Fully automated kidney image biomarker prediction in ultrasound scans using Fast-Unet+.

Any kidney dimension and volume variation can be a remarkable indicator of kidney disorders. Precise kidney segmentation in standard planes plays an undeniable role in predicting kidney size and volume. On the other hand, ultrasound is the modality of choice in diagnostic procedures. This paper proposes a convolutional neural network with nested layers, namely Fast-Unet++, promoting the Fast and accurate Unet model. First, the model was trained and evaluated for segmenting sagittal and axial images of the kidney. Then, the predicted masks were used to estimate the kidney image biomarkers, including its volume and dimensions (length, width, thickness, and parenchymal thickness). Finally, the proposed model was tested on a publicly available dataset with various shapes and compared with the related networks. Moreover, the network was evaluated using a set of patients who had undergone ultrasound and computed tomography. The dice metric, Jaccard coefficient, and mean absolute distance were used to evaluate the segmentation step. 0.97, 0.94, and 3.23 mm for the sagittal frame, and 0.95, 0.9, and 3.87 mm for the axial frame were achieved. The kidney dimensions and volume were evaluated using accuracy, the area under the curve, sensitivity, specificity, precision, and F1.

Basilic vein aneurysm and palmar intramuscular hemangioma with peri and inter tendinous growth.

In this report, we describe a case of concomitant basilic vein aneurysm and palmar hemangioma with peri- and inter-tendinous growth around the fourth and fifth flexor digitorum superficialis and flexor digitorum profundus tendons. It seems reasonable for physicians and radiologists to keep in mind the possibility of venous aneurysms in the presence of soft tissue hemangiomas; as they can present as palpable mass and be mistaken for other pathologies. Familiarity with clinical and imaging findings of this entity could be helpful to prevent misdiagnosis.

Is Zika Virus an Emerging TORCH Agent? An Invited Commentary.

Zika virus (ZIKV) is a mosquito-borne arbovirus from the family Flaviviridae, which had caused some epidemics since its discovery in 1947 without any significant impacts on public health. In 2015, however, a 20-fold increase in congenital microcephaly cases in northeastern Brazil was attributed to prenatally acquired ZIKV infection. Traditionally, TORCH agents have 4 common characteristics including causing a mild illness in infected mother, vertical transmission to fetus, developing several anomalies in the affected fetus, and in some instances, maternal therapy may not ameliorate fetal prognosis. Prenatal ZIKV infection has shown the aforementioned characteristics during the recent epidemics in South America and the Caribbean region; therefore, it should be considered as an emerging TORCH agent that may seriously threaten public health. Fetal ultrasound can be used as a safe, inexpensive, and easy-to-access imaging modality for detecting suspicious cases of congenital Zika syndrome in utero and suggesting confirmatory diagnostic examinations to these patients.