Uterine leiomyomas affect 20%-30% of women older than 35 years. Extrauterine leiomyomas are rarer, and they present a greater diagnostic challenge: These histologically benign tumors, which originate from smooth muscle cells, usually arise in the genitourinary tract (in the vulva, ovaries, urethra, and urinary bladder) but may arise in nearly any anatomic site. In addition, unusual growth patterns may be seen, including benign metastasizing leiomyoma, disseminated peritoneal leiomyomatosis, intravenous leiomyomatosis, parasitic leiomyoma, and retroperitoneal growth. In the presence of such a pattern, a synchronous uterine leiomyoma or a previous hysterectomy for removal of a primary uterine tumor may be indicative of the diagnosis. However, some extrauterine leiomyomas may mimic malignancies, and serious diagnostic errors may result. The most useful modalities for detecting extrauterine leiomyomas are ultrasonography, computed tomography, and magnetic resonance (MR) imaging. The superb contrast resolution and multiplanar capabilities of MR imaging make it particularly valuable for characterizing these tumors, which usually show low signal intensity similar to that of smooth muscle on T2-weighted images. The radiologist's recognition of this and other characteristic features may help steer the clinician toward timely, appropriate management and away from unnecessary, potentially harmful treatment.

The Liver Imaging Reporting and Data System (LI-RADS) uses an algorithm to assign categories that reflect the probability of hepatocellular carcinoma (HCC), non-HCC malignancy, or benignity. Unlike other imaging algorithms, LI-RADS utilizes ancillary features (AFs) to refine the final category. AFs in LI-RADS v2017 are divided into those favoring malignancy in general, those favoring HCC specifically, and those favoring benignity. Additionally, LI-RADS v2017 provides new rules regarding application of AFs. The purpose of this review is to discuss ancillary features included in LI-RADS v2017, the rationale for their use, potential pitfalls encountered in their interpretation, and tips on their application.

The Liver Imaging Reporting and Data System (LI-RADS) is an imaging-based diagnostic system applicable in patients at high risk of hepatocellular carcinoma (HCC). In LI-RADS, each liver observation is assigned a category that reflects probability of benignity, HCC, or other malignancy. Familiarity with the LI-RADS diagnostic algorithm is necessary to appropriately implement LI-RADS in clinical practice. This review discusses steps necessary for application of the LI-RADS algorithm and provides examples illustrating each step.

The atrioventricular (AV) node responds in a complex fashion to changes in activation rate. A variety of approaches have been used to explain these dynamic AV nodal responses, but none has been able to account fully for AV nodal behavior. Three specific rate-dependent properties of the AV node have been described: 1) time-dependent recovery after excitation, 2) an effect of short cycles to advance recovery ("facilitation"), and 3) a gradual slowing of conduction in response to sustained, high-frequency activation ("fatigue"). We hypothesized that a model incorporating quantitative descriptors of all three processes might be able to account for a wide variety of AV nodal behaviors. Quantitative descriptors of AV nodal recovery, facilitation, and fatigue were developed based on AV nodal conduction changes during selective pacing protocols in seven autonomically blocked dogs. These descriptors were incorporated into a set of mathematical equations that define AV nodal conduction of any beat based on activation history. The equations were then applied to predict pacing-induced Wenckebach periodicity in each dog. Experimental data were obtained after nine to 19 step decreases in atrial cycle length into the Wenckebach zone in each animal. Observed behaviors included complex patterns of block, a progressive increase in the level of block over 5 minutes of rapid pacing, and periods of alternating patterns of block. The model accurately predicted the onset of AV block at each cycle length, the relation between conduction ratio and cycle length as a function of time, and the changing patterns of Wenckebach periodicity during sustained atrial pacing. All three terms of the model equation (describing recovery, facilitation, and fatigue) were essential to account fully for the observed behaviors. Elimination of AV nodal fatigue from the model resulted in failure to account for time-dependent changes in Wenckebach patterns, whereas exclusion of facilitation led to consistent overestimation of the degree of AV block at each cycle length. We conclude that a mathematical model incorporating terms to describe recovery, facilitation, and fatigue accurately predicts a wide range of Wenckebach-type behavior and that complex conduction patterns of the AV node can be fully accounted for by simple functional AV nodal properties. (Circulation Research 1991;68:1280-1293 Preliminary results from this study have been presented in abstract form (JAm Coll Cardiol 1990;15:201A

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The manifestations of endometriosis commonly present a challenge to the gynecologist and radiologist. Familiarity with its varied presentations may allow accurate diagnosis.

Introduction: Preoperative prostate cancer stage predicts prognosis and affects treatment decisions. The purpose of this study was to estimate the sensitivity and specificity of surface coil magnetic resonance imaging (MRI) for prostate cancer stage using surgical pathologic data as the reference standard. Methods: High-risk patients (≥cT3 or PSA ≥20 ng/mL or Gleason ≥8) and selected intermediate-risk patients (clinically bulky disease on exam or biopsy, cT2b/c, or Gleason 7 with ≥3 of 5 biopsy cores positive in a lobe) routinely received a pelvic MRI at our institution. The images of identified patients were reviewed by one radiologist who was blinded to clinical information. The radiologist reported presence or absence of tumour within each lobe of the prostate. Extraprostatic extension (EPE), seminal vesicle (SV) invasion and pelvic lymph node (PLN) metastasis were also reported. Radiological findings were compared with prostatectomy pathology reports. Results: During the study period, about 320 radical prostatectomies were performed. Of these, 32 had a preoperative surface coil pelvic MRI adequate for analysis. Pathologically, 53 of 64 (82.8%) prostate lobes contained tumour, 17 (26.6%) lobes had associated EPE, 12 (18.8%) had SV involvement and 7 (10.9%) sets of PLNs contained cancer. Magnetic resonance imaging sensitivity and specificity were, respectively, 94.3% and 81.8% for tumour location, 82.4% and 87.2% for EPE, 83.3% and 92.3% for SV invasion and 71.4% and 94.7% for PLN involvement. Interpretation: Surface coil MRI accurately stages many prostate cancer patients with elevated risk of extraprostatic disease. This mode of imaging may be reasonable at centres that do not have endorectal coil MRI. RésuméIntroduction : Le stade du cancer de la prostate avant l'opération permet d'établir le pronostic et influe sur les décisions en ce qui concerne le traitement. Notre étude avait pour objectif d'évaluer la sensibilité et la spécificité de l'imagerie par résonance magnétique avec bobine de surface dans l'établissement du stade du cancer de la prostate en utilisant les données pathologiques liées à la chirurgie comme données de référence. Méthodologie : Les patients à risque élevé (tumeur ≥cT3 ou taux d'APS ≥20 ng/mL ou score de Gleason ≥ 8) et certains patients à risque intermédiaire (maladie volumineuse sur le plan clinique lors de l'examen ou à la biopsie, tumeur cT2b/c, ou score de Gleason de 7 avec au moins 3 carottes biopsiques sur 5 prélevées dans le même lobe qui soient positives) subissent un examen par IRM de façon systématique à notre établissement. Les images des patients inclus dans l'étude ont été examinées par un radiologiste à qui les données cliniques n'avaient pas été divulguées (examen à l'insu). Le radiologiste signalait la présence ou l'absence de tumeur dans chaque lobe prostatique. On a aussi signalé des cas d'extension extraprostatique, d'envahissement des vésicules séminales et de métastases touchant les ganglions lymphatiques pelviens. Les observations radiologiques ont été ...

Hepatocarcinogenesis is a multi-step process characterized by progressive cellular and molecular dedifferentiation of hepatocytes and culminating in the emergence of hepatocellular carcinoma (HCC). Knowledge of hepatocarcinogenesis is important because familiarity with the associated imaging features can lead to improved diagnosis of HCC at its early stages. The article reviews the alterations that accumulate leading to HCC result in abnormal imaging features, many of which are included in LI-RADS v2017 as major and ancillary features.