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Uterine fibroids are the most common gynecologic neoplasm. Although non-degenerated fibroids are easily identifiable on imaging, degenerated fibroids, fibroid variants, and fibroids with unusual growth patterns can constitute a diagnostic dilemma. Identification of these abnormal morphologic features can alter the diagnosis of presumed uterine fibroids and hence change management plans. This article reviews the typical and atypical radiologic imaging features of uterine fibroids, with an emphasis on the pitfalls, mimics, and radiologically identifiable features that can alter clinical management plans., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background Prostatic ductal adenocarcinoma (DAC) is an aggressive histologic variant of prostate cancer that often warrants multimodal therapy and poses a significant diagnostic challenge clinically and at imaging. Purpose To develop multiparametric MRI criteria to define DAC and to assess their diagnostic performance in differentiating DAC from prostatic acinar adenocarcinoma (PAC). Materials and Methods Men with histologically proven DAC who had multiparametric MRI before radical prostatectomy were retrospectively identified from January 2011 through November 2018. MRI features were predefined using a subset of nine DACs and then compared for men with peripheral-zone DACs 1 cm or greater in size and men with matched biopsy-confirmed International Society of Urological Pathology grade group 4-5 PAC, by four independent radiologists blinded to the pathologic diagnosis. Diagnostic performance was determined by consensus read. Patient and tumor characteristics were compared by using the Fisher test, t -tests, and Mann-Whitney U test. Agreement (Cohen κ) and sensitivity analyses were also performed. Results There were 59 men with DAC (median age, 63 years [interquartile range, 56, 67 years]) and 59 men with PAC (median age, 64 years [interquartile range, 59, 69 years]). Predefined MRI features, including intermediate T2 signal, well-defined margin, lobulation, and hypointense rim, were detected in a higher proportion of DACs than PACs (76% [45 of 59] vs 5% [three of 59]; P < .001). On consensus reading, the presence of three or more features demonstrated 76% sensitivity, 94% specificity, 94% positive predictive value [PPV], and 80% negative predictive value [NPV] for all DACs and 100% sensitivity, 95% specificity, 81% PPV, and 100% NPV for pure DACs. The DACs and PACs showed no difference in contrast enhancement (100% vs 100%; P >.99, median T2 signal intensity (254 vs 230; P = .99), or apparent diffusion coefficient (median, 677 10 -6 mm 2 /sec vs 685 10 -6 mm 2 /sec; P = .73). Conclusion The presence of intermediate T2 signal, well-defined margin, lobulation, and/or hypointense rim, together with restricted diffusion and contrast enhancement at multiparametric MRI of the prostate, suggests prostatic ductal adenocarcinoma rather than prostatic acinar adenocarcinoma. © RSNA, 2022 Online supplemental material is available for this article.

The Peutz-Jeghers Syndrome (PJS) is an autosomal dominant neoplastic syndrome defined by hamartomatous polyps through the gastrointestinal tract, development of characteristic mucocutaneous pigmentations, and an elevated lifetime cancer risk. The majority of cases are due to a mutation in the STK11 gene located at 19p13.3. The estimated incidence of PJS ranges from 1:50,000 to 1:200,000. PJS carries an elevated risk of malignancies including gastrointestinal, breast, lung, and genitourinary (GU) neoplasms. Patients with PJS are at a 15- to 18-fold increased malignancy risk relative to the general population. Radiologists have an integral role in the diagnosis of these patients. Various imaging modalities are used to screen for malignancies and complications associated with PJS. Awareness of various PJS imaging patterns, associated malignancies, and their complications is crucial for accurate imaging interpretation and patient management. In this manuscript, we provide a comprehensive overview of PJS, associated malignancies, and surveillance protocols.

Introduction: Magnetic resonance imaging (MRI) has played an increasingly major role in the evaluation of patients with prostate cancer, although prostate MRI presents several technical challenges. Newer techniques, such as deep learning (DL), have been applied to medical imaging, leading to improvements in image quality. Our goal is to evaluate the performance of a new deep learning-based reconstruction method, "DLR" in improving image quality and mitigating artifacts, which is now commercially available as AIR TM Recon DL (GE Healthcare, Waukesha, WI). We hypothesize that applying DLR to the T2WI images of the prostate provides improved image quality and reduced artifacts., Methods: This study included 31 patients with a history of prostate cancer that had a multiparametric MRI of the prostate with an endorectal coil (ERC) at 1.5 T or 3.0 T. Four series of T2-weighted images were generated in total: one set with the ERC signal turned on (ERC) and another set with the ERC signal turned off (Non-ERC). Each of these sets then reconstructed using two different reconstruction methods: conventional reconstruction (Conv) and DL Recon (DLR): ERC DLR , ERC Conv , Non-ERC DLR , and Non-ERC Conv . Three radiologists independently reviewed and scored the four sets of images for (i) image quality, (ii) artifacts, and (iii) visualization of anatomical landmarks and tumor., Results: The Non-ERC DLR scored as the best series for (i) overall image quality (p < 0.001), (ii) reduced artifacts (p < 0.001), and (iii) visualization of anatomical landmarks and tumor., Conclusion: Prostate imaging without the use of an endorectal coil could benefit from deep learning reconstruction as demonstrated with T2-weighted imaging MRI evaluations of the prostate.

Objective: Li-Fraumeni syndrome (LFS) is a rare autosomal-dominant inherited syndrome containing a germline mutation in the TP53 gene, which predisposes to oncogenesis. Leukemia and tumors of the brain, soft tissues, breasts, adrenal glands, and bone are the most common cancers associated with this syndrome. Patients with LFS are very susceptible to radiation, therefore the use of whole-body MRI is recommended for regular cancer screening. It is important to recognize the common tumors associated with LFS on MRI, and it is also important to be aware of the high rate of false-positive lesions., Conclusion: Whole-body MRI is useful for the detection of cancer in patients who come for regular screening; however, it is associated with pitfalls about which the radiologist must remain aware.

Objective: The aim of this study was to optimize chest port contrast injections using stepwise improvements., Methods: Ex vivo injections were tested. Two hundred scans using power port injections were then evaluated., Results: The highest flow rate was achieved using a 19G access needle, larger diameter tubing, and warmed contrast.The mean injection rates in baseline and postimprovement groups were 2.7 ± 0.4 and 4.8 ± 0.4 mL/s, respectively (P < .0001)., Conclusion: Component optimization of the port apparatus can maximize contrast flow rates.

The discrimination of mass-forming chronic pancreatitis (MFCP) from pancreatic ductal adenocarcinoma (PDAC) is a central diagnostic dilemma. It is important to differentiate these entities since they have markedly different prognoses and management. Importantly, the appearance of these two entities significantly overlaps on a variety of imaging modalities. However, there are imaging features that may be suggestive of one entity more than the other. MFCP and PDAC may show different enhancement patterns on perfusion computed tomography (CT) and/or dynamic contrast-enhanced MRI (DCE-MRI). The duct-penetrating sign on magnetic resonance cholangiopancreatography (MRCP) is more often associated with MFCP, whereas abrupt cutoff with upstream dilatation of the main pancreatic duct and the double-duct sign (obstruction/cutoff of both the common bile duct and pancreatic duct) are more often associated with PDAC. Nevertheless, tissue sampling is the most reliable method to differentiate between these entities and is currently generally necessary for management.