Browsing by Subject "Biopsy"
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Item Acquired coronary-cameral fistula(Wiley, 2009-08) Jacob, Sony; Feigenbaum, Harvey; Medicine, School of MedicineItem Circulating Extracellular Vesicles Carrying Sphingolipid Cargo for the Diagnosis and Dynamic Risk Profiling of Alcoholic Hepatitis(Wolters Kluwer, 2021) Sehrawat, Tejasav S.; Arab, Juan P.; Liu, Mengfei; Amrollahi, Pouya; Wan, Meihua; Fan, Jia; Nakao, Yasuhiko; Pose, Elisa; Navarro-Corcuera, Amaia; Dasgupta, Debanjali; Liao, Chieh-Yu; He, Li; Mauer, Amy S.; Avitabile, Emma; Ventura-Cots, Meritxell; Bataller, Ramon A.; Sanyal, Arun J.; Chalasani, Naga P.; Heimbach, Julie K.; Watt, Kymberly D.; Gores, Gregory J.; Gines, Pere; Kamath, Patrick S.; Simonetto, Douglas A.; Hu, Tony Y.; Shah, Vijay H.; Malhi, Harmeet; Medicine, School of MedicineBackground and aims: Alcoholic hepatitis (AH) is diagnosed by clinical criteria, although several objective scores facilitate risk stratification. Extracellular vesicles (EVs) have emerged as biomarkers for many diseases and are also implicated in the pathogenesis of AH. Therefore, we investigated whether plasma EV concentration and sphingolipid cargo could serve as diagnostic biomarkers for AH and inform prognosis to permit dynamic risk profiling of AH subjects. Approach and results: EVs were isolated and quantified from plasma samples from healthy controls, heavy drinkers, and subjects with end-stage liver disease (ESLD) attributed to cholestatic liver diseases and nonalcoholic steatohepatitis, decompensated alcohol-associated cirrhosis (AC), and AH. Sphingolipids were quantified by tandem mass spectroscopy. The median plasma EV concentration was significantly higher in AH subjects (5.38 × 1011 /mL) compared to healthy controls (4.38 × 1010 /mL; P < 0.0001), heavy drinkers (1.28 × 1011 /mL; P < 0.0001), ESLD (5.35 × 1010 /mL; P < 0.0001), and decompensated AC (9.2 × 1010 /mL; P < 0.0001) disease controls. Among AH subjects, EV concentration correlated with Model for End-Stage Liver Disease score. When EV counts were dichotomized at the median, survival probability for AH subjects at 90 days was 63.0% in the high-EV group and 90.0% in the low-EV group (log-rank P value = 0.015). Interestingly, EV sphingolipid cargo was significantly enriched in AH when compared to healthy controls, heavy drinkers, ESLD, and decompensated AC (P = 0.0001). Multiple sphingolipids demonstrated good diagnostic and prognostic performance as biomarkers for AH. Conclusions: Circulating EV concentration and sphingolipid cargo signature can be used in the diagnosis and differentiation of AH from heavy drinkers, decompensated AC, and other etiologies of ESLD and predict 90-day survival permitting dynamic risk profiling.Item Computational modeling for identification of low-frequency single nucleotide variants(2015-11-16) Hao, Yangyang; Liu, Yunlong; Edenberg, Howard J.; Li, Lang; Nakshatr, HarikrishnaReliable detection of low-frequency single nucleotide variants (SNVs) carries great significance in many applications. In cancer genetics, the frequencies of somatic variants from tumor biopsies tend to be low due to contamination with normal tissue and tumor heterogeneity. Circulating tumor DNA monitoring also faces the challenge of detecting low-frequency variants due to the small percentage of tumor DNA in blood. Moreover, in population genetics, although pooled sequencing is cost-effective compared with individual sequencing, pooling dilutes the signals of variants from any individual. Detection of low frequency variants is difficult and can be cofounded by multiple sources of errors, especially next-generation sequencing artifacts. Existing methods are limited in sensitivity and mainly focus on frequencies around 5%; most fail to consider differential, context-specific sequencing artifacts. To face this challenge, we developed a computational and experimental framework, RareVar, to reliably identify low-frequency SNVs from high-throughput sequencing data. For optimized performance, RareVar utilized a supervised learning framework to model artifacts originated from different components of a specific sequencing pipeline. This is enabled by a customized, comprehensive benchmark data enriched with known low-frequency SNVs from the sequencing pipeline of interest. Genomic-context-specific sequencing error model was trained on the benchmark data to characterize the systematic sequencing artifacts, to derive the position-specific detection limit for sensitive low-frequency SNV detection. Further, a machine-learning algorithm utilized sequencing quality features to refine SNV candidates for higher specificity. RareVar outperformed existing approaches, especially at 0.5% to 5% frequency. We further explored the influence of statistical modeling on position specific error modeling and showed zero-inflated negative binomial as the best-performed statistical distribution. When replicating analyses on an Illumina MiSeq benchmark dataset, our method seamlessly adapted to technologies with different biochemistries. RareVar enables sensitive detection of low-frequency SNVs across different sequencing platforms and will facilitate research and clinical applications such as pooled sequencing, cancer early detection, prognostic assessment, metastatic monitoring, and relapses or acquired resistance identification.Item Concordance of Solid Organ Biopsy Diagnoses With Hospital Autopsy and the Contribution of Biopsies to Death(Springer Nature, 2023-01-17) Priemer, David S.; Curran, Joseph M.; Phillips, Carrie L.; Cummings, Oscar W.; Saxena, Romil; Pathology and Laboratory Medicine, School of MedicineBiopsies of the liver, lung, and kidney are performed for many indications, including organ dysfunction, mass lesions, and allograft monitoring. The diagnosis depends on the sample, which may or may not be representative of the lesion or pathology in question. Further, biopsies are not without risk of complications. Autopsies are a resource for assessing the accuracy of biopsy diagnoses and evaluating possible complications. Herein, we aimed to compare liver, lung, and kidney biopsy diagnoses with those from autopsies conducted soon after the procedure and to assess the contribution of biopsy to mortality. A 28-year search of our database identified 147 patients who were autopsied after dying within 30 days of a liver, lung, or kidney biopsy. The concordance of the biopsy diagnosis with the autopsy findings was determined. Finally, medical records were reviewed to determine the likelihood that a biopsy contributed to the patient's death. The contribution of the biopsy to death was categorized as "unlikely," "possible," or "probable." Overall concordance between biopsy and autopsy diagnoses was 87% (128/147), including 95% (87/92), 71% (32/45), and 90% (9/10) for liver, lung, and kidney biopsies, respectively. Concordance was lower for biopsies of suspected neoplasms versus non-neoplastic diseases. Lung biopsy concordance was higher for wedge biopsy versus needle or forceps biopsy. A biopsy was determined to at least "possibly" contribute to death in 23 cases (16%). In conclusion, an autopsy is an important tool to validate liver, lung, or kidney biopsy diagnoses. Confirmation of biopsy diagnoses via post-mortem examination may be particularly valuable when patients die soon after the biopsy procedure. Furthermore, an autopsy is especially useful when patients die soon after a biopsy in order to determine what role, if any, the procedure played in their deaths. Though biopsy complications are uncommon, a biopsy may still contribute to or precipitate death in a small number of patients.Item Development and external validation of a diagnostic model for biopsy-proven acute interstitial nephritis using electronic health record data(Oxford University Press, 2022) Moledina, Dennis G.; Eadon, Michael T.; Calderon, Frida; Yamamoto, Yu; Shaw, Melissa; Perazella, Mark A.; Simonov, Michael; Luciano, Randy; Schwantes-An, Tae-Hwi; Moeckel, Gilbert; Kashgarian, Michael; Kuperman, Michael; Obeid, Wassim; Cantley, Lloyd G.; Parikh, Chirag R.; Wilson, F. Perry; Medicine, School of MedicineBackground: Patients with acute interstitial nephritis (AIN) can present without typical clinical features, leading to a delay in diagnosis and treatment. We therefore developed and validated a diagnostic model to identify patients at risk of AIN using variables from the electronic health record. Methods: In patients who underwent a kidney biopsy at Yale University between 2013 and 2018, we tested the association of >150 variables with AIN, including demographics, comorbidities, vital signs and laboratory tests (training set 70%). We used least absolute shrinkage and selection operator methodology to select prebiopsy features associated with AIN. We performed area under the receiver operating characteristics curve (AUC) analysis with internal (held-out test set 30%) and external validation (Biopsy Biobank Cohort of Indiana). We tested the change in model performance after the addition of urine biomarkers in the Yale AIN study. Results: We included 393 patients (AIN 22%) in the training set, 158 patients (AIN 27%) in the test set, 1118 patients (AIN 11%) in the validation set and 265 patients (AIN 11%) in the Yale AIN study. Variables in the selected model included serum creatinine {adjusted odds ratio [aOR] 2.31 [95% confidence interval (CI) 1.42-3.76]}, blood urea nitrogen:creatinine ratio [aOR 0.40 (95% CI 0.20-0.78)] and urine dipstick specific gravity [aOR 0.95 (95% CI 0.91-0.99)] and protein [aOR 0.39 (95% CI 0.23-0.68)]. This model showed an AUC of 0.73 (95% CI 0.64-0.81) in the test set, which was similar to the AUC in the external validation cohort [0.74 (95% CI 0.69-0.79)]. The AUC improved to 0.84 (95% CI 0.76-0.91) upon the addition of urine interleukin-9 and tumor necrosis factor-α. Conclusions: We developed and validated a statistical model that showed a modest AUC for AIN diagnosis, which improved upon the addition of urine biomarkers. Future studies could evaluate this model and biomarkers to identify unrecognized cases of AIN.Item Development and Validation of Web-Based Tool to Predict Lamina Propria Fibrosis in Eosinophilic Esophagitis(Wolters Kluwer, 2022) Hiremath, Girish; Sun, Lili; Correa, Hernan; Acra, Sari; Collins, Margaret H.; Bonis, Peter; Arva, Nicoleta C.; Capocelli, Kelley E.; Falk, Gary W.; King, Eileen; Gonsalves, Nirmala; Gupta, Sandeep K.; Hirano, Ikuo; Mukkada, Vincent A.; Martin, Lisa J.; Putnam, Philip E.; Spergel, Jonathan M.; Wechsler, Joshua B.; Yang, Guang-Yu; Aceves, Seema S.; Furuta, Glenn T.; Rothenberg, Marc E.; Koyama, Tatsuki; Dellon, Evan S.; Medicine, School of MedicineIntroduction: Approximately half of esophageal biopsies from patients with eosinophilic esophagitis (EoE) contain inadequate lamina propria, making it impossible to determine the lamina propria fibrosis (LPF). This study aimed to develop and validate a web-based tool to predict LPF in esophageal biopsies with inadequate lamina propria. Methods: Prospectively collected demographic and clinical data and scores for 7 relevant EoE histology scoring system epithelial features from patients with EoE participating in the Consortium of Eosinophilic Gastrointestinal Disease Researchers observational study were used to build the models. Using the least absolute shrinkage and selection operator method, variables strongly associated with LPF were identified. Logistic regression was used to develop models to predict grade and stage of LPF. The grade model was validated using an independent data set. Results: Of 284 patients in the discovery data set, median age (quartiles) was 16 (8-31) years, 68.7% were male patients, and 93.4% were White. Age of the patient, basal zone hyperplasia, dyskeratotic epithelial cells, and surface epithelial alteration were associated with presence of LPF. The area under the receiver operating characteristic curve for the grade model was 0.84 (95% confidence interval: 0.80-0.89) and for stage model was 0.79 (95% confidence interval: 0.74-0.84). Our grade model had 82% accuracy in predicting the presence of LPF in an external validation data set. Discussion: We developed parsimonious models (grade and stage) to predict presence of LPF in esophageal biopsies with inadequate lamina propria and validated our grade model. Our predictive models can be easily used in the clinical setting to include LPF in clinical decisions and determine its effect on treatment outcomes.Item Impact of Skin Biopsy and Clinical-Pathologic Correlation in Dermatology Inpatient Consults(Springer Nature, 2022-08-29) Wells, Amy; Harmel, Allison; Smith, Kristin N.; Beers, Paula; Qiu, Yingjie; Datta, Susmita; Schoch, Jennifer J.; De Benedetto, Anna; Longo, Isabel; Motaparthi, Kiran; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public HealthBackground: While studies of hospital dermatology have demonstrated diagnostic discordance between primary teams and dermatology consultants, little is known about the impact of biopsy and clinical-pathologic correlation (CPC) in consultation. This study compares biopsy performance based on diagnostic discordance and evaluates the impact of CPC on the diagnosis. Methods: This was a retrospective review of 376 dermatologic consultations at a single academic medical center between July 1, 2017, and June 27, 2018. Results: Biopsy was significantly less likely to be performed when the diagnosis by the referring primary team was unspecified (p < 0.001). In 24 percent of cases, the diagnosis based on histopathology alone differed from the diagnosis reached by formal CPC consensus review with either potential or significant impact on management. Conclusion: Dermatologists who perform inpatient consultations and rely on hospital-based pathology services may consider a consensus review for CPC. Requests to perform a biopsy may be interpreted as a request for diagnostic assistance rather than pressure to perform a procedure.Item mTOR Pathway Activation Assessed by Immunohistochemistry in Cervical Biopsies of HPV-associated Endocervical Adenocarcinomas (HPVA): Correlation With Silva Invasion Patterns(Wolters Kluwer, 2021) Segura, Sheila; Stolnicu, Simona; Boros, Monica; Park, Kay; Ramirez, Pedro; Salvo, Gloria; Frosina, Denise; Jungbluth, Achim; Soslow, Robert A.; Pathology and Laboratory Medicine, School of MedicineThe Silva pattern of invasion, recently introduced to stratify patients at risk for lymph node metastases in human papillomavirus-associated endocervical adenocarcinomas (HPVAs), can only be assessed in cone and loop electrosurgical excision procedure excisions with negative margins or in a hysterectomy specimen. Previous studies found associations between destructive stromal invasion patterns (Silva patterns B and C) and mutations in genes involved in the MEK/PI3K pathways that activate the mammalian target of rapamycin (mTOR) pathway. The primary aim of this study was to use cervical biopsies to determine whether markers of mTOR pathway activation associate with aggressive invasion patterns in matched excision specimens. The status of the markers in small biopsy specimens should allow us to predict the final and biologically relevant pattern of invasion in a resection specimen. Being able to predict the final pattern of invasion is important, since prediction as Silva A, for example, might encourage conservative clinical management. If the pattern in the resection specimen is B with lymphovascular invasion or C, further surgery can be performed 34 HPVA biopsies were evaluated for expression of pS6, pERK, and HIF1α. Immunohistochemical stains were scored semiquantitatively, ranging from 0 to 4+ with scores 2 to 4+ considered positive, and Silva pattern was determined in follow-up excisional specimens. Silva patterns recognized in excisional specimens were distributed as follows: pattern A (n=8), pattern B (n=4), and pattern C (n=22). Statistically significant associations were found comparing pS6 and pERK immunohistochemistry with Silva pattern (P=0.034 and 0.05, respectively). Of the 3 markers tested, pERK was the most powerful for distinguishing between pattern A and patterns B and C (P=0.026; odds ratio: 6.75, 95% confidence interval: 1.111-41.001). Although the negative predictive values were disappointing, the positive predictive values were encouraging: 90% for pERK, 88% for pS6 and 100% for HIF1α. mTOR pathway activation assessed by immunohistochemistry in cervical biopsies of HPVA correlate with Silva invasion patterns.Item Role of endoscopic ultrasound fine-needle aspiration evaluating adrenal gland enlargement or mass(Baishideng Publishing Group Inc., 2014-08-06) Martinez, Melissa; LeBlanc, Julia; Al-Haddad, Mohammad; Sherman, Stuart; DeWitt, John; Department of Medicine, IU School of MedicineAIM: To report the clinical impact of adrenal endoscopic ultrasound fine-needle aspiration (EUS-FNA) in the evaluation of patients with adrenal gland enlargement or mass. METHODS: In a retrospective single-center case-series, patients undergoing EUS-FNA of either adrenal gland from 1997-2011 in our tertiary care center were included. Medical records were reviewed and results of EUS, cytology, adrenal size change on follow-up imaging ≥ 6 mo after EUS and any repeat EUS or surgery were abstracted. A lesion was considered benign if: (1) EUS-FNA cytology was benign and the lesion remained < 1 cm from its original size on follow-up computed tomography (CT), magnetic resonance imaging or repeat EUS ≥ 6 mo after EUS-FNA; or (2) subsequent adrenalectomy and surgical pathology was benign. RESULTS: Ninety-four patients had left (n = 90) and/or right (n = 5) adrenal EUS-FNA without adverse events. EUS indications included: cancer staging or suspected recurrence (n = 31), pancreatic (n = 20), mediastinal (n = 10), adrenal (n = 7), lung (n = 7) mass or other indication (n = 19). Diagnoses after adrenal EUS-FNA included metastatic lung (n = 10), esophageal (n= 5), colon (n = 2), or other cancer (n = 8); benign primary adrenal mass or benign tissue (n = 60); or was non-diagnostic (n = 9). Available follow-up confirmed a benign lesion in 5/9 non-diagnostic aspirates and 32/60 benign aspirates. Four of the 60 benign aspirates were later confirmed as malignant by repeat biopsy, follow-up CT, or adrenalectomy. Adrenal EUS-FNA diagnosed metastatic cancer in 24, and ruled out metastasis in 10 patients. For the diagnosis of malignancy, EUS-FNA of either adrenal had sensitivity, specificity, positive predictive value and negative predictive value of 86%, 97%, 96% and 89%, respectively. CONCLUSION: Adrenal gland EUS-FNA is safe, minimally invasive and a sensitive technique with significant impact in the management of adrenal gland mass or enlargement.