RESUMEN
Intrauterine devices (IUDs) are a commonly used form of long-acting reversible contraception, which either contain copper or levonorgestrel to prevent pregnancy. Although symptomatic patients with indwelling IUDs may first undergo ultrasound to assess for device malposition and complications, IUDs are commonly encountered on CT in patients undergoing evaluation for unrelated indications. Frequently, IUD malposition and complications may be asymptomatic or clinically unsuspected. For these reasons, it is important for the radiologist to carefully scrutinize the IUD on any study in which it is encountered. To do so, the radiologist must recognize that normally positioned IUDs are located centrally within the uterine cavity. IUDs are extremely effective in preventing pregnancy, though inadvertent pregnancy risk is higher with malpositioned IUDs. Presence of fibroids or Mullerian abnormalities may preclude proper IUD placement. Radiologists play an important role in identifying complications when they arise and special considerations when planning for an IUD placement. There is a wide range of IUD malposition, affecting IUDs differently depending on the type of IUD and its mechanism of action. IUD malposition is the most common complication, but embedment and/or partial perforation can and can lead to difficulty when removed. Retained IUD fragments can result in continued contraceptive effect. Perforated IUDs do not typically cause intraperitoneal imaging findings.
Asunto(s)
Dispositivos Intrauterinos , Leiomioma , Embarazo , Femenino , Humanos , Dispositivos Intrauterinos/efectos adversos , Útero , Ultrasonografía , Tomografía Computarizada por Rayos XRESUMEN
Small solid renal masses (SRMs) are frequently detected at imaging. Nearly 20% are benign, making careful evaluation with MRI an important consideration before deciding on management. Clear cell renal cell carcinoma (ccRCC) is the most common renal cell carcinoma subtype with potentially aggressive behavior. Thus, confident identification of ccRCC imaging features is a critical task for the radiologist. Imaging features distinguishing ccRCC from other benign and malignant renal masses are based on major features (T2 signal intensity, corticomedullary phase enhancement, and the presence of microscopic fat) and ancillary features (segmental enhancement inversion, arterial-to-delayed enhancement ratio, and diffusion restriction). The clear cell likelihood score (ccLS) system was recently devised to provide a standardized framework for categorizing SRMs, offering a Likert score of the likelihood of ccRCC ranging from 1 (very unlikely) to 5 (very likely). Alternative diagnoses based on imaging appearance are also suggested by the algorithm. Furthermore, the ccLS system aims to stratify which patients may or may not benefit from biopsy. The authors use case examples to guide the reader through the evaluation of major and ancillary MRI features of the ccLS algorithm for assigning a likelihood score to an SRM. The authors also discuss patient selection, imaging parameters, pitfalls, and areas for future development. The goal is for radiologists to be better equipped to guide management and improve shared decision making between the patient and treating physician. © RSNA, 2023 Quiz questions for this article are available in the supplemental material. See the invited commentary by Pedrosa in this issue.
Asunto(s)
Carcinoma de Células Renales , Neoplasias Renales , Humanos , Carcinoma de Células Renales/diagnóstico , Neoplasias Renales/patología , Imagen por Resonancia Magnética/métodos , Diagnóstico Diferencial , Estudios RetrospectivosRESUMEN
Urinary bladder masses are commonly encountered in clinical practice, with 95% arising from the epithelial layer and rarer tumors arising from the lamina propria, muscularis propria, serosa, and adventitia. The extent of neoplastic invasion into these bladder layers is assessed with multimodality imaging, and the MRI-based Vesical Imaging Reporting and Data System is increasingly used to aid tumor staging. Given the multiple layers and cell lineages, a diverse array of pathologic entities can arise from the urinary bladder, and distinguishing among benign, malignant, and nonneoplastic entities is not reliably feasible in most cases. Pathologic assessment remains the standard of care for classification of bladder masses. Although urothelial carcinoma accounts for most urinary bladder malignancies in the United States, several histopathologic entities exist, including squamous cell carcinoma, adenocarcinoma, melanoma, and neuroendocrine tumors. Furthermore, there are variant histopathologic subtypes of urothelial carcinoma (eg, the plasmacytoid variant), which are often aggressive. Atypical benign bladder masses are diverse and can have inflammatory or iatrogenic causes and mimic malignancy. © RSNA, 2022 Online supplemental material is available for this article.
Asunto(s)
Carcinoma de Células Transicionales , Anomalías del Sistema Digestivo , Enfermedades de la Vejiga Urinaria , Neoplasias de la Vejiga Urinaria , Humanos , Carcinoma de Células Transicionales/patología , Neoplasias de la Vejiga Urinaria/diagnóstico por imagen , Neoplasias de la Vejiga Urinaria/patología , Vejiga Urinaria/diagnóstico por imagen , Estadificación de NeoplasiasRESUMEN
The heterogeneity in the pathological and clinical manifestations of ovarian cancer is a major hurdle impeding early and accurate diagnosis. A host of imaging modalities, including Doppler ultrasound, MRI, and CT, have been investigated to improve the assessment of ovarian lesions. We hypothesized that pathologic conditions might affect the ovarian vasculature and that these changes might be detectable by optical-resolution photoacoustic microscopy (OR-PAM). In our previous work, we developed a benchtop OR-PAM and demonstrated it on a limited set of ovarian and fallopian tube specimens. In this study, we collected data from over 50 patients, supporting a more robust statistical analysis. We then developed an efficient custom analysis pipeline for characterizing the vascular features of the samples, including the mean vessel diameter, vascular density, global vascular directionality, local vascular definition, and local vascular tortuosity/branchedness. Phantom studies using carbon fibers showed that our algorithm was accurate within an acceptable error range. Between normal ovaries and normal fallopian tubes, we observed significant differences in five of six extracted vascular features. Further, we showed that distinct subsets of vascular features could distinguish normal ovaries from cystic, fibrous, and malignant ovarian lesions. In addition, a statistically significant difference was found in the mean vascular tortuosity/branchedness values of normal and abnormal tubes. The findings support the proposition that OR-PAM can help distinguish the severity of tubal and ovarian pathologies.