Notes

Rheumatoid arthritis being an first display regarding malignancy: two situation reviews.
Charcot foot (CF) is a rare complication of diabetes associated with foot deformities and foot ulcers. Peripheral arterial disease (PAD) is a factor of poor prognosis in patients with diabetic foot ulcers (DFUs). However, PAD has infrequently been studied in CF. We aimed to determine the prevalence, the characteristics and the prognosis of PAD in a large group of patients with diabetic CF. We retrospectively compared 56 patients with diabetic CF to 116 patients with diabetic foot without CF. The prevalence of PAD in patients with CF was 66.1%. Compared to patients without CF, patients with CF had similar risks to have PAD (OR 0.98, 95%CI 0.50-1.94, p= .97) and neuro-ischemic DFUs (OR 1.19, 95%CI 0.57-2.49, p= .65), more risk to have lesions of distal arteries (OR 4.17, 95%CI 1.76-9.94, p= .001) and less risk to need revascularization (OR 0.14, 95%CI 0.06-0.36, p less then .001). In patients with CF, PAD was strongly predicted by DFUs (OR 24.55, 95%CI 1.80-334.43, p= .016) and coronary artery disease (OR 17.11, 95%CI 1.75-167.43, p =.015). Survival rate and limb salvage rate in patients with CF were not worsened by PAD and by neuro-ischemic DFUs, respectively. In conclusion, we show that PAD should not be overlooked in patients with diabetic CF, especially in those having DFUs or coronary artery disease. PAD in patients with CF differed from that of patients without CF since it predominated in distal arteries and required less often revascularization.Transitioning from parental leave during radiology residency training can be a time of stress and uncertainty. However, there are ways that program directors can help make the transition smoother and less overwhelming. Trainees report numerous stressors upon returning from leave involving childcare, lactation concerns and logistics, and discrimination. Program directors can help alleveate these stressors by counseling trainees returning from parental leave and providing reseources and a supportive enviroment. This article provides a structured frame work with tool for programs directors to ensure the transition from parental leave back to training is a smooth one.
To evaluate the diagnostic performance of the radiomics score (rad-score) for differentiating focal-type autoimmune pancreatitis (fAIP) from pancreatic ductal adenocarcinoma (PDAC).

This retrospective review included 42 consecutive patients with fAIP diagnosed according to the International Consensus Diagnostic Criteria between January 2011 and December 2018. Furthermore, 334 consecutive patients with PDAC confirmed by pathology were also reviewed during the same period. Patients with PDAC and fAIP were matched via propensity score matching (PSM). this website All patients underwent multidetector computed tomography (MDCT). For each patient, 1409 radiomics features of the portal phase were extracted and reduced using the least absolute shrinkage and selection operator (LASSO) logistic regression algorithm. The portal rad-score performance was assessed based on its discriminative ability.

After PSM, we matched 55 patients with PDAC to 42 patients with fAIP, based on clinical and CT characteristics (e.g., patient age, sex, body mass index, location, size, enhanced mode). A rad-score for discriminating fAIP from PDAC, which contained four CT derived radiomic features, was developed (area under the curve=0.97). The sensitivity, specificity, and accuracy of the radiomics model were 95.24%, 92.73% and 0.94, respectively.

The portal rad-score can accurately and noninvasively differentiate fAIP from PDAC.
The portal rad-score can accurately and noninvasively differentiate fAIP from PDAC.
To evaluate a weakly supervised deep learning approach to breast Magnetic Resonance Imaging (MRI) assessment without pixel level segmentation in order to improve the specificity of breast MRI lesion classification.

In this IRB approved study, the dataset consisted of 278,685 image slices from 438 patients. The weakly supervised network was based on the Resnet-101 architecture. Training was implemented using the Adam optimizer and a final SoftMax score threshold of 0.5 was used for two class classification (malignant or benign). 278,685 image slices were combined into 92,895 3-channel images. 79,871 (85%) images were used for training and validation while 13,024 (15%) images were separated for testing. Of the testing dataset, 11,498 (88%) were benign and 1531 (12%) were malignant. Model performance was assessed.

The weakly supervised network achieved an AUC of 0.92 (SD ± 0.03) in distinguishing malignant from benign images. The model had an accuracy of 94.2% (SD ± 3.4) with a sensitivity and specificity of 74.4% (SD ± 8.5) and 95.3% (SD ± 3.3) respectively.

It is feasible to use a weakly supervised deep learning approach to assess breast MRI images without the need for pixel-by-pixel segmentation yielding a high degree of specificity in lesion classification.
It is feasible to use a weakly supervised deep learning approach to assess breast MRI images without the need for pixel-by-pixel segmentation yielding a high degree of specificity in lesion classification.
Biopsy of lung nodules in the lower lung fields can be difficult because of breathing motion. Ipsilateral phrenic nerve block (PNB) before biopsy should make the biopsy safer, easier, and more precisely targeted. We describe the use of ultrasound-guided PNB before lung nodule biopsy, including relevant anatomy and variations, complications, and technique, along with our first 40 cases.

We retrospectively reviewed patients who underwent PNB before computed tomography (CT)- or ultrasound-guided lung nodule biopsy from April 2015 through March 2020. Patient demographics, CT fluoroscopy time, radiation dose, complications, diagnostic yield, and effectiveness of PNB were recorded. Effectiveness of PNB was based on direct observation of diaphragmatic motion. Control group data for biopsies during the same time frame were collected and matched with nodules ≤1 cm from the PNB group.

Among 40 patients identified, no complications occurred related to the PNB. Mean (SD) nodule size was 12.4 (6.2) mm. True-positive results were obtained in 39 patients (98%), with 1 false-negative after an ineffective PNB.
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