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Nonmass lesions were the major cause of false-positive breast MRI findings. BI-RADS descriptors are not sufficient for differentiating benign and malignant nonmass lesions.

Sensitivity and specificity of ueMRM in mass lesions equal that of ceMRM. However, a reduced lesion visibility in ueMRM may lead to more false-negative findings.

Patients hospitalized for infection with SARS-CoV-2 typically present with pneumonia. The respiratory failure is frequently complicated by pulmonary embolism in segmental pulmonary arteries. The distribution of pulmonary embolism in regard to lung parenchymal opacifications has not been investigated yet. Methods: All patients with COVID-19 treated at a medical intensive care unit between March 8th and April 15th, 2020 undergoing computed tomography pulmonary angiography (CTPA) were included. All CTPA were assessed by two radiologists independently in respect to parenchymal changes and pulmonary embolism on a lung segment basis. Results: Out of 22 patients with severe COVID-19 treated within the observed time period, 16 (age 60.4 ± 10.2 years, 6 female SAPS2 score 49.2 ± 13.9) underwent CT. A total of 288 lung segment were analyzed. Thrombi were detectable in 9/16 (56.3%) patients, with 4.4 ± 2.9 segments occluded per patient and 40/288 (13.9%) segments affected in the whole cohort. Patients with thrombi had significantly worse segmental opacifications in CT (p < 0.05) and all thrombi were located in opacitated segments. There was no correlation between d-dimer level and number of occluded segmental arteries. Conclusions: Thrombi in segmental pulmonary arteries are common in COVID-19 and are located in opacitated lung segments. This might suggest local clot formation.

Introduction Primary prostate cancer (PCa) can be visualized on prostate-specific membrane antigen positron emission tomography (PSMA-PET) with high accuracy. However, intraprostatic lesions may be missed by visual PSMA-PET interpretation. In this work, we quantified and characterized the intraprostatic lesions which have been missed by visual PSMA-PET image interpretation. In addition, we investigated whether PSMA-PET-derived radiomics features (RFs) could detect these lesions. Methodology This study consists of two cohorts of primary PCa patients: a prospective training cohort (n = 20) and an external validation cohort (n = 52). All patients underwent 68Ga-PSMA-11 PET/CT and histology sections were obtained after surgery. PCa lesions missed by visual PET image interpretation were counted and their International Society of Urological Pathology score (ISUP) was obtained. Finally, 154 RFs were derived from the PET images and the discriminative power to differentiate between prostates with or without visually undetectable lesions was assessed and areas under the receiver-operating curve (ROC-AUC) as well as sensitivities/specificities were calculated. Results In the training cohort, visual PET image interpretation missed 134 tumor lesions in 60% (12/20) of the patients, and of these patients, 75% had clinically significant (ISUP > 1) PCa. The median diameter of the missed lesions was 2.2 mm (range: 1–6). Standard clinical parameters like the NCCN risk group were equally distributed between patients with and without visually missed lesions (p < 0.05). Two RFs (local binary pattern (LBP) size-zone non-uniformality normalized and LBP small-area emphasis) were found to perform excellently in visually unknown PCa detection (Mann-Whitney U: p < 0.01, ROC-AUC: ≥ 0.93). In the validation cohort, PCa was missed in 50% (26/52) of the patients and 77% of these patients possessed clinically significant PCa. The sensitivities of both RFs in the validation cohort were ≥ 0.8. Conclusion Visual PSMA-PET image interpretation may miss small but clinically significant PCa in a relevant number of patients and RFs can be implemented to uncover them. This could be used for guiding personalized treatments.