Early Development of a Machine Learning Approach to Quantify MYC Immunohistochemical Staining in Lymphoma

Newer data suggest that double expression of MYC and BCL2 proteins (DE) evaluated by quantitative immunohistochemistry (qIHC) may be a powerful marker of worse prognosis in diffuse large B cell lymphoma (DLBCL). Testing for DE status, defined as >40% MYC+ and >50% BCL2+ tumor cells, is recommended in the WHO 2016 classification and clinical trials are using DE scoring to assign therapy arms. However, other data suggest that significant variability in manual DE scoring diminishes the predictive value. Error sources include high interobserver variability (IOV) associated with field choice, discrimination of tumor immunoreactivity from adjacent non-neoplastic cells, cell-to-cell variability in staining intensity, crush artifacts and necrosis. Thus, there is a need for standardized, reproducible approaches for DE scoring by qIHC. To address this need, we have begun developing a novel machine-learning approach to analyze IHC digital pathology whole-slide images, focusing initially on MYC IHC.

Digital whole-slide images (400x) of 22 DLBCL cases were uploaded to a web-based annotation platform. Using all cases, one annotator created 138 regions of interest (ROIs) containing approximately 200 nucleated cells and representing a variety of tissue types. Eight pathologists were assigned the same 10 ROIs in which to annotate all nuclei from which ground-truth seed nucleus labels (location, classification) were created for a validation set. Nuclei were classified as “tumor-positive”, “tumor-negative”, “non-tumor-positive”, “non-tumor-negative”, or “unknown”. This generated a set of 15,792 annotations with 1974 +/- 272 (Avg+/-STD) labels/annotator. Agglomerative hierarchical clustering afforded the creation of 2299 ground-truth seed locations. A maximum diameter of 3 mm/cluster was set by visual inspection of annotations. Of these seed locations, 1041 (45%) were detected by 8/8 annotators and, on average, 6/8 agreed on class. 302 +/- 72 (Avg+/-STD) “tumor positive” labels per annotator generated 382 seeds locations, 178 (47%) of which were detected by 8/8 annotators, with an average of 7.5/8 agreeing on class. 286 +/- 168 (Avg+/-STD) “tumor-negative” labels per annotator generated 336 seeds, 195 (58%) of which were detected by 8/8 annotators, with an average of 5/8 agreeing on class. Among all classes, the “tumor-positive” label displayed best overall label agreement whereas the “tumor-negative“ label yielded similar localization rate, but lower class agreement. These promising early findings provide a novel basis for quantifying IOV and utilizing multi-observer agreement to create a ground-truth validation set for a supervised machine learning approach to qIHC. Future efforts will make use of these data to optimize the validation set by rationally determining the number of additional annotations required, optimizing the number of annotators per ROI required, devising an adaptive approach to nuclear clustering based on nuclear density, and utilizing the additional 31,422 annotations in hand from all annotators as a robust algorithm training set.

Histopathologic and Ultrastructural Findings in Human Myocardium After Stereotactic Body Radiation Therapy for Recalcitrant Ventricular Tachycardia

BACKGROUND

Stereotactic body radiation therapy (SBRT) is a novel treatment for refractory ventricular tachycardia (VT). While outcomes have been described in small studies, histological findings after SBRT for VT are unknown.

METHODS

We identified 4 explanted hearts in the context of transplant that received prior SBRT as part of an 11-patient compassionate use series at our institution. Clinical VTs and computed tomography-defined target volume areas of SBRT were correlated to the anatomic specimens. Gross pathological, histological, and ultrastructural examination of tissue in the target area of SBRT was performed.

RESULTS

All 4 patients had nonischemic cardiomyopathy, and 3 had left ventricular assist devices. In all cases, patients had recurrent sustained VT and had failed multiple antiarrhythmics and radiofrequency ablations. Four patients underwent 5 total SBRT therapy sessions with 25-Gy single-fraction dose delivered to the area of culprit scar. The time from SBRT to explant ranged from 12 to 250 days. Histopathologic features following radiation were comparable in all patients and were characterized by areas of subendocardial necrosis surrounded by a rim of fibrosis. In 1 patient, the surrounding myocardium showed cytoplasmic vacuolization in myocytes and in another patchy interstitial fibrosis. Vascular changes consisted of myointimal thickening with prominence of endothelial cells. Electron microscopy of myocardium showed irregular, convoluted intercalated disc regions, loss of contractile elements with disrupted and haphazardly arranged myofibrils, and edematous mitochondria with loss of cisternae.

CONCLUSIONS

Here, we report the first series of findings in human tissue in 4 patients after SBRT. Histopathologic features were consistent across all 4 patients and were indicative of cell injury, death, and to a lesser extent, fibrosis. Electron microscopy demonstrated features consistent with acute injury. These specimens provide radiobiological mechanisms of acute cellular injury during SBRT for VT, which may have an antiarrhythmic effect before the onset of fibrosis.

Lung Cancer Staging

Lung cancer staging is a foundation of patient care, informing management decisions and prognosis. This comprehensive overview of the current 8th edition American Joint Committee on Cancer Cancer Staging Manual addresses common difficulties in staging, such as measuring the invasive component of adenocarcinomas and staging multiple lung nodules.