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The gold standard for enrollment and endpoint assessment in metabolic dysfunction-associated steatosis clinical trials is histologic assessment of a liver biopsy performed on glass slides. However, obtaining the evaluations from several expert pathologists on glass is challenging, as shipping the slides around the country or around the world is time-consuming and comes with the hazards of slide breakage. This study demonstrated that pathologic assessment of disease activity in steatohepatitis, performed using digital images on the AISight whole slide image management system, yields results that are comparable to those obtained using glass slides. The accuracy of scoring for steatohepatitis (nonalcoholic fatty liver disease activity score ≥4 with ≥1 for each feature and absence of atypical features suggestive of other liver disease) performed on the system was evaluated against scoring conducted on glass slides. Both methods were assessed for overall percent agreement with a consensus "ground truth" score (defined as the median score of a panel of three pathologists' glass slides). Each case was also read by three different pathologists, once on glass and once digitally with a minimum 2-week washout period between the modalities. It was demonstrated that the average agreement across three pathologists of digital scoring with ground truth was noninferior to the average agreement of glass scoring with ground truth [noninferiority margin: -0.05; difference: -0.001; 95% CI: (-0.027, 0.026); and p < 0.0001]. For each pathologist, there was a similar average agreement of digital and glass reads with glass ground truth (pathologist A, 0.843 and 0.849; pathologist B, 0.633 and 0.605; and pathologist C, 0.755 and 0.780). Here, we demonstrate that the accuracy of digital reads for steatohepatitis using digital images is equivalent to glass reads in the context of a clinical trial for scoring using the Clinical Research Network scoring system., (© 2024 PathAI. The Journal of Pathology: Clinical Research published by The Pathological Society of Great Britain and Ireland and John Wiley & Sons Ltd.)

Introduction: Breast cancers are complex ecosystem like networks of malignant cells and their associated microenvironment. Applications for machine intelligence and the tumoral microenvironment are expanding frontiers in pathology. Previously, computational approaches have been developed to quantify and spatially analyze immune cells, proportionate stroma, and detect tumor budding. Little work has been done to analyze different types of tumor-associated stromata both quantitatively and computationally in relation to clinical endpoints., Methods: We aimed to quantify stromal features from whole slide images (WSI) including stromata (myxoid, collagenous, immune) and tumoral components and combined them with traditional clinical and pathologic parameters in 120 triple-negative breast cancer (TNBC) patients treated with neoadjuvant chemotherapy (NAC) to predict pathologic complete response (pCR) and poor clinical outcomes., Results: High collagenous stroma on WSI was best associated with lower rates of pCR, while combined high proportionated stroma (myxoid, collagenous, and immune) most optimally predicted worse clinical survival outcomes. When combining clinical, pathologic, and WSI features, Receiver Operator Characteristics (ROC) curves for LASSO features was up to 0.67 for pCR and 0.77 for poor outcomes., Conclusion: The techniques demonstrated in the present study can be performed with appropriate quality assurance. Future trials are needed to demonstrate whether coupling applications for machine intelligence, inclusive of the tumor mesenchyme, can improve outcomes prediction for patients with breast cancer., Competing Interests: Declaration of Competing Interest Author SH is the founder and has ownership equity in Odyssey HealthCare Solutions Inc. The remaining authors have no other possible conflicts of interest to disclose., (Copyright © 2023 Elsevier GmbH. All rights reserved.)

Mass-forming ductal carcinoma in situ (DCIS) detected on core needle biopsy (CNB) is often a radiology-pathology discordance and thought to represent missed invasive carcinoma. This brief report applied supervised machine learning (ML) for image segmentation to investigate a series of 44 mass-forming DCIS cases, with the primary focus being stromal computational signatures. The area under the curve (AUC) for receiver operator curves (ROC) in relation to upgrade to invasive carcinoma from DCIS were as follows: high myxoid stromal ratio (MSR): 0.923, P = <0.001; low collagenous stromal percentage (CSP): 0.875, P = <0.001; and low proportionated stromal area (PSA): 0.682, P = 0.039. The use of ML in mass-forming DCIS could predict upgraded to invasive carcinoma with high sensitivity and specificity. The findings from this brief report are clinically useful and should be further validated by future studies., (Copyright © 2022 Elsevier GmbH. All rights reserved.)

Background and Aims: Manual histological assessment is currently the accepted standard for diagnosing and monitoring disease progression in NASH, but is limited by variability in interpretation and insensitivity to change. Thus, there is a critical need for improved tools to assess liver pathology in order to risk stratify NASH patients and monitor treatment response., Approach and Results: Here, we describe a machine learning (ML)-based approach to liver histology assessment, which accurately characterizes disease severity and heterogeneity, and sensitively quantifies treatment response in NASH. We use samples from three randomized controlled trials to build and then validate deep convolutional neural networks to measure key histological features in NASH, including steatosis, inflammation, hepatocellular ballooning, and fibrosis. The ML-based predictions showed strong correlations with expert pathologists and were prognostic of progression to cirrhosis and liver-related clinical events. We developed a heterogeneity-sensitive metric of fibrosis response, the Deep Learning Treatment Assessment Liver Fibrosis score, which measured antifibrotic treatment effects that went undetected by manual pathological staging and was concordant with histological disease progression., Conclusions: Our ML method has shown reproducibility and sensitivity and was prognostic for disease progression, demonstrating the power of ML to advance our understanding of disease heterogeneity in NASH, risk stratify affected patients, and facilitate the development of therapies., (© 2021 PathAI. Hepatology published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.)

Chondrosarcoma is a highly aggressive primary malignant bone tumor mostly occurring in adults. There are no effective systemic treatments, and patients with this disease have poor survival. miR-181a is an oncomiR that is overexpressed in high-grade chondrosarcoma and promotes tumor progression. Regulator of G-protein signaling 16 (RGS16) is a target of miR-181a. Inhibition of RGS16 expression by miR-181a enhances CXC chemokine receptor 4 signaling, which in turn increases MMP1 and VEGF expression, angiogenesis, and metastasis. Here, we report the results of systemic treatment with anti-miRNA oligonucleotides (AMO) directed against miR-181a utilizing a nanopiece delivery platform (NPs). NPs were combined with a molecular beacon or anti-miR-181a oligonucleotides and are shown to transfect chondrosarcoma cells in vitro and in vivo Intratumoral injection and systemic delivery had similar effects on miR-181a expression in nude mice bearing chondrosarcoma xenografts. Systemic delivery of NPs carrying anti-miR-181a also restored RGS16 expression, decreased expression of VEGF and MMP1, MMP activity, and tumor volume by 32% at day 38, and prolonged survival from 23% to 45%. In conclusion, these data support that systemic delivery of AMO shows promise for chondrosarcoma treatment., (©2019 American Association for Cancer Research.)

Aims: The immune microenvironment is a prognostic factor for various malignancies. The significance of key players of this immune microenvironment, including tumour-infiltrating lymphocytes (TILs) and expression of programmed death-ligand 1 (PD-L1), indoleamine 2,3-dioxygenase (IDO) and tryptophanyl-tRNA synthetase (WARS) in gastrointestinal stromal tumours (GISTs) is largely unknown., Methods and Results: Tissue microarrays were constructed from pathology files, 1996-2016. Immunohistochemistry for PD-L1, IDO and WARS was correlated with tumour size, mitoses and outcomes. TILs expressing CD3, CD4, CD8, FoxP3 and GBP5 were counted. A total of 129 GISTs were analysed. Mean patient age was 62.5 years; 52.0% were male. Tumour location included 89 stomach (69.0%), 33 small bowel (25.6%) and seven other (5.4%). Mean tumour size was 5.6 cm; mean mitoses were 7.2 per 50 high-power field. Nineteen patients (15.0%) developed disease progression, to abdominal wall (n = 8), liver (n = 6) and elsewhere (n = 5). Median progression-free survival was 56.6 months; five patients died of disease. PD-L1 was positive in 88 of 127 tumour samples (69.0%), 114 of 127 tumours were IDO-positive (89.8%) and 60 of 127 were positive for WARS (47.2%). PD-L1 was associated with increased size (P = 0.01), necrosis (P = 0.018) and mitoses (P = 0.006). Disease progression was not associated with PD-L1 (P = 0.44), IDO (P = 0.14) or WARS (P = 0.36) expression. PD-L1-positive GISTs with CD8 + or CD3 + TILs were significantly smaller than tumours with CD8 + or CD3 + TILs., Conclusions: PD-L1 expression was associated with increased size and mitoses. High CD8 + or CD3 + TIL counts were associated with decreased PD-L1/IDO + GIST size. PD-L1 and IDO could be significant in GIST tumour biology, which invites consideration of immunotherapy as a potential treatment option., (© 2017 John Wiley & Sons Ltd.)

A new transintegumental power transformer uses the walls of an isolated intestinal pouch to separate primary and secondary coils. It may surpass transcutaneous devices in heat dissipation potential and in comfort. It was acutely tested in 13 dogs. Corrections in geometry and insulation were suggested by the nine initial trials. In the remaining four animals, up to 14.1 W were delivered, incrementing over 90 to 395 min. Three pouch and two remote thermistors recorded temperature (T) at 10 min intervals. Thirty sets of data were taken at 4 W or less (Group A), 31 at 4-8 W (Group B), and 16 at more than 8 W (Group C). T elevations above reference drift were 0.096 + 0.062 degrees C, 0.468 + 0.234 degrees C, and 0.876 + 0.156 degrees C for groups A, B, and C, respectively. These were significant by t-tests (p less than 0.001 for Group A vs. B; p less than 0.05 for Group B vs. C). The concept appears to be feasible, and longer term implantation trials seem justified.