Johnson, Tucker F.

Abstract Objectives To investigate the clinicopathologic and radiologic features of pulmonary hamartomas (PHs) with uncommon clinical presentation. Methods A retrospective clinicopathologic and radiologic review was performed for patients diagnosed (1999-2019) with multiple hamartomas, lesions arising adjacent to a coexisting pulmonary malignancy, and tumors with predominantly extrapulmonary localization. Results Of 979 patients diagnosed with PHs, 6 (0.6%) had multiple hamartomas, 4 (0.4%) had hamartomas adjacent to lung adenocarcinoma, and 2 (0.2%) had large mediastinal masses. Patients with multiple lesions had a median age of 65 years and mean tumor size of 0.9 cm; 1 patient had 3 hamartomas, and 5 patients had 2. Lesions next to adenocarcinomas had a mean size of 1.4 cm, and affected patients had a median age of 69 years. Predominantly mediastinal PHs, diagnosed in a 63-year-old woman and a 68-year-old man, measured 4.1 to 6 cm and were connected to the lung. All lesions were solid on imaging with absence of definitive fat or calcification, concerning for granuloma or malignancy. All cases had typical histology of PH, although one of the mediastinal tumors had an unusual amount of epithelial hyperplasia. Conclusions PHs can be clinically and radiologically challenging to diagnose. Histopathologic examination of biopsies and resection specimens is diagnostically crucial in this setting.

Context.— Respiratory failure appears to be the ultimate mechanism of death in most patients with severe coronavirus disease 2019 (COVID-19) infection. Studies of postmortem COVID-19 lungs largely report diffuse alveolar damage and capillary fibrin thrombi, but we have also observed other patterns. Objective.— To report demographic and radiographic features along with macroscopic, microscopic, and microbiologic postmortem lung findings in patients with COVID-19 infections. Design.— Patients with confirmed COVID-19 infection and postmortem examination (March 2020–May 2020) were included. Clinical findings were abstracted from medical records. Lungs were microscopically reviewed independently by 4 thoracic pathologists. Imaging studies were reviewed by a thoracic radiologist. Results.— Eight patients (7 men, 87.5%; median age, 79 years; range, 69–96 years) died within a median of 17 days (range, 6–100 days) from onset of symptoms. The median lung weight was 1220 g (range, 960–1760 g); consolidations were found in 5 patients (62.5%) and gross thromboemboli were noted in 1 patient (12.5%). Histologically, all patients had acute bronchopneumonia; 6 patients (75%) also had diffuse alveolar damage. Two patients (25%) had aspiration pneumonia in addition. Thromboemboli, usually scattered and rare, were identified in 5 patients (62.5%) in small vessels and in 2 of these patients also in pulmonary arteries. Four patients (50%) had perivascular chronic inflammation. Postmortem bacterial lung cultures were positive in 4 patients (50%). Imaging studies (available in 4 patients) were typical (n = 2, 50%), indeterminate (n = 1, 25%), or negative (n = 1, 25%) for COVID-19 infection. Conclusions.— Our study shows that patients infected with COVID-19 not only have diffuse alveolar damage but also commonly have acute bronchopneumonia and aspiration pneumonia. These findings are important for management of these patients.

Abstract This study assessed the inter-user reproducibility of Computer-Aided Nodule Assessment and Risk Yield (CANARY), a novel analytical tool that risk stratifies lung adenocarcinomas (ADCs) according to defined computed tomography (CT) structural characteristics. CANARY detects nine distinct voxel signatures in ADCs based on standard CT imaging, thereby defining nodule characteristics correlating with patient outcomes, and corresponding to invasion or lepidic growth histologically. A software user segments the borders of each ADC prior to voxel analysis, introducing potential variability into the assessment. While CANARY is a promising method, it requires validation of the analytical variability between users and prediction of accuracy in an independent cohort. To evaluate the reproducibility of CANARY analysis, three independent users who are not part of the CANARY development team segmented and analyzed 50 biopsy-confirmed primary lung ADCs from Vanderbilt University Medical Center. The CT scans of ADCs were selected retrospectively based on the following criteria: ADC-histology proven on biopsy, diagnosed between 2009-2015, less than 3cm in greatest diameter, and stages IA-IV. Users followed a standard operating procedure established at the Mayo Clinic, and were blinded to clinical characteristics and patient outcomes. Results: To measure inter-user variability of ADC voxel composition, the intraclass correlation coefficient (ICC) was calculated based upon the percentage of each voxel subtype within the whole ADC. An ICC of 1 reflects high reproducibility between users. Amongst all 50 ADCs, the average ICC for all nine voxel types was 0.828 (95% CI 0.76, 0.895). The ICC of the four voxel types associated with invasive features on CT was 0.865 (95% CI 0.805, 0.924). ICCs were also calculated using a logarithmic transformation for data normalization, generating an ICC of 0.745 (95% CI 0.663, 0.826) for all nine voxel types, and an ICC of 0.995 (95% CI 0.993, 0.997) for the four voxel types associated with invasion. Conclusions: (1) CANARY analysis of lung ADC voxel signatures appears to be reproducible amongst users, making it a reliable tool for the evaluation of ADC voxel density. (2) Correlation of invasive signatures associated with more aggressive ADCs was nearly perfect amongst users. Additional validation metrics for CANARY with larger datasets are being evaluated, including the accuracy of tumor prognostic predictions between users and analysis of ADC datasets from other institutions. Citation Format: Erica C. Nakajima, Michael P. Frankland, Tucker Johnson, Sanja L. Antic, Ronald A. Karwoski, Bennett Landman, Heidi Chen, Ronald C. Walker, Brian J. Bartholmai, Tobias Peikert, Srinivasan Rajagopalan, Pierre P. Massion, Fabien Maldonado. Assessing the reproducibility of computer-aided nodule assessment and risk yield (CANARY) method to characterize lung adenocarcinomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3723. doi:10.1158/1538-7445.AM2017-3723

AbstractThe antithrombotic surface of endothelium is regulated in a coordinated manner. Tissue factor pathway inhibitor (TFPI) localized at the endothelial cell surface regulates the production of FXa by inhibiting the TF/VIIa complex. Systemic homozygotic deletion of the first Kunitz (K1) domain of TFPI results in intrauterine lethality in mice. Here we define the cellular sources of TFPI and their role in development, hemostasis, and thrombosis using TFPI conditional knockout mice. We used a Cre-lox strategy and generated mice with a floxed exon 4 (TFPIFlox) which encodes for the TFPI-K1 domain. Mice bred into Tie2-Cre and LysM-Cre lines to delete TFPI-K1 in endothelial (TFPITie2) and myelomonocytic (TFPILysM) cells resulted in viable and fertile offspring. Plasma TFPI activity was reduced in the TFPITie2 (71% ± 0.9%, P < .001) and TFPILysM (19% ± 0.6%, P < .001) compared with TFPIFlox littermate controls. Tail and cuticle bleeding were unaffected. However, TFPITie2 mice but not TFPILysM mice had increased ferric chloride–induced arterial thrombosis. Taken together, the data reveal distinct roles for endothelial- and myelomonocytic-derived TFPI.