Superior scapular location: An overlooked albeit frequent finding in elastofibroma dorsi.

PURPOSE: To explore the frequency of superior scapular elastofibroma dorsi in a large patient series with elastofibroma dorsi. METHODS: 136 chest CTs from January 2016 to July 2022 reporting elastofibroma dorsi were retrospectively analyzed. Three radiologists assessed the number, size, and location of elastofibroma dorsi. Continuous variables underwent two-tailed t-tests with p < 0.05. Inter-observer agreement was assessed by using Cohen's Kappa values. RESULTS: In 136 patients (mean age, 75.9 +/- 9.8 years; 117 female), 330 elastofibroma dorsi were found. Six (4.4 %) patients had single, 87 (64 %) double, 22 (16.2 %) triple and 21 (15.4 %) quadruple lesions. All single and double lesions were in the inferior scapular regions. 43 (31.6 %) patients had superior scapular lesions in addition to inferior scapular elastofibroma dorsi. Inferior scapular elastofibroma dorsi was significantly larger than superior scapular elastofibroma dorsi. The probability of a right superior lesion was significantly higher in patients with a larger right inferior lesion. Inter-observer agreement was very good for experienced radiologist (κ = 94.1) and good for other radiologists (κ = 79.4 and κ = 78). CONCLUSION: In contrast to current belief, superior scapular elastofibroma dorsi accompanying the typical inferior scapular lesions is not uncommon and can even manifest bilaterally. To the best of our knowledge, this is the first case series reporting prevalence of quadruple elastofibroma dorsi.

Machine learning prediction of Gleason grade group upgrade between in-bore biopsy and radical prostatectomy pathology.

This study aimed to enhance the accuracy of Gleason grade group (GG) upgrade prediction in prostate cancer (PCa) patients who underwent MRI-guided in-bore biopsy (MRGB) and radical prostatectomy (RP) through a combined analysis of prebiopsy and MRGB clinical data. A retrospective analysis of 95 patients with prostate cancer diagnosed by MRGB was conducted where all patients had undergone RP. Among the patients, 64.2% had consistent GG results between in-bore biopsies and RP, whereas 28.4% had upgraded and 7.4% had downgraded results. GG1 biopsy results, lower biopsy core count, and fewer positive cores were correlated with upgrades in the entire patient group. In patients with GG > 1 , larger tumor sizes and fewer biopsy cores were associated with upgrades. By integrating MRGB data with prebiopsy clinical data, machine learning (ML) models achieved 85.6% accuracy in predicting upgrades, surpassing the 64.2% baseline from MRGB alone. ML analysis also highlighted the value of the minimum apparent diffusion coefficient ( ADC min ) for GG > 1 patients. Incorporation of MRGB results with tumor size, ADC min value, number of biopsy cores, positive core count, and Gleason grade can be useful to predict GG upgrade at final pathology and guide patient selection for active surveillance.