Autopsies of patients who have died from COVID‐19 have been crucial in delineating patterns of injury associated with SARS‐CoV‐2 infection. Despite their utility, comprehensive autopsy studies are somewhat lacking relative to the global burden of disease, and very few comprehensive studies contextualize the findings to other fatal viral infections. We developed a novel autopsy protocol in order to perform postmortem examinations on victims of COVID‐19 and herein describe detailed clinical information, gross findings, and histologic features observed in the first 16 complete COVID‐19 autopsies. We also critically evaluated the role of ancillary studies used to establish a diagnosis of COVID‐19 at autopsy, including immunohistochemistry (IHC), in situ hybridization (ISH), and electron microscopy (EM). IHC and ISH targeting SARS‐CoV‐2 were comparable in terms of the location and number of infected cells in lung tissue; however, nonspecific staining of bacteria was seen occasionally with IHC. EM was unrevealing in blindly sampled tissues. We then compared the clinical and histologic features present in this series to six archival cases of fatal seasonal influenza and six archival cases of pandemic influenza from the fourth wave of the ‘Spanish Flu’ in the winter of 1920. In addition to routine histology, the inflammatory infiltrates in the lungs of COVID‐19 and seasonal influenza victims were compared using quantitative IHC. Our results demonstrate that the clinical and histologic features of COVID‐19 are similar to those seen in fatal cases of influenza, and the two diseases tend to overlap histologically. There was no significant difference in the composition of the inflammatory infiltrate in COVID‐19 and influenza at sites of acute lung injury at the time of autopsy. Our study underscores the relatively nonspecific clinical features and pathologic changes shared between severe cases of COVID‐19 and influenza, while also providing important caveats to ancillary methods of viral detection.

Cranial fasciitis is an uncommon benign fibroblastic tumor, generally histologically identical to nodular fasciitis. It develops almost exclusively in children. Cranial fasciitis manifests clinically as a painless rapidly growing solitary nodule in the head and neck area, frequently eroding the underlying bone. Thus, this entity is often confused with aggressive lesions such as sarcomas, both clinically and radiologically. Histopathologic examination is essential to differentiate between cranial fasciitis and fibrohistiocytic or even sarcomatous lesions observed in children. In this article, we present a case of cranial fasciitis with intracranial extension in a 2-year-old boy. Although USP6 rearrangement has recently been recognized as a recurring alteration in nodular fasciitis, we present a novel COL1A1-CAMTA1 fusion in this lesion.

Gene expression-based recurrence assays are strongly recommended to guide the use of chemotherapy in hormone receptor-positive, HER2-negative breast cancer, but such testing is expensive, can contribute to delays in care, and may not be available in low-resource settings. Here, we describe the training and independent validation of a deep learning model that predicts recurrence assay result and risk of recurrence using both digital histology and clinical risk factors. We demonstrate that this approach outperforms an established clinical nomogram (area under the receiver operating characteristic curve of 0.83 versus 0.76 in an external validation cohort, p = 0.0005) and can identify a subset of patients with excellent prognoses who may not need further genomic testing.

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