Automated analysis of small intestinal lamina propria to distinguish normal, Celiac Disease, and Non-Celiac Duodenitis biopsy images.

BACKGROUND AND OBJECTIVE: Celiac Disease (CD) is characterized by gluten intolerance in genetically predisposed individuals. High disease prevalence, absence of a cure, and low diagnosis rates make this disease a public health problem. The diagnosis of CD predominantly relies on recognizing characteristic mucosal alterations of the small intestine, such as villous atrophy, crypt hyperplasia, and intraepithelial lymphocytosis. However, these changes are not entirely specific to CD and overlap with Non-Celiac Duodenitis (NCD) due to various etiologies. We investigated whether Artificial Intelligence (AI) models could assist in distinguishing normal, CD, and NCD (and unaffected individuals) based on the characteristics of small intestinal lamina propria (LP). METHODS: Our method was developed using a dataset comprising high magnification biopsy images of the duodenal LP compartment of CD patients with different clinical stages of CD, those with NCD, and individuals lacking an intestinal inflammatory disorder (controls). A pre-processing step was used to standardize and enhance the acquired images. RESULTS: For the normal controls versus CD use case, a Support Vector Machine (SVM) achieved an Accuracy (ACC) of 98.53%. For a second use case, we investigated the ability of the classification algorithm to differentiate between normal controls and NCD. In this use case, the SVM algorithm with linear kernel outperformed all the tested classifiers by achieving 98.55% ACC. CONCLUSIONS: To the best of our knowledge, this is the first study that documents automated differentiation between normal, NCD, and CD biopsy images. These findings are a stepping stone toward automated biopsy image analysis that can significantly benefit patients and healthcare providers.

Human Polyomavirus 9-An Emerging Cutaneous and Pulmonary Pathogen in Solid Organ Transplant Recipients.

IMPORTANCE: We describe the first report to our knowledge of cutaneous and systemic pathogenicity of human polyomavirus 9 in solid organ transplant recipients. OBJECTIVE: Three solid organ transplant recipients developed a widespread, progressive, violaceous, and hyperkeratotic skin eruption. All died from pulmonary and multiorgan failure around 1 year from onset of the rash. Routine clinical diagnostic testing could not identify any causative agent; therefore, samples and autopsies were investigated for novel pathogens using high-throughput sequencing. DESIGN, SETTING, AND PARTICIPANTS: This case series, including 3 solid organ transplant recipients who developed characteristic pink, violaceous, or brown hyperkeratotic papules and plaques throughout the body, was conducted at the Columbia University Medical Center. Lesional skin biopsies were collected from all 3 patients and subjected to high-throughput illumina sequencing for identification of microbial pathogens. Human polyomavirus 9 was identified in lesional skin biopsies. We subsequently collected ocular swabs, oral swabs, urine samples, and blood samples from patients, and organ tissues at autopsy in 1 patient. We investigated these samples for the presence of human polyomavirus 9 using in situ hybridization and quantitative polymerase chain reaction (PCR) assays. MAIN OUTCOMES AND MEASURES: A description of the clinical and pathologic findings of 3 patients. RESULTS: This case series study found that human polyomavirus 9 was detected in the skin biopsies of all 3 patients by a capture-based high-throughput sequencing method platform (VirCapSeq-VERT). Human polyomavirus 9 was also detected in blood, oral, ocular swabs, and urine by real-time polymerase chain reaction (PCR) assay. In situ hybridization and quantitative PCR assays were performed on the skin biopsies from 3 patients and lung autopsy of 1 patient, which showed the presence of human polyomavirus 9 messenger RNA transcripts, indicating active viral replication and pathogenesis in the skin and lungs. CONCLUSIONS AND RELEVANCE: Human polyomavirus 9 was associated with the widespread cutaneous eruption. All 3 patients had progression of cutaneous disease, accompanied by clinical deterioration, pulmonary failure, and death. One patient underwent autopsy and human polyomavirus 9 was identified in the lungs and paratracheal soft tissue. These findings suggest that human polyomavirus 9 may be associated with cutaneous and possibly pulmonary infection and death in solid organ transplant recipients.

Automated interpretation of biopsy images for the detection of celiac disease using a machine learning approach.

BACKGROUND AND OBJECTIVES: Celiac disease is an autoimmune disease occurring in about 1 in 100 people worldwide. Early diagnosis and efficient treatment are crucial in mitigating the complications that are associated with untreated celiac disease, such as intestinal lymphoma and malignancy, and the subsequent high morbidity. The current diagnostic methods using small intestinal biopsy histopathology, endoscopy, and video capsule endoscopy (VCE) involve manual interpretation of photomicrographs or images, which can be time-consuming and difficult, with inter-observer variability. In this paper, a machine learning technique was developed for the automation of biopsy image analysis to detect and classify villous atrophy based on modified Marsh scores. This is one of the first studies to employ conventional machine learning to automate the use of biopsy images for celiac disease detection and classification. METHODS: The Steerable Pyramid Transform (SPT) method was used to obtain sub bands from which various types of entropy and nonlinear features were computed. All extracted features were automatically classified into two-class and multi-class, using six classifiers. RESULTS: An accuracy of 88.89%, was achieved for the classification of two-class villous abnormalities based on analysis of Hematoxylin and Eosin (H&E) stained biopsy images. Similarly, an accuracy of 82.92% was achieved for the two-class classification of red-green-blue (RGB) biopsy images. Also, an accuracy of 72% was achieved in the classification of multi-class biopsy images. CONCLUSION: The results obtained are promising, and demonstrate the possibility of automating biopsy image interpretation using machine learning. This can assist pathologists in accelerating the diagnostic process without bias, resulting in greater accuracy, and ultimately, earlier access to treatment.

SATB2 in Neoplasms of Lung, Pancreatobiliary, and Gastrointestinal Origins.

OBJECTIVES: Special AT-rich binding protein 2 (SATB2) immunohistochemistry (IHC) has high sensitivity and specificity for colorectal adenocarcinoma (CRC), but data on its expression in specific subsets of pulmonary, gastric, small bowel, and pancreatobiliary adenocarcinomas (ADCAs) are relatively limited or discordant. We assessed SATB2 expression in a large cohort of ADCAs from these sites to determine its reliability in distinguishing CRC from them. METHODS: SATB2 IHC was performed on 335 neoplasms, including 40 lung ADCAs, 165 pancreatobiliary neoplasms (34 intraductal papillary mucinous neoplasms [IPMNs], 19 pancreatic ADCAs, 112 cholangiocarcinomas [CCs]), and 35 gastric, 13 small bowel, 36 ampullary (AMP), and 46 CRC ADCAs. The cases were evaluated for positivity (defined as ≥5% nuclear staining), and an H-score was calculated based on the percentage of SATB2+ cells and staining intensity. Analysis was performed to determine the optimal H-score threshold to separate CRC and non-CRC. RESULTS: SATB2 was positive in 3% of lung, 2% of CC, 17% of gastric, 38% of small bowel, and 6% of AMP ADCAs. All pancreatic ADCA/IPMNs were negative, and 87% CRCs were positive. CONCLUSIONS: SATB2 is not entirely specific for colorectal origin and can be expressed in a subset of gastrointestinal ADCAs. It is most useful in the differential of CRC vs lung and pancreatobiliary ADCAs.

Masson Trichrome and Sulfated Alcian Blue Stains Distinguish Light Chain Deposition Disease From Amyloidosis in the Lung.

Light chain deposition disease, characterized by nonamyloidogenic deposits of immunoglobulin light chains, is rare in the lung and possibly underdiagnosed due to low clinical suspicion and lack of readily accessible tests. We encountered a case of pulmonary light chain deposition disease (PLCDD) in which light chain deposits appeared crimson red with a Masson trichrome (MT) stain and salmon pink with a sulfated Alcian blue (SAB) stain. This prompted us to characterize a series of PLCDD cases and assess the utility of MT and SAB stains to distinguish them from amyloidosis. From the pathology archives of 2 institutions spanning 10 years, we identified 11 cases of PLCDD, including 7 diagnosed as such and 4 determined retrospectively. The deposits in all cases of PLCDD stained crimson red with MT and salmon pink with SAB, while the cases of pulmonary amyloid (n=10) stained blue-gray and blue-green, respectively. The immunoglobulin light chain nature of the deposits was confirmed in 10 of 11 cases by either immunofluorescence microscopy (n=5) or mass spectrometry (n=5). Transmission electron microscopy revealed osmiophilic, electron-dense deposits in all cases analyzed (n=3). An extranodal marginal zone lymphoma of mucosa-associated lymphoid tissue type was diagnosed in 10 cases and 1 represented a plasma cell neoplasm. Our study highlights the importance of considering PLCDD in the differential diagnosis of amyloid-like deposits in the lung and the value of performing MT and SAB stains to distinguish between PLCDD and amyloidosis.

Forty Postmortem Examinations in COVID-19 Patients.

OBJECTIVES: Although diffuse alveolar damage, a subtype of acute lung injury (ALI), is the most common microscopic pattern in coronavirus disease 2019 (COVID-19), other pathologic patterns have been described. The aim of the study was to review autopsies from COVID-19 decedents to evaluate the spectrum of pathology and correlate the results with clinical, laboratory, and radiologic findings. METHODS: A comprehensive and quantitative review from 40 postmortem examinations was performed. The microscopic patterns were categorized as follows: "major" when present in more than 50% of cases and "novel" if rarely or not previously described and unexpected clinically. RESULTS: Three major pulmonary patterns were identified: ALI in 29 (73%) of 40, intravascular fibrin or platelet-rich aggregates (IFPAs) in 36 (90%) of 40, and vascular congestion and hemangiomatosis-like change (VCHL) in 20 (50%) of 40. The absence of ALI (non-ALI) was novel and seen in 11 (27%) of 40. Compared with ALI decedents, those with non-ALI had a shorter hospitalization course (P = .02), chest radiographs with no or minimal consolidation (P = .01), and no pathologically confirmed cause of death (9/11). All non-ALI had VCHL and IFPAs, and clinically most had cardiac arrest. CONCLUSIONS: Two distinct pulmonary phenotypic patterns-ALI and non-ALI-were noted. Non-ALI represents a rarely described phenotype. The cause of death in non-ALI is most likely COVID-19 related but requires additional corroboration.

Hepatic pathology in patients dying of COVID-19: a series of 40 cases including clinical, histologic, and virologic data.

The novel coronavirus SARS-CoV-2 (coronavirus disease 19, or COVID-19) primarily causes pulmonary injury, but has been implicated to cause hepatic injury, both by serum markers and histologic evaluation. The histologic pattern of injury has not been completely described. Studies quantifying viral load in the liver are lacking. Here we report the clinical and histologic findings related to the liver in 40 patients who died of complications of COVID-19. A subset of liver tissue blocks were subjected to polymerase chain reaction (PCR) for viral ribonucleic acid (RNA). Peak levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were elevated; median ALT peak 68 U/l (normal up to 46 U/l) and median AST peak 102 U/l (normal up to 37 U/l). Macrovesicular steatosis was the most common finding, involving 30 patients (75%). Mild lobular necroinflammation and portal inflammation were present in 20 cases each (50%). Vascular pathology, including sinusoidal microthrombi, was infrequent, seen in six cases (15%). PCR of liver tissue was positive in 11 of 20 patients tested (55%). In conclusion, we found patients dying of COVID-19 had biochemical evidence of hepatitis (of variable severity) and demonstrated histologic findings of macrovesicular steatosis and mild acute hepatitis (lobular necroinflammation) and mild portal inflammation. We also identified viral RNA in a sizeable subset of liver tissue samples.

COVID-19 Associated Hepatitis Complicating Recent Living Donor Liver Transplantation.

We present a case of COVID-19 hepatitis in a living donor liver allograft recipient whose donor subsequently tested positive for COVID-19. The patient is a female infant with biliary atresia (failed Kasai procedure). She recovered well, with improving liver function tests for 4 days. On post-operative day (POD) 4 the patient developed respiratory distress and fever. COVID-19 testing (polymerase chain reaction) was positive. Liver function tests increased approximately 5-fold. Liver biopsy showed moderate acute hepatitis with prominent clusters of apoptotic hepatocytes and associated cellular debris. Lobular lymphohistiocytic inflammation was noted. Typical portal features of mild to moderate acute cellular rejection were also noted.