Domain Adaptation-Based Deep Learning for Automated Tumor Cell (TC) Scoring and Survival Analysis on PD-L1 Stained Tissue Images.

We report the ability of two deep learning-based decision systems to stratify non-small cell lung cancer (NSCLC) patients treated with checkpoint inhibitor therapy into two distinct survival groups. Both systems analyze functional and morphological properties of epithelial regions in digital histopathology whole slide images stained with the SP263 PD-L1 antibody. The first system learns to replicate the pathologist assessment of the Tumor Cell (TC) score with a cut-point for positivity at 25% for patient stratification.

Comparison of continuous measures across diagnostic PD-L1 assays in non-small cell lung cancer using automated image analysis.

Tumor programmed cell death ligand-1 (PD-L1) expression is a key biomarker to identify patients with non-small cell lung cancer who may have an enhanced response to anti-programmed cell death-1 (PD-1)/PD-L1 treatment. Such treatments are used in conjunction with PD-L1 diagnostic immunohistochemistry assays. We developed a computer-aided automated image analysis with customized PD-L1 scoring algorithm that was evaluated via correlation with manual pathologist scores and used to determine comparability across PD-L1 immunohistochemistry assays.

Relevance of deep learning to facilitate the diagnosis of HER2 status in breast cancer.

Tissue biomarker scoring by pathologists is central to defining the appropriate therapy for patients with cancer. Yet, inter-pathologist variability in the interpretation of ambiguous cases can affect diagnostic accuracy. Modern artificial intelligence methods such as deep learning have the potential to supplement pathologist expertise to ensure constant diagnostic accuracy.

Gadofosveset-based biomarker of tissue albumin concentration: Technical validation in vitro and feasibility in vivo.

Purpose: There is currently no adequate method of mapping physiologic and pathophysiologic tissue albumin concentrations in human subjects. The objective of this study was to devise and evaluate a biomarker of regional albumin concentration using gadofosveset-enhanced MRI.

Theory And Methods: A binding and relaxation model was devised and evaluated in vitro in solutions of albumin at 3.

Noninvasive tumor hypoxia measurement using magnetic resonance imaging in murine U87 glioma xenografts and in patients with glioblastoma.

Purpose: There is a clinical need for noninvasive, nonionizing imaging biomarkers of tumor hypoxia and oxygenation. We evaluated the relationship of T1 -weighted oxygen-enhanced magnetic resonance imaging (OE-MRI) measurements to histopathology measurements of tumor hypoxia in a murine glioma xenograft and demonstrated technique translation in human glioblastoma multiforme.

Methods: Preclinical evaluation was performed in a subcutaneous murine human glioma xenograft (U87MG).

Exploring intra- and inter-reader variability in uni-dimensional, bi-dimensional, and volumetric measurements of solid tumors on CT scans reconstructed at different slice intervals.

Objective: Understanding magnitudes of variability when measuring tumor size may be valuable in improving detection of tumor change and thus evaluating tumor response to therapy in clinical trials and care. Our study explored intra- and inter-reader variability of tumor uni-dimensional (1D), bi-dimensional (2D), and volumetric (VOL) measurements using manual and computer-aided methods (CAM) on CT scans reconstructed at different slice intervals.

Materials And Methods: Raw CT data from 30 patients enrolled in oncology clinical trials was reconstructed at 5, 2.

Age at onset and vascular pathology in late-life depression.

Objective: There is considerable evidence to suggest that late-onset depression may be etiologically distinct from early-onset depression. The aim of this study was to compare vascular function and magnetic resonance imaging-defined brain ischemic changes between early-onset depressed (EOD) and late-onset depressed (LOD) subjects.

Design: Case-control study.

Vascular function in older adults with depressive disorder.

Background: Cerebrovascular disease plays an important role in depressive disorder, especially in older adults. An understanding of vascular function in depression is important etiologically and to develop innovative treatments that may improve prognosis by ameliorating vascular damage.

Methods: This study assessed endothelial function, arterial stiffness, and atherosclerosis in a variety of vessel beds in 25 elderly subjects with depressive disorder compared with 21 nondepressed control subjects.

Robust tissue boundary detection for cerebral cortical thickness estimation.

This paper presents an algorithm for determining regional cerebral grey matter cortical thickness from magnetic resonance scans. In particular, the modification of a gradient-based edge detector into an iso-grey-level boundary detector for reliably determining the low-contrast grey-white matter interface is described and discussed. The reproducibility of the algorithm over 31 gyral regions is assessed using repeat scans of four subjects, and a technique for correcting the misplacement of the grey-white matter boundary is shown to significantly reduce the systematic error on the reproducibility.