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No predictive biomarkers can robustly identify patients with non–small cell lung cancer (NSCLC) who will benefit from immune checkpoint inhibitor (ICI) therapies. Here, in a machine learning setting, we compared changes (“delta”) in the radiomic texture (DelRADx) of CT patterns both within and outside tumor nodules before and after two to three cycles of ICI therapy. We found that DelRADx patterns could predict response to ICI therapy and overall survival (OS) for patients with NSCLC. We retrospectively analyzed data acquired from 139 patients with NSCLC at two institutions, who were divided into a discovery set (D1 = 50) and two independent validation sets (D2 = 62, D3 = 27). Intranodular and perinodular texture descriptors were extracted, and the relative differences were computed. A linear discriminant analysis (LDA) classifier was trained with 8 DelRADx features to predict RECIST-derived response. Association of delta-radiomic risk score (DRS) with OS was determined. The association of DelRADx features with tumor-infiltrating lymphocyte (TIL) density on the diagnostic biopsies (n = 36) was also evaluated. The LDA classifier yielded an AUC of 0.88 ± 0.08 in distinguishing responders from nonresponders in D1, and 0.85 and 0.81 in D2 and D3. DRS was associated with OS [HR: 1.64; 95% confidence interval (CI), 1.22–2.21; P = 0.0011; C-index = 0.72). Peritumoral Gabor features were associated with the density of TILs on diagnostic biopsy samples. Our results show that DelRADx could be used to identify early functional responses in patients with NSCLC.

Malignancy has long been implicated with hypercoagulability, leading to an increased rate of both venous and arterial thromboembolic events (VTE and ATE). Immunotherapy has established itself as a cornerstone of modern cancer therapy by promoting antitumor immune responses, though there have been some suggestions that immune-related adverse events could include increased rates of VTE and ATE. In this review, we examine the available evidence regarding the use of immune checkpoint inhibitors (ICIs) and thrombosis. First, we describe the potential mechanisms by which ICIs might lead to thrombophilia given the overlap between the immune system, coagulation cascade, and platelet adhesion and activation. In addition, while there are some preclinical data evaluating immunotherapy-associated ATEs in animal models, there is a paucity of evidence exploring potential mechanism of VTEs in ICIs. Second, we review the incidence of ATE and VTE in patients receiving ICIs in the published literature. Finally, we discuss current limitations in understanding, areas of conflicting evidence, and approaches to further investigation.

OBJECTIVE: To review the epidemiology, presentation, diagnosis, and management of head and neck paragangliomas. METHODS: A literature review of english language papers with focus on most current literature. RESULTS: Paragangliomas (PGLs) are a group of neuroendocrine tumors that arise in the parasympathetic or sympathetic ganglia. Head and neck PGLs (HNPGLs) comprise 65% to 70% of all PGLs and account for 0.6% of all head and neck cancers. The majority of HNPGLs are benign, and 6% to 19% of all HNPGLs develop metastasis outside the tumor site and significantly compromise survival. PGLs can have a familial etiology with germline sequence variations in different susceptibility genes, with the gene encoding succinate dehydrogenase being the most common sequence variation, or they can arise from somatic sequence variations or fusion genes. Workup includes biochemical testing to rule out secretory components, although it is rare in HNPGLs. In addition, imaging modalities, such as computed tomography and magnetic resonance imaging, help in monitoring in surgical planning. Functional imaging with DOTATATE-positron emission tomography, 18F-fluorodeoxyglucose, or 18F-fluorohydroxyphenylalanine may be necessary to rule out sites of metastases. The management of HNPGLs is complex depending on pathology, location, and aggressiveness of the tumor. Treatment ranges from observation to resection to systemic treatment. Similarly, the prognosis ranges from a normal life expectancy to a 5-year survival of 11.8% in patients with distant metastasis. CONCLUSION: Our review is a comprehensive summary of the incidence, mortality, pathogenesis, presentation, workup and management of HNPGLs.

BACKGROUND: Our objective was to explore whether differences in patient satisfaction based on gender exist at the Veterans Affairs Portland Health Care System (VAPHCS) outpatient chemotherapy infusion unit. METHODS: Veterans who received outpatient infusion treatments at the VAPHCS outpatient chemotherapy infusion unit from 2018 to 2020 were invited to take an anonymous survey. Response differences were analyzed using Fisher exact and Welch t tests. Male and female patient lists were first generated based on Computerized Patient Record System designation, then defined and results reported based on gender self-identification from survey responses. RESULTS: The survey was conducted over a 2-week period during January and February of 2021. In total, 69 veterans were contacted: 21 (70%) of 30 female and 20 (51%) of 39 male veterans completed the survey. Most (62%) female patients were aged < 65 years, and 52% were treated for breast cancer. Most (90%) male patients were aged ≥ 65 years, and most commonly treated for prostate cancer (20%) or a hematologic malignancy (20%). Using our survey, patient satisfaction (SD) was 8.7 (2.2) on a 10-point scale among women, and 9.6 (0.6) among men (P = .11). History of sexual abuse or harassment was reported by 86% of women compared with 10% of men (P < .001). Women reported feeling uncomfortable around other patients in the infusion unit compared with men (29% vs 0%; P = .02) and discomfort in relaying uncomfortable feelings to a clinician (29% vs 0%; P = .02). CONCLUSIONS: Gender seems to be related to how veterans with cancer perceive their ambulatory cancer care. This may be due to the combination of a high history of sexual abuse and/or harassment among women who represent a minority of the total infusion unit population, the majority of whom receive treatment for a primarily gender-specific breast malignancy. Analysis was limited by the small sample size of women, many with advanced malignancy.

OBJECTIVE: To identify stable and discriminating radiomic features on non-contrast CT scans to develop more generalizable radiomic classifiers for distinguishing granulomas from adenocarcinomas. METHODS: In total, 412 patients with adenocarcinomas and granulomas from three institutions were retrospectively included. Segmentations of the lung nodules were performed manually by an expert radiologist in a 2D axial view. Radiomic features were extracted from intra- and perinodular regions. 145 patients were employed as part of the training set (S(tr)) whereas 205 patients were used as part of test set I ([Formula: see text]) and 62 patients were employed as part of independent test set II ([Formula: see text]). To mitigate the variation of CT acquisition parameters, we defined ‘stable’ radiomic features as those for which the feature expression remains relatively unchanged between different sites, as assessed using a Wilcoxon rank-sum test. These stable features were employed to develop more generalizable radiomic classifiers that were more resilient to variations in lung CT scans. Features were ranked based on two criteria, firstly based on discriminability (i.e. maximizing AUC) alone and subsequently based on maximizing both feature stability and discriminability. Different machine learning classifiers (LDA, QDA, Support vector machines and random forest) were trained with features selected using the two different criteria and then compared on the two independent test sets for distinguishing granulomas from adenocarcinomas, in terms of area under the receiver operating characteristic curve. RESULTS: In the test sets, classifiers constructed using the criteria involving maximizing feature stability and discriminability simultaneously achieved higher AUC compared to the discriminating alone criteria ([Formula: see text] (n=205): maximum AUCs of 0.85 vs. 0.80; p-value = 0.047 and [Formula: see text] (n=62): maximum AUCs of 0.87 vs. 0.79; p-value = 0.021). These differences held for features extracted from scans with < 3 mm slice thickness (AUC = 0.88 vs. AUC = 0.80; p-value = 0.039, n=100) and for the ≥ 3 mm cases (AUC = 0.81 vs. AUC = 0.76; p-value = 0.034, n=105). In both experiments, shape and peritumoral texture features had a higher stability compared to intratumoral texture features. CONCLUSIONS: Our study suggests that explicitly accounting for both stability and discriminability results in more generalizable radiomic classifiers to distinguish adenocarcinomas from granulomas on non-contrast CT scans. Our results also showed that peritumoral texture and shape features were less affected by the scanner parameters compared to intratumoral texture features, however, they were also less discriminating compared to intratumoral features.

Sinonasal malignancies make up5% of all head and neck neoplasms, with an incidence of 0.5-1.0 per 100,000. The outcome of these rare malignancies has been poor, whereas significant progress has been made in the management of other cancers. The objective of the current review was to describe the incidence, causes, presentation, diagnosis, treatment, and recent developments of malignancies of the sinonasal tract. The diagnoses covered in this review included sinonasal undifferentiated carcinoma, sinonasal adenocarcinoma, sinonasal squamous cell carcinoma, and esthesioneuroblastoma, which are exclusive to the sinonasal tract. In addition, the authors covered malignances that are likely to be encountered in the sinonasal tract-primary mucosal melanoma, NUT (nuclear protein of the testis) carcinoma, and extranodal natural killer cell/T-cell lymphoma. For the purpose of keeping this review as concise and focused as possible, sarcomas and malignancies that can be classified as salivary gland neoplasms were excluded.

Objectives To evaluate whether combining stability and discriminability criteria in building radiomic classifiers will improve the prognosis of cancer recurrence in early stage non-small cell lung cancer on non-contrast computer tomography (CT). Materials and Methods CT scans of 610 patients with early stage (IA, IB, IIA) NSCLC from four independent cohorts were evaluated. A total of 350 patients from Cleveland Clinic Foundation and University of Pennsylvania were divided into two equal sets for training (D1) and validation set (D2). 80 patients from The Cancer Genome Atlas Lung Adenocarcinoma and Squamous Cell Carcinoma and 195 patients from The Cancer Imaging Archive, were used as independent second (D3) and third (D4) validation sets. A linear discriminant analysis (LDA) classifier was built based on the most stable and discriminate features. In addition, a radiomic risk score (RRS) was generated by using least absolute shrinkage and selection operator, Cox regression model to predict time to progression (TTP) following surgery. Results A feature selection strategy focusing on both feature discriminability and stability resulted in the classifier having a higher discriminability on validation datasets compared to the discriminability alone criteria in discriminating cancer recurrence (D2, AUC of 0.75 vs. 0.65; D3, 0.74 vs. 0.62; D4, 0.76 vs. 0.63). The RRS generated by most stable-discriminating features was significantly associated with TTP compared to discriminating alone criteria (HR = 1.66, C-index of 0.72 vs. HR = 1.04, C-index of 0.62). Conclusion Accounting for both stability and discriminability yielded a more generalizable classifier for predicting cancer recurrence and TTP in early stage NSCLC.

No predictive biomarkers can robustly identify patients with non–small cell lung cancer (NSCLC) who will benefit from immune checkpoint inhibitor (ICI) therapies. Here, in a machine learning setting, we compared changes (“delta”) in the radiomic texture (DelRADx) of CT patterns both within and outside tumor nodules before and after two to three cycles of ICI therapy. We found that DelRADx patterns could predict response to ICI therapy and overall survival (OS) for patients with NSCLC. We retrospectively analyzed data acquired from 139 patients with NSCLC at two institutions, who were divided into a discovery set (D1 = 50) and two independent validation sets (D2 = 62, D3 = 27). Intranodular and perinodular texture descriptors were extracted, and the relative differences were computed. A linear discriminant analysis (LDA) classifier was trained with 8 DelRADx features to predict RECIST-derived response. Association of delta-radiomic risk score (DRS) with OS was determined. The association of DelRADx features with tumor-infiltrating lymphocyte (TIL) density on the diagnostic biopsies (n = 36) was also evaluated. The LDA classifier yielded an AUC of 0.88 ± 0.08 in distinguishing responders from nonresponders in D1, and 0.85 and 0.81 in D2 and D3. DRS was associated with OS [HR: 1.64; 95% confidence interval (CI), 1.22–2.21; P = 0.0011; C-index = 0.72). Peritumoral Gabor features were associated with the density of TILs on diagnostic biopsy samples. Our results show that DelRADx could be used to identify early functional responses in patients with NSCLC.

279 Background: Our objective was to explore if differences in patient satisfaction based on gender exist in a Veterans Health Administration (VHA) outpatient chemotherapy infusion unit. Methods: Veterans who received outpatient infusion treatments from 2018 to 2020 were contacted by phone and agreed to partake in an anonymous 25 question online survey. Response differences were analyzed using Fisher’s exact and Welch's t-tests. Results: 69 veterans were contacted. 70% (21/30) of women and 51% (20/39) of male veterans completed the survey. Most women were < 65 years (62%), and 52% treated for breast cancer. 90% of men were > 65 years old, majority treated for prostate cancer (20%) or a hematological cancer (20%). Using our survey, patient satisfaction was 8.71/10 points (± 0.60) in women vs. 9.55 (± 2.24) in men (p = 0.113). 86% of women endorsed hx of sexual abuse or harassment vs 10% of men (p < 0.001). More women vs men felt uncomfortable around other patients and unable to voice uncomfortable experiences to a provider in the infusion unit (p < 0.05). Not statistically significant but potential clinical importance was more women felt uncomfortable around the offending gender (29% vs 0%), more women felt greater emotional support and importance with access to a tx room with the same gender (29% vs 0%), and more women preferred access to a gender specific restroom (30% vs 20%). Conclusions: Gender appears related to how veterans with cancer perceive their ambulatory cancer care. This may be due to the combination of high sexual abuse and/or harassment hx amongst women who are a minority of the total infusion unit population, the majority of whom receive tx for a primarily gender specific breast malignancy. Analysis was limited by the small sample size of women, many with advanced malignancy. Ongoing initiatives based on these survey results are underway and may be applicable to other outpatient cancer center facilities where patient demographic and infusion unit design may be similar.[Table: see text]

e18817 Background: Recent clinical trials testing use of immune-checkpoint inhibitors in esophageal and gastric carcinomas have shown both positive and negative results. Given these mixed signals, we aimed to assess outcomes and tolerability of key subgroups using the ASCO Net Health Benefit Score (NHBS) and ESMO Magnitude of Clinical Benefit Scale (MCBS). Methods: A detailed search for phase III trials investigating use of FDA-approved anti PD-1 or anti PD-L1 drugs in esophageal and gastric cancer trials was completed using www.clinicaltrials.gov followed by primary literature identification on PubMed. These studies were then independently selected, reviewed, and scored using the ASCO NHBS and ESMO MCBS by two investigators, and any discrepancy was mutually resolved. The ASCO NGBS scores were compared by primary site of cancer (esophageal vs gastric) and PD-L1 expression using the Mann-Whitney test. The ESMO-MCBS grading were compared using Fisher's Exact test. Results: Of the 45 records identified, 15 clinical trials were included. Of them, six were primarily esophageal cancer trials, and nine were primarily gastric cancer trials. Of all 15, 10 stratified their analysis based on PD-L1 expression. The ASCO NHBS score was significantly higher for esophageal cancer than gastric cancer (mean 40, range 20 – 56.6 vs. mean 12, range -1.1 – 18.4, p < .01). No difference, however, was observed in survival and response rate outcome endpoints between the two groups. Similarly, the ESMO MCBS was also higher for esophageal cancer group than gastric cancer (p < .05). Additionally, the median scores were higher in the patients with high PD-L1 expression vs low PD-L1 expression (mean 37, range 11.2 – 66.6 vs. mean 14, range -19.5 – 43.6, p < .05). Conclusions: In this cohort of drug registration trials of immune checkpoint inhibitors for upper GI cancers, we showed the ASCO NHB scores and ESMO scores were consistently higher among esophageal cancer trials than gastric cancer trials and in those with high PD-L1 expression than those with low PD-L1 expression. Oncologists should carefully discuss overall clinical value and expectations of immunotherapy benefit with their patients per cancer histology and PDL1 expression, exercising caution in cases of gastric adenocarcinoma with low PD-L1 expression.[Table: see text]

BackgroundThe second wave of the COVID-19 pandemic has led to considerable morbidity and mortality in India, in part due to lack of healthcare access, low health literacy, and poor disease surveillance. In this retrospective, descriptive ecological study, we utilized Google Trends (GT) to characterize the second COVID-19 wave and its association with official case counts based on search terms related to symptoms, testing, disease complications, medications, preventive behaviors, and healthcare utilization.MethodsGT is a publicly available, online tracking system of Google searches. Searches are presented as relative search volumes (RSV) from 0 (least) to 100 (most number of searches). We performed pre-defined Web searches in India from 2/12/2021 to 5/09/2021. We characterized the peak RSV, RSV doubling rates, and Spearman rank correlation of selected search terms with official case counts. We also used date-adjusted linear regression to estimate the association between highly correlated search terms and official case counts. We then qualitatively classified public search queries into thematic groups to better understand public awareness and needs related to COVID-19.ResultsWe observed that searches for symptoms (most searched terms in order: fever, cough, headache, fatigue, chest pain), disease states (infection, pneumonia), COVID-19-related medications (remdesivir, ivermectin, azithromycin, Fabiflu, dexamethasone), testing modalities (PCR, CT Scan, D-dimer, C-reactive protein, oxygen saturation), healthcare utilization (oxygen cylinders, hospital, physician), and preventive behaviors (lockdown, mask, pulse oximetry, hand sanitizer, quarantine) all demonstrated increases, in line with increases in official case counts. Symptoms, PCR testing, outpatient medications, and preventive behaviors peaked around April 24th, approximately two weeks prior to the peak RSV in official case counts. Contrarily, healthcare utilization factors, including searches for hospital, physicians, beds, disease states, and inpatient medications did not peak until the first week of May. There were highly significant correlations between ‘Coronavirus Disease 2019’ (r=0.959), ‘fever’ (r=0.935), ‘pulse oximetry’ (r=0.952), ‘oxygen saturation’ (r=0.944), ‘C-reactive protein’ (r=0.955), ‘D-Dimer’ (r=0.945), & ‘Fabiflu’ (r=0.943) and official case counts.ConclusionGT search terms related to symptoms, testing, and medications are highly correlated with official case counts in India, suggesting need for further studies examining GT’s potential use as a disease surveillance and public informant tool for public health officials.

A significant challenge in Glioblastoma (GBM) management is identifying pseudo-progression (PsP), a benign radiation-induced effect, from tumor recurrence, on routine imaging following conventional treatment. Previous studies have linked tumor lobar presence and laterality to GBM outcomes, suggesting that disease etiology and progression in GBM may be impacted by tumor location. Hence, in this feasibility study, we seek to investigate the following question: Can tumor location on treatment-naïve MRI provide early cues regarding likelihood of a patient developing pseudo-progression vs. tumor recurrence? In this study, 74 pre-treatment Glioblastoma MRI scans with PsP (33) and tumor recurrence (41) were analyzed. First, enhancing lesion on Gd-T1w MRI and peri-lesional hyperintensities on T2w/FLAIR were segmented by experts and then registered to a brain atlas. Using patients from the two phenotypes, we construct two atlases by quantifying frequency of occurrence of enhancing lesion and peri-lesion hyperintensities, by averaging voxel intensities across the population. Analysis of differential involvement was then performed to compute voxel-wise significant differences (p-value < 0.05) across the atlases. Statistically significant clusters were finally mapped to a structural atlas to provide anatomic localization of their location. Our results demonstrate that patients with tumor recurrence showed prominence of their initial tumor in the parietal lobe, while patients with PsP showed a multi-focal distribution of the initial tumor in the frontal and temporal lobes, insula, and putamen. These preliminary results suggest that lateralization of pre-treatment lesions toward certain anatomical areas of the brain may allow to provide early cues regarding assessing likelihood of occurrence of pseudo-progression from tumor recurrence on MRI scans.

Clinical assessment (4Ts) followed by testing for Heparin/platelet factor 4 (HPF4) antibody in intermediate and high risk patients is the standard algorithm of pretest for Heparin induced thrombocytopenia (HIT), and the diagnosis is confirmed by serotonin releasing assay (SRA) in those who have positive antibodies. We conducted a retrospective analysis in a cohort of patients treated in a community hospital who had HIT antibody test by either ELISA or a rapid Particle Immunofiltration Assay (PIFA), regardless of their 4Ts scores. Among 224 patients, 17 had HIT. The PPV for those with a 4 T score ≥4 was 10.4%, which misdianosed 3 patients with HIT who tested positive for antibodies. Combining 4 T score ≥4 AND positive HIT antibody showed a PPV of 20.3% and a sensitivity of 70.6%, misdiagnosing 5 HIT patients. Using 4Ts ≥4 OR positive HIT antibody showed 100% sensitivity and 100% negative predictive value (NPV). The ELISA test had 100% sensitivity and 100% NPV, while the PIFA test missed 2 HIT patients, with sensitivity of 60% and NPV of 96.7%. Our results suggest that SRA testing should be conducted if a patient presents with a 4 T score ≥4 OR a positive HIT antibody, and antibody tests should be conducted for every patient suspected of HIT.

Background: High mortality rates are predominant even in COVID-19 patients requiring minimal supportive therapy, with a short-coming of data on COVID-19 patients requiring mechanical ventilation.Objectives/Design: We performed a single-center, retrospective, cohort study at a tertiary care, community-based teaching hospital with patient who required invasive mechanical ventilatory support and were COVID-19 positive. All patients were treated according to the ARDSnet protocol. The primary outcome was overall mortality, and secondary outcome was successful extubation.Results: A total of 72 COVID-19 positive intubated patients were included. Twenty-six (66.6%) patients died within the first 15 days of hospital admission; thirty-eight (52.7%) died within 28 days, and thirty-nine (54.2%) died within 29 days. A total of 22 patients (30.5%) were successfully extubated. 15 patients (20.8%) who required reintubation or could not be extubated further underwent tracheostomy.Conclusions: Mortality of critically ill COVID-19 patients requiring mechanical ventilatory support is high, our observed mortality rate (54.2%) was significantly lower than currently published reports. We believe our rate to be a consequence of early intubation in conjunction with adherence to ARDSnet protocol. We also observed patients with hyperlipidemia, higher CRP, renal failure, or those requiring vasopressor use had worse outcomes.

Lung cancer is responsible for a large proportion of cancer-related deaths across the globe, with delayed detection being perhaps the most significant factor for its high mortality rate. Though the National Lung Screening Trial argues for screening of certain at-risk populations, the practical implementation of these screening efforts has not yet been successful and remains in high demand. Radiomics refers to the computerized extraction of data from radiologic images, and provides unique potential for making lung cancer screening more rapid and accurate using machine learning algorithms. The quantitative features analyzed express subvisual characteristics of images which correlate with pathogenesis of diseases. These features are broadly classified into four categories: intensity, structure, texture/gradient, and wavelet, based on the types of image attributes they capture. Many studies have been done to show correlation between these features and the malignant potential of a nodule on a chest CT. In cancer patients, these nodules also have features that can be correlated with prognosis and mutation status. The major limitations of radiomics are the lack of standardization of acquisition parameters, inconsistent radiomic methods, and lack of reproducibility. Researchers are working on overcoming these limitations, which would make radiomics more acceptable in the medical community.

Patient: Male, 47 Final Diagnosis: Pulmonic valve endocarditis Symptoms: Fever • myalgia Medication: — Clinical Procedure: — Specialty: Cardiology Objective: Rare disease Background: Infective endocarditis (IE) has a high mortality rate, even when treated with appropriate antibiotic therapy and surgical intervention. Right-sided endocarditis is in itself rare, with some studies reporting an incidence of 5–10%. The majority of these cases involve the tricuspid valve, and isolated pulmonary valve endocarditis (PVE) is an extremely rare entity affecting less than 2% of patients with infective endocarditis. Identification and early management are crucial to prevent long-term complications and reduce mortality. Case Report: We present a patient with a history of essential hypertension and no underlying valvular disease, who underwent dental cleaning and subsequently developed low-grade fever, myalgia, and malaise. This occurred during the flu season, and was initially diagnosed and treated as flu, without any improvement. The patient was later found to be bacteremic with S. mitis, with no identifiable source, and a normal transthoracic echocardiogram (TTE). He was later hospitalized, had a transesophageal echocardiogram, and was found to have a large pulmonic valve vegetation. Conclusions: This case presents an interesting and rare finding of endocarditis, isolated to the pulmonic valve, in an otherwise healthy individual with no predisposing risk factors. The lack of peripheral stigmata, as well as an unremarkable initial outpatient TTE, made the diagnosis more difficult. It should also be noted that current guidelines do not specifically address right-sided endocarditis, and do not specify the role of surgical intervention.

Asian Indians are at increased risk of developing cardiometabolic diseases. We sought to determine differences between Asian Indians and other races/ethnicities in hypertension and diabetes prevalence and associated annual blood pressure (BP) and fasting blood glucose (FBG) testing. A total of 257,652 adults ≥18 years from the 2011–2018 U.S. National Health Interview Surveys (NHIS) were included. BP and FBG testing in the past 12 months was defined dichotomously (yes/not yes). Racial/ethnic groups included non-Hispanic White (NHW), non-Hispanic Black (NHB), Asian Indian, Other Asians, and Hispanic/Multiracial. We used logistic regression, adjusting for covariates and the survey design. Analyses were completed from 08/2020–06/2021. Asian Indians (N = 3049) had 21% and 99% higher odds of hypertension and diabetes, respectively, than NHWs (aOR [95% CI]; hypertension: 1.21[1.04,1.40], diabetes: 1.99[1.64,2.41]). Accordingly, Asian Indians without diabetes had significantly higher odds of FBG screening than NHWs (Asian Indian: 1.41[1.25,1.59], NHB: 0.99 [0.95,1.04], Other Asian: 1.07[0.98, 1.18], Hispanic: 1.13[1.07,1.20]). Asian Indians without hypertension had a 14% insignificant increase in BP testing compared to NHWs (1.14[0.97,1.33]). Predictors of testing in Asian Indians included older age, doctor's visit, graduate-level education, insurance coverage, and history of hypertension or diabetes. NHBs with diabetes and Hispanics with hypertension had lower odds of FBG testing (0.75[0.66,0.84]) and BP testing (0.85[0.79,0.92]), respectively, than NHWs. Asian Indians have higher odds of diabetes and hypertension than NHWs and higher, but relatively lower, odds of FBG and BP testing. Increasing routine BP and FBG testing in Asian Indians in younger adults may allow for earlier detection of high-risk individuals.

Introduction: Malignancy is a well-known risk factor for thrombosis. While many clinical risk factors for cancer-associated thrombosis have been described, it remains unknown how certain tumor specific observations (such as programmed death ligand 1 expression (PD-L1) and tumor mutational burden (TMB)) correspond to thrombotic risk. To determine the relationship between PD-L1 and TMB quantification and thrombosis in patients with solid tumors, we evaluated a large cohort of clinical samples from an NCI designated cancer center, correlating tissue sample pathology with the development of venous or arterial thromboembolism. Methods: We performed a retrospective cohort study of patients between the ages of 18-89 who underwent histopathologic examination and next generation sequencing for a diagnosis of a solid organ malignancy at the Knight Cancer Institute between June 2019 and Feb 2021. Medical records were reviewed to document clinical and demographic information as well as for the development of thrombosis after cancer diagnosis. Multivariable logistic regression was performed to assess if PD-L1 expression and TMB are independent predictors of thrombosis. Subgroup analysis was then performed to evaluate whether this relationship differed by the organ of the primary malignancy. All analyses were conducted in R (R Core Team 2019). Results: We identified 1,221 patients with solid organ malignancies (mean age 62, 53.6% male). The most common malignancies in the cohort were lung cancer (13.8%), pancreatic cancer (12.3%) and colon cancer (12.3%). Thrombotic events occurred in 206 patients (16.8%) after diagnosis of their malignancy (100 deep vein thrombosis, 42 pulmonary embolism, 46 visceral vein thromboses, 6 superficial vein thromboses, and 11 arterial events). The mean time from initial biopsy to thrombosis was 224 days. TMB (mean 8.5 mutations/Mb) was evaluated in all patients in the cohort, while PD-L1 expression testing (mean 23.0%) was available for 255 patients. On multivariable logistic regression adjusting for age and patient sex, neither TMB (ORadj: 0.97, CI: 0.92-1.03) nor PD-L1 expression (ORadj 1.00, CI: 1.00-1.02) were significant predictors of thrombotic events. Subgroup analysis by primary malignancy type did not demonstrate any specific primary sites for which TMB or PD-L1 were predictive of thrombosis. Discussion: Our analysis found no predictive relationship between TMB and PD-L1 expression with thrombotic events in patients with solid organ malignancy. Further analysis is needed to determine if specific treatment protocols, such as the use of immunotherapy in patients with varying levels of PD-L1 and TMB, alter thrombosis risk. Disclosures Shatzel: Aronora Inc,: Consultancy.

Identification of patients with early stage non-small cell lung cancer (NSCLC) with high risk of recurrence could help identify patients who would receive additional benefit from adjuvant therapy. In this work, we present a computational histomorphometric image classifier using nuclear orientation, texture, shape, and tumor architecture to predict disease recurrence in early stage NSCLC from digitized H&E tissue microarray (TMA) slides. Using a retrospective cohort of early stage NSCLC patients (Cohort #1, n = 70), we constructed a supervised classification model involving the most predictive features associated with disease recurrence. This model was then validated on two independent sets of early stage NSCLC patients, Cohort #2 (n = 119) and Cohort #3 (n = 116). The model yielded an accuracy of 81% for prediction of recurrence in the training Cohort #1, 82% and 75% in the validation Cohorts #2 and #3 respectively. A multivariable Cox proportional hazard model of Cohort #2, incorporating gender and traditional prognostic variables such as nodal status and stage indicated that the computer extracted histomorphometric score was an independent prognostic factor (hazard ratio = 20.81, 95% CI: 6.42–67.52, P

To develop an approach for radiology-pathology fusion of ex vivo histology of surgically excised pulmonary nodules with pre-operative CT, to radiologically map spatial extent of the invasive adenocarcinomatous component of the nodule. Six subjects (age: 75 ± 11 years) with pre-operative CT and surgically excised ground-glass nodules (size: 22.5 ± 5.1 mm) with a significant invasive adenocarcinomatous component (>5 mm) were included. The pathologist outlined disease extent on digitized histology specimens; two radiologists and a pulmonary critical care physician delineated the entire nodule on CT (in-plane resolution

Purpose To evaluate ability of radiomic (computer-extracted imaging) features to distinguish non-small cell lung cancer adenocarcinomas from granulomas at noncontrast CT. Materials and Methods For this retrospective study, screening or standard diagnostic noncontrast CT images were collected for 290 patients (mean age, 68 years; range, 18-92 years; 125 men [mean age, 67 years; range, 18-90 years] and 165 women [mean age, 68 years; range, 33-92 years]) from two institutions between 2007 and 2013. Histopathologic analysis was available for one nodule per patient. Corresponding nodule of interest was identified on axial CT images by a radiologist with manual annotation. Nodule shape, wavelet (Gabor), and texture-based (Haralick and Laws energy) features were extracted from intra- and perinodular regions. Features were pruned to train machine learning classifiers with 145 patients. In a test set of 145 patients, classifier results were compared against a convolutional neural network (CNN) and diagnostic readings of two radiologists. Results Support vector machine classifier with intranodular radiomic features achieved an area under the receiver operating characteristic curve (AUC) of 0.75 on the test set. Combining radiomics of intranodular with perinodular regions improved the AUC to 0.80. On the same test set, CNN resulted in an AUC of 0.76. Radiologist readers achieved AUCs of 0.61 and 0.60, respectively. Conclusion Radiomic features from intranodular and perinodular regions of nodules can distinguish non-small cell lung cancer adenocarcinomas from benign granulomas at noncontrast CT. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by Nishino in this issue.

Objective The use of a neoadjuvant chemoradiation followed by surgery in patients with stage IIIA NSCLC is controversial and the benefit of surgery is limited. There are currently no clinically validated biomarkers to select patients for such an approach. In this study we evaluate computed tomography (CT) derived intratumoral and peritumoral texture and nodule shape features in their ability to predict major pathological response (MPR). MPR being defined as ≤10% of residual viable tumor, assessed at the time of surgery. Material and methods Ninety patients with stage III NSCLC treated with chemoradiation prior to surgical resection were selected. The patients were divided randomly into two equal sets, one for training and one for independent testing. The radiomic texture and shape features were extracted from within the nodule (intra) and from the parenchymal regions immediately surrounding the nodule (peritumoral). A univariate regression analysis was performed on the image and clinicopathologic variables and then included into a multivariable logistic regression (MLR) for binary outcome prediction of MPR. The radiomic signature risk-score was generated by using a multivariate Cox regression model and association of the signature with OS and DFS was also evaluated. Results Thirteen stable and predictive intratumoral and peritumoral radiomic texture features were found to be predictive of MPR. The MLR classifier yielded an AUC of 0.90 ± 0.025 within the training set and a corresponding AUC = 0.86 in prediction of MPR within the test set. The radiomic signature was also significantly associated with OS (HR = 11.18, 95% CI = 3.17, 44.1; p-value = 0.008) and DFS (HR = 2.78, 95% CI = 1.11, 4.12; p-value = 0.0042) in the testing set. Conclusion Texture features extracted within and around the lung tumor on CT images appears to be associated with the likelihood of MPR, OS and DFS to chemoradiation.

Patients with transfusion-dependent thalassemia are expected to have an unfavorable quality of life due to multiple factors. We studied the quality of life in 72 patients (age 5-39 y) with transfusion-dependent thalassemia in the era of improved care, and assessed different parameters affecting it.

The symptoms of primary renal lymphoma (PRL) may mimic a renal cell carcinoma. Since the diagnosis is mostly after a radical nephrectomy, we recommend a percutaneous biopsy or cytology from the renal mass in patients who have features suggestive of a lymphoma. A magnetic resonance imaging may give an image more specific for a lymphoma. There are no clinical trials for the treatment of PRL, but all previously published case reports used R-CHOP and a few patients did better than the median survival of 6 months.

e21743 Background: Lung cancer is the most common cause of cancer-related mortality and most deaths are associated with metastatic disease, with brain being a common site. Historically, whole brain radiation therapy was the treatment of choice and resulted in median survivals in the range of 6 months. There is no consensus in management of patients who have brain metastasis with systemic disease.We aim to evaluate patients with brain metastasis from lung cancer for cause of death, to investigate whether patients died from central nervous system (CNS) progression or systemic disease or other/undetermined causes. Our hypothesis is that most deaths in contemporary patients with brain metastasis in lung cancer are due to systemic disease, and less commonly due to CNS progression. Methods: In this retrospective observational study, we did a chart review of all adult patients with non-small cell lung cancer and brain metastasis or leptomeningeal disease, who received treatment at Maimonides Cancer Center between 2010 and 2017. Patients with unavailable or incomplete medical records were excluded. Baseline characteristics, pathological factors of the tumor and cause of death was collected from the chart. The cause of death was categorized into systemic and brain causes, and difference in characteristics of patients and tumor were studied. Results: A total of 132 patients were included and their charts were reviewed. Out of 132, 96 could have a clear cause of death categorized into systemic or brain causes, the rest were either mixed or uncategorized. We found that 33% patients died of brain metastasis, and related causes, whereas 67% died of systemic disease progression. There were no different in the two groups in terms of gender, smoking status, histology, size of lung lesion, or number and size of brain lesion. The patients who died of brain metastasis had a significantly higher age, and worse Eastern Cooperative Oncology Group status. Interestingly, the patients who died of systemic causes more commonly had adrenal metastasis (12 vs 0) which was statistically significant, and liver (14 vs 3) metastasis which was not statistically significant. Conclusions: Two-thirds of patients with brain metastases died of systemic disease rather than CNS progression. This may reflect improvements in systemic and local therapies to forestall cancer progression in the CNS. This finding suggests that delaying systemic therapy for CNS treatment may negatively impact overall cancer control. More research needs to be done to answer this question with certainty, including prospective clinical trials.

BACKGROUND AND PURPOSE: Differentiating pseudoprogression, a radiation-induced treatment effect, from tumor progression on imaging is a substantial challenge in glioblastoma management. Unfortunately, guidelines set by the Response Assessment in Neuro-Oncology criteria are based solely on bidirectional diametric measurements of enhancement observed on T1WI and T2WI/FLAIR scans. We hypothesized that quantitative 3D shape features of the enhancing lesion on T1WI, and T2WI/FLAIR hyperintensities (together called the lesion habitat) can more comprehensively capture pathophysiologic differences across pseudoprogression and tumor recurrence, not appreciable on diametric measurements alone. MATERIALS AND METHODS: A total of 105 glioblastoma studies from 2 institutions were analyzed, consisting of a training ( n = 59) and an independent test ( n = 46) cohort. For every study, expert delineation of the lesion habitat (T1WI enhancing lesion and T2WI/FLAIR hyperintense perilesional region) was obtained, followed by extraction of 30 shape features capturing 14 “global” contour characteristics and 16 “local” curvature measures for every habitat region. Feature selection was used to identify most discriminative features on the training cohort, which were evaluated on the test cohort using a support vector machine classifier. RESULTS: The top 2 most discriminative features were identified as local features capturing total curvature of the enhancing lesion and curvedness of the T2WI/FLAIR hyperintense perilesional region. Using top features from the training cohort (training accuracy = 91.5%), we obtained an accuracy of 90.2% on the test set in distinguishing pseudoprogression from tumor progression. CONCLUSIONS: Our preliminary results suggest that 3D shape attributes from the lesion habitat can differentially express across pseudoprogression and tumor progression and could be used to distinguish these radiographically similar pathologies.

PURPOSE: A significant challenge in post-treatment assessment of Glioblastoma is differentiating tumor recurrence (TR) from pseudo-progression (PsP), a radiation-induced treatment effect on routine MRI scans. Previous studies on pre-treatment MRI suggested that aggressive GBM lesions are spatially localized in the right hemisphere; and are associated with poor survival. We thus hypothesize that aggressive TR lesions appearing on post-treatment scans, will likely be more localized in the right hemisphere, as compared to benign PsP. METHODS: 106 post-treatment MRI studies (35 PsP, 71 TR) were collected from 2 institutions. Confirmation for PsP and TR was obtained either from pathologic resection or MRI follow-up using RANO criteria. Scans were registered to T1-weighted brain atlas (MNI152), followed by expert delineation of enhancing lesion on Gd-T1w MRI and peri-lesional hyperintensities on T2/FLAIR. Population atlases quantifying the frequency of occurrence of enhancing lesion and peri-lesional hyperintensities were constructed by averaging voxel intensities across all patients. Analysis of differential involvement (ADIFFI) based on a two-tailed Fisher’s exact test was performed to compute significant differences (p-value

Tracheomediastinal fistula is a rare condition caused by multiple etiologies. We present a case of a patient of lung carcinoma receiving chemotherapy. A 63-year-old woman presented to the emergency room with a two-month history of worsening cough and shortness of breath. She was being treated with pemetrexed and bevacizumab for Stage IV non-small cell lung carcinoma. Chest X-ray showed a mass in the lung with mediastinal adenopathy. Computed tomography (CT) scan showed a perforation, confirmed with bronchoscopy. She had a secondary infection and she was started on intravenous antibiotics. The patient decided to continue care in a hospice. We present a rare complication of bevacizumab which has been only reported once in literature. Bevacizumab is known to cause tracheal fistulas when coupled with like invasive procedures. In our case, the patient developed a fistula without any invasive interventions. We advise that physicians using bevacizumab should be aware of the possibility of having such fistulas.

Crohn’s Disease is a relapsing and remitting disease involving chronic intestinal inflammation that is often characterized by hypertrophy of visceral adipose tissue (VAT). While an increased ratio of VAT to subcutaneous fat (SQF) has previously been identified as a predictor of worse outcomes in Crohn’s Disease, bowel-proximal fat regions have also been hypothesized to play a role in inflammatory response. However, there has been no detailed study of VAT and SQF regions on MRI to determine their potential utility in assessing Crohn’s Disease severity or guiding therapy. In this paper we present a fully-automated algorithm to segment and quantitatively characterize VAT and SQF via routinely acquired diagnostic bowel MRIs. Our automated segmentation scheme for VAT and SQF regions involved a combination of morphological processing and connected component analysis, and demonstrated DICE overlap scores of 0.86±0.05 and 0.91±0.04 respectively, when compared against expert annotations. Additionally, VAT regions proximal to the bowel wall (on diagnostic bowel MRIs) demonstrated a statistically significantly, higher expression of four unique radiomic features in pediatric patients with moderately active Crohn’s Disease. These features were also able to accurately cluster patients who required aggressive biologic therapy within a year of diagnosis from those who did not, with 87.5% accuracy. Our findings indicate that quantitative radiomic characterization of visceral fat regions on bowel MRIs may be highly relevant for guiding therapeutic interventions in Crohn’s Disease.

T/NK cell lymphoma is a rare subtype of lymphoma that is known to be of aggressive nature. We present two cases of this disease that originally presented with symptoms consistent with chronic rhinosinusitis. We outline how we managed the diseases and review literature on it.

Early identification of PCa patients at risk for biochemical recurrence (BCR) post-therapy will potentially complement definitive therapy with either neo- or adjuvant therapy to improve prognosis. BCR post definitive therapy is often associated with disease progression that might cause a bulge in the prostate gland. In this work we explored if an atlas-based comparison approach reveals shape differences in the prostate capsule as observed on pre-treatment T2-weighted MRI between prostate cancer patients who do (BCR+) and do not (BCR−) have BCR following definitive therapy. A single center IRB approved study included 874 patients. Complete image datasets, clinically localized PCa, availability of Gleason score, data available for post-treatment PSA and follow-up for at least 3 years in patients without BCR were the inclusion criteria to select 77 patients out of the 874 patients. Further controlling for Gleason score, stage, age and to maintain equal number of cases for the BCR+ and BCR− categories, the total number of cases was reduced to 50. Manually segmented prostate capsules were aligned to a BCR− template for statistical comparison between the BCR+ and BCR− groups. Statistically significant shape difference between the two groups was observed towards the lateral and the posterior sides of prostate.