity treatment. Many residents across both long-term care facilities were unaware of most of the treatment options for spasticity. Participants were most aware of physical/occupational therapy  and least aware of intrathecal baclofen . After learning about treatments, only 7% of participants (95% CI: 0–23%) were not interested in receiving any form of spasticity treatment. Among residents previously unaware of spasticity treatments, at least one quarter became interested in receiving treatment and at least one-fifth indicated possibly being interested in the treatment after learning about it. Potential barriers to receiving treatment included traveling to see a doctor and limited knowledge of insurance coverage of spasticity treatments. These results suggest that patient-centered approaches, including education and discerning patient preferences, may improve spasticity treatment in long-term care settings. Spasticity affects up to one-third of residents in long-term care settings but remains largely undiagnosed and undertreated ,2,3,4. TSafe and efficacious treatments for spasticity include physical/occupational therapy, medications, and surgery. These treatments can enhance quality of life by improving care delivery and restoring ADL function ,11. AlthParticipants in this study include residents of two long-term care facilities who participated in prior research projects and completed treatment awareness interviews as part of this investigation. At the first long-term care facility, the prevalence of spasticity in a single 240-bed university-affiliated nursing home was evaluated as part of a quality-improvement project conducted at the direction of the facility’s medical director (Vanderbilt IRB #071234) [In both cohorts, participants with spasticity were asked to complete a treatment awareness interview, and interviews were conducted in-person at the long-term care facility by trained research assistants. The treatment awareness interview consisted of a standardized survey designed to evaluate the participant’s awareness of and willingness to consider each of five available spasticity treatments: oral medications, physical/occupational therapy (PT/OT), neurotoxin injections, intrathecal baclofen, and orthopedic procedures. Participants were asked if they were aware of each treatment . Operational definitions of each treatment were then read aloud. Specific names of therapies were excluded from definitions to focus the description on how the therapy would be administered and the most common problem associated with the treatment. Participants were then asked if they would be interested in possibly receiving each treatment . Interviews conducted at the veterans’ home ended with an additional brief set of questions designed to evaluate potential barriers to treatment not captured in the treatment awareness interview. These questions covered five potential barriers: physician appointment scheduling, access to specialty care, transportation to physician offices, perceived efficacy of available therapies, and awareness of insurance coverage of available therapies.Survey data were analyzed using descriptive statistics. The Agresti-Coull method was used to determine 95% confidence intervals (CI) for proportions. Analysis was performed using STATA 15.1 .n = 7), while others had cerebral palsy (n = 1) and multiple sclerosis (n = 1). The majority of nursing home participants were not receiving any treatment for spasticity , while two were receiving oral baclofen.Eighteen nursing home residents with spasticity  completed the treatment awareness interview. Most residents approached for an in-person interview provided informed consent and completed the interview , but among residents not competent to make medical decisions, only two medical decision makers provided informed consent . Nursing home participants were 61% female (11/18) with a mean age of 79.5 ± 14.1 years . Eighty-Eleven veterans’ home residents with spasticity  completed the treatment awareness interview. Veterans’ home participants were all male (11/11) with a mean age of 77.5 ± 8.2 years . None ofn = 29), participants were most aware of physical/occupational therapy  were not interested in receiving any form of spasticity treatment (10% (95% CI: 3–27%) were unsure). Participants across both facilities were most interested in physical/occupational therapy  and least interested in therapies requiring surgery: intrathecal baclofen  and orthopedic procedures . Among residents previously unaware of spasticity treatments, at least one-quarter became interested in receiving treatment and at least one-fifth indicated possibly being interested in the treatment after learning about it . Among nNearly two-thirds of veterans’ home participants thought that their quality of life would improve with spasticity treatment  are unaware of most of the available spasticity treatment options but also that many are interested in the treatments once informed about them. Additional exploration of potential barriers to treatment revealed perceived challenges regarding travel to the doctor’s office and insurance coverage of spasticity treatments. Participants from both long-term care facilities had more awareness of than interest in receiving physical/occupational therapy, likely because these are commonly offered in long-term care settings and also in acute care settings for medical situations that often lead to long-term care placement. Participants’ interest in oral medications and neurotoxin injection exceeded their awareness of these treatments, and a majority of residents previously unaware of these treatments indicated interest or potential interest in receiving them after learning more about them. This result highlights a potential opportunity to expand education about these treatments to residents, their medical decision makers, and their healthcare providers. Across all spasticity therapies presented, more than one out of five previously unaware residents indicated they might be interested in receiving treatment, which suggests that further education may lead to receiving spasticity treatment. Both cohorts were more averse to spasticity therapies requiring surgery  than other treatment options, consistent with patients preferring less invasive therapies for other conditions . Female Spasticity is prevalent in long-term care facilities (up to one-third of residents) ,2,3,4, aWhile this study reports similar results from residents of two long-term care facilities, the small sample size at each center limits the generalizability of these findings. Most veterans’ home residents with spasticity completed this interview (79%), compared to only 40% of nursing home residents with spasticity. This discrepancy in participation is attributed to the proportion of residents able to answer the survey at each facility, with nearly half of nursing home residents with spasticity requiring a medical decision maker in order to participate. The reliance on medical decision makers to conduct clinical research studies in long-term care settings remains a challenge . MedicalThese results suggest that many long-term care residents living with spasticity are unaware of all treatment options available to them but are interested in receiving spasticity treatments after learning about them. More work is needed in a larger population to evaluate long-term care resident awareness of and interest in the wide variety of safe and effective spasticity treatments available. A more patient-centered approach that combines patient, medical decision maker, and provider education with informed patient preferences will likely improve access to spasticity treatment in long-term care settings.