European Society of Urogenital Radiology (ESUR) Guidelines: MR Imaging of Leiomyomas

Development and validation of a deep learning-based method for automatic measurement of uterus, fibroid, and ablated volume in MRI after MR-HIFU treatment of uterine fibroids

INTRODUCTION

The non-perfused volume divided by total fibroid load (NPV/TFL) is a predictive outcome parameter for MRI-guided high-intensity focused ultrasound (MR-HIFU) treatments of uterine fibroids, which is related to long-term symptom relief. In current clinical practice, the MR-HIFU outcome parameters are typically determined by visual inspection, so an automated computer-aided method could facilitate objective outcome quantification. The objective of this study was to develop and evaluate a deep learning-based segmentation algorithm for volume measurements of the uterus, uterine fibroids, and NPVs in MRI in order to automatically quantify the NPV/TFL.

MATERIALS AND METHODS

A segmentation pipeline was developed and evaluated using expert manual segmentations of MRI scans of 115 uterine fibroid patients, screened for and/or undergoing MR-HIFU treatment. The pipeline contained three separate neural networks, one per target structure. The first step in the pipeline was uterus segmentation from contrast-enhanced (CE)-T1w scans. This segmentation was subsequently used to remove non-uterus background tissue for NPV and fibroid segmentation. In the following step, NPVs were segmented from uterus-only CE-T1w scans. Finally, fibroids were segmented from uterus-only T2w scans. The segmentations were used to calculate the volume for each structure. Reliability and agreement between manual and automatic segmentations, volumes, and NPV/TFLs were assessed.

RESULTS

For treatment scans, the Dice similarity coefficients (DSC) between the manually and automatically obtained segmentations were 0.90 (uterus), 0.84 (NPV) and 0.74 (fibroid). Intraclass correlation coefficients (ICC) were 1.00 [0.99, 1.00] (uterus), 0.99 [0.98, 1.00] (NPV) and 0.98 [0.95, 0.99] (fibroid) between manually and automatically derived volumes. For manually and automatically derived NPV/TFLs, the mean difference was 5% [-41%, 51%] (ICC: 0.66 [0.32, 0.85]).

CONCLUSION

The algorithm presented in this study automatically calculates uterus volume, fibroid load, and NPVs, which could lead to more objective outcome quantification after MR-HIFU treatments of uterine fibroids in comparison to visual inspection. When robustness has been ascertained in a future study, this tool may eventually be employed in clinical practice to automatically measure the NPV/TFL after MR-HIFU procedures of uterine fibroids.

Recent trends in AI applications for pelvic MRI: a comprehensive review

Magnetic resonance imaging (MRI) is an essential tool for evaluating pelvic disorders affecting the prostate, bladder, uterus, ovaries, and/or rectum. Since the diagnostic pathway of pelvic MRI can involve various complex procedures depending on the affected organ, the Reporting and Data System (RADS) is used to standardize image acquisition and interpretation. Artificial intelligence (AI), which encompasses machine learning and deep learning algorithms, has been integrated into both pelvic MRI and the RADS, particularly for prostate MRI. This review outlines recent developments in the use of AI in various stages of the pelvic MRI diagnostic pathway, including image acquisition, image reconstruction, organ and lesion segmentation, lesion detection and classification, and risk stratification, with special emphasis on recent trends in multi-center studies, which can help to improve the generalizability of AI.

Imaging in pelvic exenteration-a multidisciplinary practice guide from the ESGAR-SAR-ESUR-PelvEx collaborative group

Pelvic exenteration (PE) is a radical surgical approach designed for the curative treatment of advanced pelvic malignancies, requiring en-bloc resection of multiple pelvic organs. While the procedure is radical, it has shown promise in enhancing long-term survival and is now comparable in surgical mortality to elective resections for primary pelvic cancers. Imaging plays a crucial role in preoperative planning, with MRI, CT, and PET/CT being pivotal in assessing the extent of cancer and formulating a surgical roadmap. This paper presents clinical practice guidelines for imaging in the context of PE, developed jointly by ESGAR, SAR, ESUR, and the PelvEx Collaborative. These guidelines aim to standardize imaging protocols and reporting to improve the preoperative assessment and facilitate decision-making in the multidisciplinary treatment of pelvic cancers. Our recommendations underscore the importance of a multidisciplinary approach and the need for clear and precise imaging reports to optimize patient care. CLINICAL RELEVANCE STATEMENT: Our recommendations underscore the importance of a multidisciplinary approach and the need for clear and precise imaging reports to optimize patient care. KEY POINTS: MRI is mandatory for local staging in pelvic exenteration. Structured reporting (using the template provided in this guide) is recommended. Multidisciplinary review of imaging is critical for surgical planning.

Validating the diagnostic accuracy of an MRI-based scoring system for differentiating benign uterine leiomyomas from leiomyosarcomas

OBJECTIVE

Uterine leiomyomas are the most common benign uterine tumors. They are difficult to distinguish from their malignant counterparts-smooth muscle tumors of unknown malignant potential (STUMP) and leiomyosarcoma. The purpose of this study is to propose and validate the diagnostic accuracy of the MRI-based Oman-Canada Scoring System of Myometrial Masses (OCSSMM) to differentiate uterine leiomyomas from STUMP/leiomyosarcomas.

METHODS

This is a retrospective study performed at two tertiary care centers. All patients with a pathology-proven uterine mass who underwent pre-operative pelvic MRI between January 2010 and January 2020 were included. Using a 1.5T MRI machine, sequences included were axial/coronal/sagittal T2 and T1 weighted imaging, axial diffusion weighted and apparent diffusion coefficient map, and axial or sagittal dynamic contrast-enhanced sequences. A scoring system was designed based on previously published worrisome MRI features for uterine leiomyosarcoma. Each feature was allocated a score from 0 to 2 according to the strength of association with malignancy. Subsequently, the MR images were blindly and independently reviewed by a fellowship-trained radiologist and a clinical fellow/senior resident. Each uterine mass was scored according to their imaging features. The scores were divided into five categories according to the sum of scores. Category III and above was considered positive for leiomyosarcoma/STUMP. Sensitivity, specificity, and positive and negative predictive values were calculated.

RESULTS

A total of 244 women were included (age range 20-74 years, mean 40). Of these, 218 patients had benign leiomyoma, 13 had STUMP, and 13 had leiomyosarcoma. The sensitivity and specificity of the scoring system were 92.3% and 64.7%, respectively. The negative predictive value was 98.6%. No leiomyosarcoma was missed using this scoring system. The presence of non-cystic T2 hyperintensity or diffusion restriction in a uterine mass were the most sensitive signs of a leiomyosarcoma/STUMP.

CONCLUSION

The proposed multi-parametric MRI scoring system may be useful in differentiating benign uterine leiomyomas from leiomyosarcomas/STUMP.

Diffuse Uterine Leiomyomatosis: A Rare Case of Symmetrically Enlarged Uterus

A rarely reported case of diffuse uterine leiomyomatosis is observed in a 43-year-old nulliparous female presenting with abdominal distension and primary infertility. Magnetic resonance imaging (MRI) of the abdomen and pelvis revealed an enlarged uterus with multiple well-defined lobulated lesions of varying sizes, causing symmetrical uterine enlargement and displacing the adjacent bowel loops superolaterally. The compression of the bladder and inferior vena cava was seen without the involvement of the adjacent structures. The diagnosis of diffuse leiomyomatosis of the uterus was confirmed through histopathological examination of the biopsy.

Deep learning-accelerated T2-weighted imaging versus conventional T2-weighted imaging in the female pelvic cavity: image quality and diagnostic performance

BACKGROUND

The deep learning (DL)-based reconstruction algorithm reduces noise in magnetic resonance imaging (MRI), thereby enabling faster MRI acquisition.

PURPOSE

To compare the image quality and diagnostic performance of conventional turbo spin-echo (TSE) T2-weighted (T2W) imaging with DL-accelerated sagittal T2W imaging in the female pelvic cavity.

METHODS

This study evaluated 149 consecutive female pelvic MRI examinations, including conventional T2W imaging with TSE (acquisition time = 2:59) and DL-accelerated T2W imaging with breath hold (DL-BH) (1:05 [0:14 × 3 breath-holds]) in the sagittal plane. In 294 randomly ordered sagittal T2W images, two radiologists independently assessed image quality (sharpness, subjective noise, artifacts, and overall image quality), made a diagnosis for uterine leiomyomas, and scored diagnostic confidence. For the uterus and piriformis muscle, quantitative imaging analysis was also performed. Wilcoxon signed rank tests were used to compare the two sets of T2W images.

RESULTS

In the qualitative analysis, DL-BH showed similar or significantly higher scores for all features than conventional T2W imaging (P <0.05). In the quantitative analysis, the noise in the uterus was lower in DL-BH, but the noise in the muscle was lower in conventional T2W imaging. In the uterus and muscle, the signal-to-noise ratio was significantly lower in DL-BH than in conventional T2W imaging (P <0.001). The diagnostic performance of the two sets of T2W images was not different for uterine leiomyoma.

CONCLUSIONS

DL-accelerated sagittal T2W imaging obtained with three breath-holds demonstrated superior or comparable image quality to conventional T2W imaging with no significant difference in diagnostic performance for uterine leiomyomas.

Abnormal Uterine Bleeding: A Pictorial Review on Differential Diagnosis and Not-So-Common Cases of Interventional Radiology Management

Abnormal uterine bleeding (AUB) poses a multifaceted challenge in women's health, necessitating an integrated approach that addresses its diverse etiologies and clinical presentations. The International Federation of Gynecology and Obstetrics PALM-COEIN classification system provides a systematic approach to the diagnosis of AUB in non-pregnant women, based on clinical and imaging-based categorization of causes into structural (Polyps, Adenomyosis, Leiomyomas and Malignancy; PALM), and non-structural causes (Coagulopathies, Ovulatory disorders, primary Endometrial disorders, Iatrogenic and Not otherwise classified; COEIN). On the other hand, placental disorders, uterine rupture, ectopic pregnancy and retained products of conceptions are the main causes of uterine bleeding during pregnancy and in the peripartum period. Ultrasound is usually the first-line imaging technique for the differential diagnosis of causes of AUB. Computed Tomography may be useful if ultrasound findings are unclear, especially in emergency settings. Magnetic resonance imaging, when indicated, is an excellent second-line diagnostic tool for a better non-invasive characterization of the underlying cause of AUB. This pictorial review aims to illustrate the main causes of AUB from the point of view of diagnostic imaging and to show not-so-common cases that can be treated by means of interventional radiology.

Smooth muscle tumours of the uterus: MR imaging malignant predictive features-a 12-year analysis in a referral hospital in Portugal

PURPOSE

To evaluate the magnetic resonance imaging (MRI) features that may help distinguish leiomyosarcomas from atypical leiomyomas (those presenting hyperintensity on T2-W images equal or superior to 50% compared to the myometrium).

MATERIALS AND METHODS

The authors conducted a retrospective single-centre study that included a total of 57 women diagnosed with smooth muscle tumour of the uterus, who were evaluated with pelvic MRI, between January 2009 and March 2020. All cases had a histologically proven diagnosis (31 Atypical Leiomyomas-ALM; 26 Leiomyosarcomas-LMS). The MRI features evaluated in this study included: age at presentation, dimension, contours, intra-tumoral haemorrhagic areas, T2-WI heterogeneity, T2-WI dark areas, flow voids, cyst areas, necrosis, restriction on diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) values, signal intensity and heterogeneity after contrast administration in T1-WI, presence and location of unenhanced areas. The association between the MRI characteristics and the histological subtype was evaluated using Chi-Square and ANOVA tests.

RESULTS

The MRI parameters that showed a statistically significance correlation with malignant histology and thus most strongly associated with LMS were found to be: irregular contours (p < 0.001), intra-tumoral haemorrhagic areas (p = 0.028), T2-WI dark areas (p = 0.016), high signal intensity after contrast administration (p = 0.005), necrosis (p = 0.001), central location for unenhanced areas (p = 0.026), and ADC value lower than 0.88 × 10-3 mm2/s (p = 0.002).

CONCLUSION

With our work, we demonstrate the presence of seven MRI features that are statistically significant in differentiating between LMS and ALM.

AI-Supported Autonomous Uterus Reconstructions: First Application in MRI Using 3D SPACE with Iterative Denoising

RATIONALE AND OBJECTIVES

T2-weighted imaging in at least two orthogonal planes is recommended for assessment of the uterus. To determine whether a convolutional neural network-based algorithm could be used for the re-constructions of uterus axes derived from a 3D SPACE with iterative denoising.

MATERIALS AND METHODS

50 patients aged 18-81 (mean: 42) years who underwent an MRI examination of the uterus participated voluntarily in this prospective study after informed consent. In addition to a standard MRI pelvis protocol, a 3D SPACE research application sequence was acquired in sagittal orientation. Reconstructions for both the cervix and the cavum in the short and long axes were performed by a research trainee (T), an experienced radiologist (E), and the prototype software (P). In the next step, the reconstructions were evaluated anonymously by two experienced readers according to 5-point-Likert-Scales. In addition, the length of the cervical canal, the length of the cavum and the distance between the tube angles were measured on all reconstructions. Interobserver agreement was assessed for all ratings.

RESULTS

For all axes, significant differences were found between the scores of the reconstructions by research T, E and P. P received higher scores and was preferred significantly more often with the exception of the comparison of the reconstruction Cervix short of E (Cervix short: P vs. T: p = 0.02; P vs. E: p = 0.26; Cervix long: P vs. T: p = 0.01; P vs. E: p < 0.01; Cavum short: P vs. T: p = 0.01; P vs. E: p = 0.02; Cavum long: P vs. T: p < 0.01; P vs. E: p < 0.01). Regarding the measured diameters, (length of cervical canal/cavum/distance between tube angles) significantly larger diameters were recorded for P compared to E and T (Cervix long (mm): T: 25.43; E: 25.65; P: 26.65; Cavum short (mm): T: 26.24; E: 25.04; P: 27.33; Cavum long (mm): T: 31.98; E: 32.91; P: 34.41; P vs. T: p < 0.01); P vs. E: p = 0.04). Moderate to substantial agreement was found between Reader 1 and Reader 2 (range: 0.39-0.67).

CONCLUSION

P was able to reconstruct the axes at least as well as or better than E and T. P could thereby lead to workflow facilitation and enable more efficient reporting of uterine MRI.

Impact of guideline adherence and expert center referral on the early management and outcomes of uterine sarcoma patients: A retrospective analysis from the French NETSARC network

OBJECTIVE

Uterine sarcomas are rare tumors with a poor prognosis. Their diagnosis is often incidental, following surgery. Our goal was to examine the early management strategies for uterine sarcomas, and to assess the impact of guideline adherence and expert center referral on both the management approaches and the clinical outcomes in patients with uterine sarcomas.

METHODS

We retrospectively analyzed medical records from patients with uterine sarcoma referred to the Institut Curie and registered in the database of the French NETSARC network.

RESULTS

In total, 100 patients, with a median age of 54 years, were included in the analyses. On MRI scans (n = 36), all patients had at least two signs suggestive of malignancy, and 77.8 % had four or more signs. No preoperative biopsy was performed in 65.6 % of cases. Only 14.1 % of patients underwent initial surgery at an expert center. Surgery performed outside the network was significantly associated with morcellation (32.9 % vs. 0 %; p = 0.036), fewer negative margins (R0 margins 52.4 % vs. 100 %; p = 0.006), and poor adherence to surgical guidelines (28.3 vs. 72.7 %; p = 0.013). Multivariate analysis showed that non-adherence to surgical recommendations was not significantly associated with relapse-free survival (HR = 0.54; 95 % CI [0.21-1.38]), but was an independent predictor of poor overall survival (HR = 0.12; 95 % CI [0.03-0.52]; p = 0.005).

CONCLUSION

Despite a high frequency of suspicious clinical and radiological signs, a large proportion of women undergoing sarcoma surgery are treated outside of expert networks. We provide guidelines, integrating the clinical context and radiological signs to encourage early referral to reference centers for sarcoma.

Clinical Outcomes of Conservative Surgery for Diffuse Uterine Leiomyomatosis: Preliminary Experience of 17 Cases in a Single Center

This study aimed to introduce the clinical outcomes of conservative surgery for diffuse uterine leiomyomatosis, which also included the specialized surgical technique. All patients with diffuse uterine leiomyomatosis underwent conservative surgery such as transient occlusion of the uterine arteries (TOUA) adenomyomectomy. All 17 surgeries were performed by a single surgeon between 2018 and 2021. The mean age of the 17 patients was 36.12 years old (range 29-48, SD = 5.4). Fourteen of the 17 patients received a previous myomectomy via a laparotomic (6, 35.3%), laparoscopic (6, 35.3%), or hysteroscopic (2, 11.8%) approach. The major symptom was menorrhagia (94.1%); the mean operation time was 97.06 min (70-160, SD = 22.71), and the mean estimated blood loss was 283.53 mL (20-1000, SD = 273.72). The mean hemoglobin level one day after the operation was 9.64 g/dL (7.2-13.1, SD = 1.85). The mean hospital stay was 6.47 days (6-8, SD = 0.62). The mean follow-up duration was 116.41 weeks (32-216, SD = 50.88). The recurrence rate was 5/17 (29.4%), and the recurrence-free interval was 50.6 weeks (27-87, SD = 23.71). In patients with diffuse uterine leiomyomatosis, who want fertility preservation and relief of disease-related symptoms, conservative surgery such as TOUA adenomyomectomy could be a good option to preserve the uterus. However, further studies are required to assess fertility outcomes with a long-term follow-up.

Hyaline and Cystic Degeneration of Uterine Leiomyomas: CT and MR Imaging with Histopathological Sample Analyses

Leiomyomas are the most common solid benign uterine neoplasms; they are usually asymptomatic and are identified incidentally. Yet, responsive to stimulation by estrogens, leiomyomas may expand, potentially outgrowing their blood supply to undergo hemorrhage, fibrosis, calcification, and atrophy. These pathologic mechanisms commonly lead to leiomyomas degeneration, i.e., red, hyaline, cystic, or myxoid. Magnetic resonance (MR) imaging is the most accurate imaging technique for the characterization of leiomyomas. In cases of degeneration, variable features on T2-weighted and contrast-enhanced images can be found. With no recent radiologic pathologic correlation literature available on this matter, herewith, we provide computed tomography (CT)/MR imaging along with histopathological specimens of two young women who were diagnosed with hyaline or hyaline and cyst degeneration of uterine leiomyomas at our university hospital. We report on the imaging features of uterine leiomyomas using CT and MR imaging and discuss the available literature on imaging signs that may be suggestive of hyaline or cyst degeneration using either of the imaging examination methods.

Gynaecological Causes of Acute Pelvic Pain: Common and Not-So-Common Imaging Findings

In female patients, acute pelvic pain can be caused by gynaecological, gastrointestinal, and urinary tract pathologies. Due to the variety of diagnostic possibilities, the correct assessment of these patients may be challenging. The most frequent gynaecological causes of acute pelvic pain in non-pregnant women are pelvic inflammatory disease, ruptured ovarian cysts, ovarian torsion, and degeneration or torsion of uterine leiomyomas. On the other hand, spontaneous abortion, ectopic pregnancy, and placental disorders are the most frequent gynaecological entities to cause acute pelvic pain in pregnant patients. Ultrasound (US) is usually the first-line diagnostic technique because of its sensitivity across most common aetiologies and its lack of radiation exposure. Computed tomography (CT) may be performed if ultrasound findings are equivocal or if a gynaecologic disease is not initially suspected. Magnetic resonance imaging (MRI) is an extremely useful second-line technique for further characterisation after US or CT. This pictorial review aims to review the spectrum of gynaecological entities that may manifest as acute pelvic pain in the emergency department and to describe the imaging findings of these gynaecological conditions obtained with different imaging techniques.

Adenomyosis at a Glance: An Integrated Review of Transvaginal Ultrasound and MR Imaging Findings

Adenomyosis is a benign uterine disorder increasingly recognized in premenopausal women. Given its significant clinical burden, an accurate noninvasive diagnosis is paramount. Both transvaginal ultrasound (TVUS) and magnetic resonance (MR) provide an adequate assessment of adenomyosis, the former being recommended for first-line imaging evaluation and the latter being mainly used as a problem-solving technique. In this article, the authors review the TVUS and MR imaging findings of adenomyosis while referring to their histopathological background. Whereas direct signs correlate directly to ectopic endometrial tissue and are highly specific to adenomyosis, indirect signs result from myometrial hypertrophy and increase diagnostic sensitivity. Potential pitfalls, differential diagnoses, and frequently associated estrogen-dependent conditions are also discussed.

Quantitative MR texture analysis for the differentiation of uterine smooth muscle tumors with high signal intensity on T2-weighted imaging

The purpose of this study was to distinguish leiomyosarcomas/smooth muscle tumors of uncertain malignant potential (STUMP) from leiomyomas with high signal intensity (SI) on T2-weighted imaging (T2WI) using quantitative MR texture analysis combined with patient characteristics and visual assessment. Thirty-one leiomyomas, 2 STUMPs, and 6 leiomyosarcomas showing high SI on T2WI were included. First, we searched for differences in patient characteristics and visual assessment between leiomyomas and leiomyosarcomas/STUMPs. We also compared the MR texture on T2WI and the apparent diffusion coefficient (ADC) to identify differences between leiomyomas and leiomyosarcomas/STUMPs. In the univariate analysis, significant differences between leiomyomas and leiomyosarcomas/STUMPs were observed in age, menopausal status, margin, hemorrhage, long diameter, T2-variance, T2-volume, ADC-variance, ADC-entropy, ADC-uniformity, ADC-90th and 95th percentile values, and ADC-volume (P < .05, respectively). There were significantly more postmenopausal patients with leiomyosarcomas/STUMPs than with leiomyomas, and leiomyosarcomas/STUMPs had more irregular margins, more frequent presence of hemorrhage and exhibited larger tumor diameters, T2-volume, T2-variance, ADC-volume, ADC-variance, ADC-entropy, and higher ADC-90th and 95th percentile values but lower ADC-uniformity. Multivariate analyses revealed that the independent differentiators were menopausal status, hemorrhage and ADC-entropy (P < .05, respectively). The area under the curve obtained by combining the 3 items was 0.980. The best cutoff value for ADC-entropy was 9.625 (sensitivity: 100%, specificity: 58%). The combination of menopausal status, hemorrhage, and ADC-entropy can help accurately distinguish leiomyosarcomas/STUMPs from leiomyomas with high SI on T2WI; however, external validation in a larger population is required because of the small sample size of our study.

MR Imaging of Gynecologic Tumors: Pearls, Pitfalls, and Tumor Mimics

MR imaging is the modality of choice for the pre-treatment evaluation of patients with gynecologic malignancies, given its excellent soft tissue contrast and multi-planar capability. However, it is not without pitfalls. Challenges can be encountered in the assessment of the infiltration of myometrium, vagina, cervical stroma, and parametria, which are crucial prognostic factors for endometrial and cervical cancers. Other challenges can be encountered in the distinction between solid and non-solid tissue and in the identification of peritoneal carcinomatosis for the sonographically indeterminate adnexal mass.

Uterine mesenchymal tumors: development and preliminary results of a magnetic resonance imaging (MRI) diagnostic algorithm

PURPOSE

The aim of our study is to propose a diagnostic algorithm to guide MRI findings interpretation and malignancy risk stratification of uterine mesenchymal masses with a multiparametric step-by-step approach.

METHODS

A non-interventional retrospective multicenter study was performed: Preoperative MRI of 54 uterine masses was retrospectively evaluated. Firstly, the performance of MRI with monoparametric and multiparametric approach was assessed. Reference standard for final diagnosis was surgical pathologic result (n = 53 patients) or at least 1-year MR imaging follow-up (n = 1 patient). Subsequently, a diagnostic algorithm was developed for MR interpretation, resulting in a Likert score from 1 to 5 predicting risk of malignancy of the uterine lesion. The accuracy and reproducibility of the MRI scoring system were then tested: 26 preoperative pelvic MRI were double-blind evaluated by a senior (SR) and junior radiologist (JR). Diagnostic performances and the agreement between the two readers with and without the application of the proposed algorithm were compared, using histological results as standard reference.

RESULTS

Multiparametric approach showed the best diagnostic performance in terms of accuracy (94.44%,) and specificity (97.56%). DWI was confirmed as the most sensible parameter with a relative high specificity: low ADC values (mean 0.66) significantly correlated to uterine sarcomas diagnosis (p < 0.01). Proposed algorithm allowed to improve both JR and SR performance (algorithm-aided accuracy 88.46% and 96%, respectively) and determined a significant increase in inter-observer agreement, helping even the less-experienced radiologist in this difficult differential diagnosis.

CONCLUSIONS

Uterine leiomyomas and sarcomas often show an overlap of clinical and imaging features. The application of a diagnostic algorithm can help radiologists to standardize their approach to a complex myometrial mass and to easily identify suspicious MRI features favoring malignancy.

Smooth Muscle Tumors of the Uterus at MRI: Focus on Leiomyomas and FIGO Classification

Leiomyomas are smooth muscle tumors of the uterus and are the most common uterine neoplasm. Although leiomyomas are usually asymptomatic, they can manifest with symptoms such as pain or uterine bleeding. Leiomyomas are classified on the basis of their anatomic location and morphology. Localization of leiomyomas relative to the endometrium, myometrium, and uterine serosa with use of the International Federation of Gynecology and Obstetrics (FIGO) classification system is helpful for guiding management in symptomatic patients. The FIGO system is a practical and universally accepted approach for classifying leiomyomas to guide radiologists and clinicians in deciding management. The MRI appearance of conventional leiomyomas is related to their tissue contents of smooth muscle and fibrous tissue and is well established. The MRI features of some leiomyoma subtypes and forms of degeneration also have been described. Other smooth muscle tumors of the uterus recognized in the 2020 World Health Organization classification system include intravenous leiomyomatosis, smooth muscle tumors of uncertain malignant potential, and metastasizing leiomyoma. At the far end of the spectrum are leiomyosarcomas, which are frankly malignant and therefore must be managed accordingly. Although MRI features that suggest a diagnosis of leiomyosarcoma have been proposed, these features overlap with those of some leiomyoma subtypes and degeneration. ^© RSNA, 2023 See the invited commentary by Fennessy and Gargiulo in this issue. Online supplemental material and the slide presentation from the RSNA Annual Meeting are available for this article. Quiz questions for this article are available through the Online Learning Center.

Clinical Impact of Deep Learning Reconstruction in MRI

Deep learning has been recognized as a paradigm-shifting tool in radiology. Deep learning reconstruction (DLR) has recently emerged as a technology used in the image reconstruction process of MRI, which is an essential procedure in generating MR images. Denoising, which is the first DLR application to be realized in commercial MRI scanners, improves signal-to-noise ratio. When applied to lower magnetic field-strength scanners, the signal-to-noise ratio can be increased without extending the imaging time, and image quality is comparable to that of higher-field-strength scanners. Shorter imaging times decrease patient discomfort and reduce MRI scanner running costs. The incorporation of DLR into accelerated acquisition imaging techniques, such as parallel imaging or compressed sensing, shortens the reconstruction time. DLR is based on supervised learning using convolutional layers and is divided into the following three categories: image domain, k-space learning, and direct mapping types. Various studies have reported other derivatives of DLR, and several have shown the feasibility of DLR in clinical practice. Although DLR efficiently reduces Gaussian noise from MR images, denoising makes image artifacts more prominent, and a solution to this problem is desired. Depending on the training of the convolutional neural network, DLR may change the imaging features of lesions and obscure small lesions. Therefore, radiologists may need to adopt the habit of questioning whether any information has been lost on images that appear clean. ^©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Uterine sarcomas: clinical practice guidelines for diagnosis, treatment, and follow-up, by Spanish group for research on sarcomas (GEIS)

Uterine sarcomas are very infrequent and heterogeneous entities. Due to its rarity, pathological diagnosis, surgical management, and systemic treatment are challenging. Treatment decision process in these tumors should be taken in a multidisciplinary tumor board. Available evidence is low and, in many cases, based on case series or clinical trials in which these tumors have been included with other soft tissue sarcoma. In these guidelines, we have tried to summarize the most relevant evidence in the diagnosis, staging, pathological disparities, surgical management, systemic treatment, and follow-up of uterine sarcomas.

Use of Non-Contrast-Enhanced MR Angiography to Assess Recanalization after Uterine Artery Embolization

The purpose of this study was to examine the use of non-contrast-enhanced MR angiography (MRA) for assessing recanalization of uterine arteries (UAs) after uterine artery embolization (UAE) for symptomatic fibroids. Pre-procedural and follow-up unenhanced MRA images of 30 patients were reviewed, and the extent to which the UAs could be visualized was classified on a 4-point scale. An increase in the score between consecutive time points indicates that a previously inconspicuous segment of the UA became visible on follow-up images. Patients were divided into two groups according to the presence (or absence) of recanalization. The median UA visualization score at each follow-up was significantly lower than that at baseline (p < 0.01), but there was no significant difference between the scores of the follow-up images. Recanalization was detected in 63% (19/30) of patients. In these patients, the mean decrease in uterine and largest fibroid volume at 12 months after UAE was inferior to the mean decrease in patients for whom recanalization was not detected. Based on MRA assessment, recanalization after UAE occurred in 63% of patients but did not compromise the reduction in uterine and dominant fibroid volumes within 12 months after UAE.

An update on uterine artery embolization for uterine leiomyomata and adenomyosis of the uterus

Uterine artery embolization (UAE) is an established technique to treat benign diseases of the uterus such as uterine leiomyomata (fibroids) and adenomyosis. This article reviews the use of UAE in these conditions and summarizes the evidence regarding safety and efficacy of the technique based on the current literature.

MRI Evaluation of Uterine Masses for Risk of Leiomyosarcoma: A Consensus Statement

Laparoscopic myomectomy, a common gynecologic operation in premenopausal women, has become heavily regulated since 2014 following the dissemination of unsuspected uterine leiomyosarcoma (LMS) throughout the pelvis of a physician treated for symptomatic leiomyoma. Research since that time suggests a higher prevalence than previously suspected of uterine LMS in resected masses presumed to represent leiomyoma, as high as one in 770 women (0.13%). Though rare, the dissemination of an aggressive malignant neoplasm due to noncontained electromechanical morcellation in laparoscopic myomectomy is a devastating outcome. Gynecologic surgeons' desire for an evidence-based, noninvasive evaluation for LMS is driven by a clear need to avoid such harms while maintaining the availability of minimally invasive surgery for symptomatic leiomyoma. Laparoscopic gynecologists could rely upon the distinction of higher-risk uterine masses preoperatively to plan oncologic surgery (ie, potential hysterectomy) for patients with elevated risk for LMS and, conversely, to safely offer women with no or minimal indicators of elevated risk the fertility-preserving laparoscopic myomectomy. MRI evaluation for LMS may potentially serve this purpose in symptomatic women with leiomyomas. This evidence review and consensus statement defines imaging and disease-related terms to allow more uniform and reliable interpretation and identifies the highest priorities for future research on LMS evaluation.

Recurrence risk stratification for locally advanced cervical cancer using multi-modality transformer network

Objectives

Recurrence risk evaluation is clinically significant for patients with locally advanced cervical cancer (LACC). We investigated the ability of transformer network in recurrence risk stratification of LACC based on computed tomography (CT) and magnetic resonance (MR) images.

Methods

A total of 104 patients with pathologically diagnosed LACC between July 2017 and December 2021 were enrolled in this study. All patients underwent CT and MR scanning, and their recurrence status was identified by the biopsy. We randomly divided patients into training cohort (48 cases, non-recurrence: recurrence = 37: 11), validation cohort (21 cases, non-recurrence: recurrence = 16: 5), and testing cohort (35 cases, non-recurrence: recurrence = 27: 8), upon which we extracted 1989, 882 and 315 patches for model's development, validation and evaluation, respectively. The transformer network consisted of three modality fusion modules to extract multi-modality and multi-scale information, and a fully-connected module to perform recurrence risk prediction. The model's prediction performance was assessed by six metrics, including the area under the receiver operating characteristic curve (AUC), accuracy, f1-score, sensitivity, specificity and precision. Univariate analysis with F-test and T-test were conducted for statistical analysis.

Results

The proposed transformer network is superior to conventional radiomics methods and other deep learning networks in both training, validation and testing cohorts. Particularly, in testing cohort, the transformer network achieved the highest AUC of 0.819 ± 0.038, while four conventional radiomics methods and two deep learning networks got the AUCs of 0.680 ± 0.050, 0.720 ± 0.068, 0.777 ± 0.048, 0.691 ± 0.103, 0.743 ± 0.022 and 0.733 ± 0.027, respectively.

Conclusions

The multi-modality transformer network showed promising performance in recurrence risk stratification of LACC and may be used as an effective tool to help clinicians make clinical decisions.

Uterine fibroid and its association with metabolic syndrome in women of reproductive age (literature review)

   Uterine fibroid is one of the most common gynecological diseases in women of reproductive age and many aspects of this disease remain the subject of investigation. In particular, the role of the metabolic syndrome is of interest as a potential predictor of uterine fibroid or a comorbid condition that has pathogenetic significance.   The aim of this literature review is to systematize current data on the prevalence and associations of the metabolic syndrome and uterine fibroid in women of reproductive age.   Literature search was carried out using the scientific literature databases eLIBRARY, PubMed, NCBI, CyberLeninka, and the official IDF website for the period from 2010 to 2022. In PubMed search, we used the following terms: uterine fibroid, metabolic syndrome, uterine fibroid and metabolic syndrome, uterine myoma and metabolic syndrome, uterine myoma and metabolic disorders, uterine myoma and MetS. A total of 439 sources were analized, 32 sources met the search criteria.   Results. An analysis of the largest epidemiological studies conducted in recent years, both in non-selective populations and in hospital samples, demonstrates a significant prevalence of both uterine fibroid and metabolic syndrome among women. The results presented in the publications which were included in the review indicate that there is a relationship between the presence of uterine fibroid and the manifestations of the metabolic syndrome.   Conclusions. Uterine fibroid and metabolic syndrome are mutually aggravating conditions. Women with uterine fibroid have a worse risk profile for cardiovascular disease, and the presence of metabolic syndrome increases the risk of uterine fibroid. One of the ways to reduce the risk of occurrence and growth of uterine fibroid is the timely correction of the metabolic syndrome and its components. On the other hand, the presence of uterine fibroid should be considered as a basis for active detection of metabolic disorders and cardiovascular risks.

ACR Appropriateness Criteria® Fibroids

Uterine fibroids (leiomyomas or myomas) are the most common neoplasm of the uterus. Though incompletely understood, fibroid etiology is multifactorial, a combination of genetic alterations and endocrine, autocrine, environmental, and other factors such as race, age, parity, and body mass index. Black women have greater than an 80% incidence of fibroids by age 50, whereas White women have an incidence approaching 70%. Fibroid symptoms are protean, and menorrhagia is most frequent. The societal economic burden of symptomatic fibroids is large, 5.9 to 34.3 billion dollars annually. There are a variety of treatment options for women with symptomatic fibroids ranging from medical therapy to hysterectomy. Myomectomy and uterine fibroid embolization are the most common uterine sparing therapies. Pelvic ultrasound (transabdominal and transvaginal) with Doppler and MRI with and without intravenous contrast are the best imaging modalities for the initial diagnosis of fibroids, the initial treatment of known fibroids, and for surveillance or posttreatment imaging. The ACR Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer-reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances in which peer-reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Utility of the Diffusion Weighted Sequence in Gynecological Imaging: Review Article

Simple Summary

Diffusion weighted imaging (DWI) is a magnetic resonance imaging sequence with diverse clinical applications in malignant and nonmalignant gynecological conditions. It provides vital supplemental information in the diagnosis and management of various gynecological conditions. Radiologists should be aware of fundamental concepts, clinical applications and pitfalls of DWI. Additionally we briefly discuss potential scope of newer advanced techniques based on DWI including diffusion tensor imaging and diffusion-weighted whole-body imaging with background signal suppression.

Abstract

Functional imaging with diffusion-weighted imaging (DWI) is a complementary tool to conventional diagnostic magnetic resonance imaging sequences. It is being increasingly investigated to predict tumor response and assess tumor recurrence. We elucidate the specific technical modifications of DWI preferred for gynecological imaging, including the different b-values and planes for image acquisition. Additionally, we discuss the problems and potential pitfalls encountered during DWI interpretation and ways to overcome them. DWI has a wide range of clinical applications in malignant and non-malignant gynecological conditions. It provides supplemental information helpful in diagnosing and managing tubo-ovarian abscess, uterine fibroids, endometriosis, adnexal torsion, and dermoid. Similarly, DWI has diverse applications in gynecological oncology in diagnosis, staging, detection of recurrent disease, and tumor response assessment. Quantitative evaluation with apparent diffusion coefficient (ADC) measurement is being increasingly evaluated for correlation with various tumor parameters in managing gynecological malignancies aiding in preoperative treatment planning. Newer advanced DWI techniques of diffusion tensor imaging (DTI) and whole body DWI with background suppression (DWIBS) and their potential uses in pelvic nerve mapping, preoperative planning, and fertility-preserving surgeries are briefly discussed.

Quantitative assessment of iteratively denoised 3D SPACE with inner-volume excitation and simultaneous multi-slice BLADE for optimizing female pelvis magnetic resonance imaging at 1.5 T

RATIONALE AND OBJECTIVES

High-resolution T2-weighted magnetic resonance imaging (MRI) of the pelvis is the main technique used for diagnosing benign and malignant uterine diseases. However, the procedure may be time-consuming and requires training and experience. Therefore, this study was performed to compare the image quality of standard clinical BLADE (stBLADE) with a prototypical accelerated simultaneous multi-slice (SMS) BLADE procedure with either improved temporal resolution (tr) at the same slice thickness (SL) or improved spatial resolution (sr) with the same examination time and a prototypical isotropic 3D SPACE procedure with inner-volume excitation and iterative denoising.

MATERIALS AND METHODS

Patients who underwent clinically indicated MRI of the uterus were included in this prospective study and underwent stBLADE (acquisition time, 2 min 59 s; SL, 4 mm) and SMS BLADE (tr) with the same SL (4 mm) but reduced examination time (1 min 20 s) as well as SMS BLADE (sr) with thinner slices (3 mm) and comparable examination time (3 min 16 s). In addition, 3D SPACE was acquired in a sagittal orientation (5 min 36 s). The short axis of the cervix and the long axis of the corpus uteri were reconstructed in 1-mm and 3-mm SLs, retrospectively. Subjective overall image impression, delineation of anatomy/organs, lesion demarcation, and motion artifacts were assessed using a 5-point Likert scale and compared among the different techniques. The preferred sequence was then selected by three independent assessors.

RESULTS

The analysis was based on 38 women (mean age, 44 ± 15 years). The overall image impression was similar for stBLADE, SMS BLADE (sr), and SMS BLADE (tr) but was significantly lower for 3D SPACE than stBLADE (p = 0.01). SMS BLADE (sr) was considered the preferred sequence because of slightly better performance in terms of overall image impression, organ delineation, and lesion demarcation, but without statistical significance. Both SMS BLADE (tr) and (sr) produced significantly fewer motion artifacts than stBLADE (p < 0.01 and p = 0.01), with no significant difference between SMS BLADE (tr) and (sr), while 3D SPACE had a significantly lower rating than stBLADE (p < 0.01). Image quality was rated as the least diagnostic criterion in all sequences and all cases.

CONCLUSION

SMS BLADE (sr) was the preferred sequence for MRI of the female pelvis, with higher sr than stBLADE. SMS BLADE (tr) may also be used to reduce the acquisition time without compromising image quality. Despite its lower image quality, 3D SPACE can also reduce the examination time and improve the workflow because of the possibility of retrospective multiplanar reconstructions.

Periprocedural imaging compared to endometrial biopsy: is biopsy required prior to uterine artery embolisation?

AIM

To compare the detection rate of magnetic resonance imaging (MRI) and ultrasound relative to endometrial biopsy for endometrial abnormalities in both pre- and post-menopausal women.

MATERIALS AND METHODS

The present study was an institutional review board-approved, single-institution retrospective analysis of patients who underwent pelvic MRI within 1 year of diagnostic-quality biopsies from 2008-2018 (n=668). There were 303 patients who received uterine artery embolisation (UAE) and 478 patients who received pelvic ultrasound within the study period. Medical records were evaluated for radiological-histopathological correlation, demographics, laboratory studies, and clinical follow-up.

RESULTS

In this cohort of 668 patients, there were 37 biopsies positive for malignancy; women with malignancy were older (58 versus 47 years, p<0.0001) and more likely to be post-menopausal (66% versus 12%, p<0.0001). There were 303 patients who underwent UAE and underwent a diagnostic-quality endometrial biopsy during the pre-procedural evaluation, none of whom were post-menopausal and had a mean age of 45 years. In women with abnormal uterine bleeding (AUB) or post-menopausal bleeding (PMB), the sensitivity of MRI for detecting endometrial cancer was 96.2%, with a negative predictive value (NPV) of 99.8%, compared to 68% and 97% for ultrasound, respectively. The receiver operating characteristic (ROC) curve of pre-biopsy MRI in identifying pre-malignant and malignant endometrial pathology demonstrated an AUC of 0.8920 (p<0.0001).

CONCLUSION

In women with AUB or PMB, MRI has a 99.8% NPV in ruling out endometrial cancer. Further consideration should be made towards optimising pre-procedural evaluation for UAE.

Predictive value of image indexes of B-mode and power Doppler sonography on the efficacy of high intensity focused ultrasound ablation for uterine fibroids

OBJECTIVE

To investigate the value of the image indexes of B-mode and power Doppler sonography in predicting the therapeutic efficacy of high intensity focused ultrasound (HIFU) ablation for uterine fibroids.

MATERIALS AND METHODS

Two hundred and three patients with a solitary uterine fibroid were enrolled in this study. Every patient underwent transvaginal sonography (TVS) and magnetic resonance imaging (MRI) before HIFU. The patients were divided into hypointense, isointense and hyperintense fibroid groups based on T2 weighted MR imaging characteristics, and ultrasonic image indexes of the fibroids in different groups were compared. Multiple linear regression analysis was used to evaluate the correlation between ultrasonic image indexes and energy efficiency factor (EEF), non-perfused volume (NPV) ratio of uterine fibroids.

RESULTS

Among them, 72 patients had a hypointense fibroid, 70 had an isointense fibroid and 61 had a hyperintense fibroid. Significant differences were observed in the ultrasound imaging gray scale value difference between the myometrium and uterine fibroids (GSmyo-fib), the ultrasound imaging gray scale value ratio of fibroids over the myometrium (GSfib/myo), and the ratio of power Doppler pixel area to fibroid area (PDPA/FA) among the three groups (p < 0.05). Linear regression analysis showed that the PDPA/FA and the location of fibroids were the factors affecting the NPV ratio, a model for predicting the NPV ratio was established.

CONCLUSIONS

A model with the PDPA/FA for NPV ratio could be used to predict the therapeutic efficacy of HIFU for fibroids.

Uterine fibroid-like tumors: spectrum of MR imaging findings and their differential diagnosis

Uterine leiomyoma, also known as uterine fibroid, is the most common gynecological tumor, affecting almost 80% of women at some point during their lives. In the same time, other fibroid-like tumors have similar clinical presentations and about 0.5% of resected tumors of which were presumed benign fibroids in the preoperative diagnosis revealed as malignant sarcomas in the final histopathological examination. Amid the emergence of nonsurgical or minimally invasive procedures for symptomatic benign uterine fibroids, such as uterine artery embolization, high-intensity-focused ultrasound, or laparoscopic myomectomy, the preoperative diagnosis of uterine tumors through imaging becomes all the more relevant. Preoperative tissue sampling is challenging because of the variable location of the myometrial mass; thus, the preoperative evaluation of size and location is increasingly performed through magnetic resonance imaging. Features in images might also be useful for examining the full spectrum of such growths, from benign fibroids to neoplasms of uncertain behavior and malignant sarcomas. Benign fibroids include usual-type leiomyomas, myomas with degeneration, and mitotically active leiomyomas. Neoplasms of uncertain behavior include smooth muscle tumors of uncertain malignant potential, leiomyomas with bizarre nuclei, and cellular leiomyomas. Malignant sarcomas comprise leiomyosarcomas, endometrial stromal sarcomas, adenosarcomas, and carcinosarcomas. The purpose of this article is to review the spectrum of MRI findings of uterine fibroid-like tumors, from benign variants, uncertain behavior to malignant sarcomas, and update the advanced imaging modalities, including diffusion-weighted imaging, positron emission tomography/computed tomography, combining texture analysis and radiomics, to tackle this important issue.

Ultrasound-Guided Trans-Uterine Cavity Core Needle Biopsy of Uterine Myometrial Tumors to Differentiate Sarcoma from a Benign Lesion—Description of the Method and Review of the Literature

Uterine sarcomas are rare, aggressive tumors with poor prognosis that can be further negatively affected by inadequate surgical approaches such as morcellation. There are no clinical and radiologic criteria for differentiating leiomyoma from malignant uterine tumors. However, some ultrasonography and magnetic resonance imaging findings may be informative. We present a technique of ultrasound-guided trans-uterine cavity (UG-TUC) core needle biopsy for uterine lesions. As the procedure is an in-organ biopsy, there is no risk of needle canal contamination. The technique also enables the biopsy of lesions inaccessible by the transvaginal tru-cut biopsy. The core needle of the automatic biopsy system is inserted via the cervical canal into the uterine cavity and is directed and activated at the myometrial lesion under ultrasound control. The standard local treatment of localized uterine sarcomas is en bloc total hysterectomy; for fibroids, there are multiple options including conservative management or tumorectomy and tumor morcellation using minimally invasive techniques. Fragmentation of the sarcoma significantly worsens oncologic outcomes and should therefore be avoided. The UG-TUC core needle biopsy of uterine lesions can complement imaging to obtain sufficient material for histologic and molecular analyses of suspected or undetermined lesions, thus facilitating treatment planning and decreasing the risk of unsuspected sarcomas.

Review of uterine fibroids: imaging of typical and atypical features, variants, and mimics with emphasis on workup and FIGO classification

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.

MRI in female pelvis: an ESUR/ESR survey

Objectives

While magnetic resonance imaging (MRI) is considered the gold standard for the imaging of female pelvis, there is an ongoing debate about the most appropriate indications and optimal imaging protocols. The European Society of Urogenital Radiology (ESUR) launched a survey to evaluate the current utilization of female pelvic MRI in clinical practice.

Methods

The ESUR female imaging subgroup developed an online survey that was then approved by the ESR board and circulated among the ESR members. The questions in the survey encompassed training and experience, indications for imaging and MR imaging protocols, reporting styles and preferences. The results of the survey were tabulated, and subgroups were compared using χ2 test.

Results

A total of 5900 ESR members with an interest in both MRI and female pelvic imaging were invited to participate; 840 (14.23%) members completed the survey. Approximately 50% of respondents were academic radiologists (50.6%) and nearly 60% women (59.69%). One third of the respondents were subspecialized in Gynecological imaging. Nearly half of the survey participants were aware of the presence of ESUR guidelines for imaging of the female pelvis (47.1%). The adoption of the ESUR recommendations was higher among subspecialized and/or academic and/or senior and/or European radiologists compared to all others. The current ESUR recommendations about female pelvic MRI protocols were generally followed. However wide variations in practice were identified with respect to the use of contrast media.

Conclusion

Female pelvic MRI protocol was generally following the ESUR recommendations, especially among subspecialized and academic radiologists. However, the fact that they are followed by only half of the participants highlights the need for wider awareness of these recommendations.

Clinical value of pre-operative scoring systems to predict leiomyosarcoma: results of a validation study in 177 patients from the NOGGO-REGSA Registry

Objectives

Benign leiomyomas are the most common uterine tumors. In contrast, uterine leiomyosarcomas are malignancies with a poor prognosis due to difficulties in early diagnosis and inappropriate surgical treatment. Most often they are diagnosed incidentally after surgery performed for treatment of leiomyoma. As the appropriate surgical treatment is crucial for survival of the patient, there is a high demand to predict leiomyosarcoma pre-operatively. Available scoring systems to discriminate leiomyoma from leiomyosarcoma are based on retrospective studies with limited numbers of patients and are not implemented in routine clinical practice.

Methods

The aim of our study was to evaluate a recently published score—the pre-operative leiomyosarcoma (pLMS) score—to determine whether it would have been predictive of leiomyosarcoma in 177 patients from the NOGGO-REGSA study, a German register of histologically proven gynecological sarcoma detected during routine clinical investigation.

Results

The threshold of the pLMS score for ‘leiomyosarcoma not probable’ (< −3) failed for 7.5% of the patients and the threshold ‘indicator for leiomyosarcoma’ (>+1) was true for 39.1% of the patients. 53.4% of the patients were attributed to the group ‘additional investigations are recommended’ (−3 to +1). The most relevant parameters in our analysis were suspicious sonography and rapid growth, but neither have been quantitatively defined.

Conclusion

In our validation cohort, the pLMS score seems not to be a reliable tool to predict leiomyosarcoma and therefore we do not recommend its clinical implementation to identify leiomyosarcoma.

Impact of Deep Learning Reconstruction Combined With a Sharpening Filter on Single-Shot Fast Spin-Echo T2-Weighted Magnetic Resonance Imaging of the Uterus

OBJECTIVE

This study aimed to evaluate the effects of deep learning (DL) reconstruction and a postprocessing sharpening filter on the image quality of single-shot fast spin-echo (SSFSE) T2-weighted imaging (T2WI) of the uterus.

MATERIALS AND METHODS

Fifty consecutive patients who underwent pelvic magnetic resonance imaging were included. Parasagittal T2WI with a slice thickness of 4 mm was obtained with the periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) and SSFSE sequences (mean scan time, 204 and 22 seconds, respectively). The following 3 types of SSFSE images were reconstructed, and the signal-to-noise ratio (SNR) and tissue contrast were assessed: conventional reconstruction (SSFSE-C), DL reconstruction (SSFSE-DL), and DL with a sharpening filter (SSFSE-DLF). Three radiologists independently assessed image quality, and area under the visual grading characteristics curve (AUCVGC) analysis was performed to compare the SSFSE and PROPELLER images.

RESULTS

Compared with that of the PROPELLER images, the SNR of the SSFSE-C, SSFSE-DL, and SSFSE-DLF images was significantly lower (P < 0.05), significantly higher (P < 0.05), and equivalent, respectively. The SSFSE-DL images exhibited significantly lower contrast between the junctional zone and myometrium than those obtained with the other sequences (P < 0.05). In qualitative comparisons with the PROPELLER images, all 3 SSFSE sequences, SSFSE-DL, and SSFSE-DLF demonstrated significantly higher scores for artifacts, noise, and sharpness, respectively (P < 0.01). The overall image quality of SSFSE-C (mean AUCVGC, 0.03; P < 0.01) and SSFSE-DL (mean AUCVGC, 0.23; P < 0.01) was rated as significantly inferior, whereas that of SSFSE-DLF (mean AUCVGC, 0.69) was equivalent or significantly higher (P < 0.01).

CONCLUSION

Using a combination of DL and a sharpening filter markedly increases the image quality of SSFSE of the uterus to the level of the PROPELLER sequence.

Differentiating uterine sarcoma from leiomyoma: BET1T2ER Check!

Although rare, uterine sarcoma is a diagnosis that no one wants to miss. Often benign leiomyomas (fibroids) and uterine sarcomas can be differentiated due to the typical low T2 signal intensity contents and well-defined appearances of benign leiomyomas compared to the suspicious appearances of sarcomas presenting as large uterine masses with irregular outlines and intermediate T2 signal intensity together with possible features of secondary spread. The problem is when these benign lesions are atypical causing suspicious imaging features. This article provides a review of the current literature on imaging features of atypical fibroids and uterine sarcomas with an aide-memoire BET¹T²ER Check! to help identify key features more suggestive of a uterine sarcoma.

New imaging modalities to distinguish rare uterine mesenchymal cancers from benign uterine lesions

PURPOSE OF REVIEW

Uterine sarcomas are rare and are often challenging to differentiate on imaging from benign mimics, such as leiomyoma. As functional MRI techniques have improved and new adjuncts, such as machine learning and texture analysis, are now being investigated, it is helpful to be aware of the current literature on imaging features that may sometimes allow for preoperative distinction.

RECENT FINDINGS

MRI, with both conventional and functional imaging, is the modality of choice for evaluating uterine mesenchymal tumors, especially in differentiating uterine leiomyosarcoma from leiomyoma through validated diagnostic algorithms. MRI is sometimes helpful in differentiating high-grade stromal sarcoma from low-grade stromal sarcoma or differentiating endometrial stromal sarcoma from endometrial carcinoma. However, imaging remains nonspecific for evaluating rarer neoplasms, such as uterine tumor resembling ovarian sex cord tumor or perivascular epithelioid cell tumor, primarily because of the small number and power of relevant studies.

SUMMARY

Through advances in MRI techniques and novel investigational imaging adjuncts, such as machine learning and texture analysis, imaging differentiation of malignant from benign uterine mesenchymal tumors has improved and could help reduce morbidity relating to misdiagnosis or diagnostic delays.

MRI findings in-between leiomyoma and leiomyosarcoma: a Rad-Path correlation of degenerated leiomyomas and variants

Leiomyomas are the most common benign tumors of the uterus. On the opposite side, leiomyosarcomas are rare malignant uterine tumors that account for a significant proportion of uterine cancer deaths. Especially when large and degenerated, leiomyomas and leiomyoma variants can have overlapping imaging characteristics with those of leiomyosarcomas. Although not always possible, it is paramount to be able to differentiate between leiomyomas and leiomyosarcomas on imaging, as the therapeutic management can differ. This pictorial review aims to familiarize radiologists with imaging features of leiomyomas and various types of leiomyoma degeneration and variants, together with their pathology correlates.

MRI of the endometrium - from normal appearances to rare pathology

MRI was recently included as a standard pre-operative diagnostic tool for patients with endometrial cancer. MR findings allow a better risk assessment and ultimately guides the surgical planning. Therefore, it is vital that the radiological interpretation is as accurate as possible. This requires essential knowledge regarding the appropriate MRI protocol, as well as different appearances of the endometrium, ranging from normal peri- and post-menopausal changes, benign findings (e.g. endometrial hyperplasia, polyp, changes due to exogenous hormones) to common and rare endometrium-related malignancies. Furthermore, this review will emphasize the role of MRI in staging endometrial cancer patients and highlight pitfalls that could result in the underestimation or overestimation of the disease extent.

Benign Uterine Disease: The Added Role of Imaging

Benign uterine diseases are very common gynecologic conditions that affect women mostly in reproductive age. Ultrasound examination is the first-line imaging technique, but MRI is more accurate for diagnosis, characterization, and patient management. In this review, we especially highlight the added value of MRI in the diagnosis of benign uterine disease, discuss their imaging characteristics, and describe the therapeutic options and the added value of MRI in the treatment planning.

Comparison of 1.5 T and 3 T non-contrast-enhanced MR angiography for visualization of uterine and ovarian arteries before uterine artery embolization

OBJECTIVES

This study aimed to compare the performance of non-contrast-enhanced magnetic resonance angiography (NCE-MRA) at 1.5 T and 3 T for the visualization of uterine and ovarian arteries (OAs) before uterine artery embolization (UAE).

METHODS

Preprocedural pelvic NCE-MRA images of 85 symptomatic patients undergoing UAE for the treatment of uterine leiomyomas were reviewed by two specialists in pelvic MRI. Left and right uterine arteries (UAs) were judged separately and scored on a 5-point scale. Score 5 was the highest, in which the UA could be visualized inside the musculature, forming a peritumoral plexus. Score 1 was the lowest, where visualization was limited to the descending segment. The detection of enlarged OAs was also compared. The Mann-Whitney U and Fisher exact tests were used for statistical analysis. p < 0.05 was considered to be statistically significant.

RESULTS

Of the 170 UAs, 110 were classified at 1.5 T and 60 were classified at 3 T. Median (interquartile range [IQR]) score was 3 (IQR: 2-4) for visualization at 1.5 T vs 5 (IQR: 4-5) for 3 T. The scores for UA visualization were significantly higher at 3 T (p < 0.05). For enlarged OAs, NCE-MRA at 1.5 T and 3 T visualized 7 and 5 enlarged OAs, respectively; there was no significant difference between the two field strengths (p = 0.36).

CONCLUSIONS

NCE-MRA performed at 3 T can visualize UAs over a greater range than at 1.5 T. No difference was found regarding the detection of enlarged OAs.

KEY POINTS

• Preprocedural MRA can provide interventional radiologists with valuable information, including the origin and course of the uterine arteries and the existence of collateral feeders to the tumor. • This study demonstrates the superiority of non-contrast-enhanced MRA performed at 3 T over that performed at 1.5 T in the visualization of the uterine arteries in patients undergoing uterine artery embolization for the treatment of uterine leiomyomas. • Non-contrast-enhanced MRA is a useful imaging modality for patients with symptomatic leiomyoma undergoing uterine artery embolization in whom contrast administration is unfeasible. If available, it is preferable to perform the examination with a 3 T MR unit rather than a 1.5 T MR unit.

Diagnostic interpretation of non-contrast qualitative MR imaging features for characterisation of uterine leiomyosarcoma

OBJECTIVE

To assess the value of non-contrast MRI features for characterisation of uterine leiomyosarcoma (LMS) and differentiation from atypical benign leiomyomas.

METHODS

This study included 57 atypical leiomyomas and 16 LMS which were referred pre-operatively for management review to the specialist gynaeoncology multidisciplinary team meeting. Non-contrast MRIs were retrospectively reviewed by five independent readers (three senior, two junior) and a 5-level Likert score (1-low/5-high) was assigned to each mass for likelihood of LMS. Evaluation of qualitative and quantitative MRI features was done using uni- and multivariable regression analysis. Inter-reader reliability for the assessment of MRI features was calculated by using Cohen's κ values.

RESULTS

In the univariate analysis, interruption of the endometrial interface and irregular tumour shape had the highest odds ratios (ORs) (64.00, p < 0.001 and 12.00, p = 0.002, respectively) for prediction of LMS. Likert score of the mass was significant in prediction (OR, 3.14; p < 0.001) with excellent reliability between readers (ICC 0.86; 95% CI, 0.76-0.92). The post-menopausal status, interruption of endometrial interface and thickened endometrial stripe were the most predictive independent variables in multivariable estimation of the risk of leiomyosarcoma with an accuracy of 0.88 (95%CI, 0.78-0.94).

CONCLUSION

At any level of expertise as a radiologist reader, the loss of the normal endometrial stripe (either thickened or not seen) in a post-menopausal patient with a myometrial mass was highly likely to be LMS.

ADVANCES IN KNOWLEDGE

This study demonstrates the potential utility of non-contrast MRI features in characterisation of LMS over atypical leiomyomas, and therefore influence on optimal management of these cases.

Low-grade serous epithelial ovarian cancer: a comprehensive review and update for radiologists

Low-grade serous carcinoma (LGSC) is an infrequent subtype of ovarian cancer, corresponding to 5% of epithelial neoplasms. This subtype of ovarian carcinoma characteristically has molecular features, pathogenesis, clinical behaviour, sensitivity to chemotherapy, and prognosis distinct to high-grade serous carcinoma (HGSC). Knowing the difference between LGSC and other ovarian serous tumours is vital to guide clinical management, which currently is only possible histologically. However, imaging can provide several clues that allow differentiating LGSC from other tumours and enable precise staging and follow-up of ovarian cancer treatment. Characteristically, LGSC appears as mixed lesions with variable papillary projections and solid components, usually in different proportions from those detected in serous borderline tumour and HGSC. Calcified extracellular bodies, known as psammoma bodies, are also a common feature of LGSC, frequently detectable within lymphadenopathies and metastases associated with this type of tumour. In addition, the characterisation of magnetic resonance imaging enhancement also plays an essential role in calculating the probability of malignancy of these lesions. As such, in this review, we discuss and update the distinct radiological modalities features and the clinicopathologic characteristics of LGSC to allow radiologists to be familiarised with them and to narrow the differential diagnosis when facing this type of tumour.

ACR Appropriateness Criteria® Postmenopausal Acute Pelvic Pain

Acute pelvic pain is a common presenting complaint in both the emergency room and outpatient settings. Pelvic pain of gynecologic origin in postmenopausal women occurs less frequently than in premenopausal women; however, it has important differences in etiology. The most common causes of postmenopausal pelvic pain from gynecologic origin are ovarian cysts, uterine fibroids, pelvic inflammatory disease, and ovarian neoplasm. Other etiologies of pelvic pain are attributable to urinary, gastrointestinal, and vascular systems. As the optimal imaging modality varies for these etiologies, it is important to narrow the differential diagnosis before choosing the initial diagnostic imaging examination. Transabdominal and transvaginal ultrasound are the best initial imaging techniques when the differential is primarily of gynecologic origin. CT with intravenous (IV) contrast is more useful if the differential diagnosis remains broad. MRI without IV contrast or MRI without and with IV contrast, as well as CT without IV contrast may also be used for certain differential considerations. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Multiparametric MR evaluation of uterine leiomyosarcoma and STUMP versus leiomyoma in symptomatic women planned for high frequency focussed ultrasound: accuracy of imaging parameters and interobserver agreement for identification of malignancy

OBJECTIVE

To assess accuracy of and interobserver agreement on multiparametric MR findings to distinguish uterine leiomyoma (LM) from uterine leiomyosarcoma (LMS) and soft tissue tumour of unknown malignant potential.

METHODS

Inclusion criteria: All females over 18 years with least one uterine mass measuring 5 cm or more in at least one of the three standard orthogonal dimensions on MR with histopathological confirmation of LM, LMS, or soft tissue tumour of unknown malignant potential (STUMP) in the 3 months following MR. Patients with LMS were drawn from a larger cohort being assessed for MR-guided focussed ultrasound (MRgFUS) suitability. Image evaluation: Assessed variables were: lesion margin, margin definition, T2 signal homogeneity, >50% of lesion with T2 signal brighter than myometrium, haemorrhage, restricted diffusion, contrast enhancement (CE), CE pattern, local lymphadenopathy and ascites.

RESULTS

32 LM, 10 LMS and 1 STUMP were evaluated. Ill-defined (p-value = 0.0003-0.0004) or irregular (p = 0.003-0.004) lesion margin, T2 hyperintensity >50% (p = 0.001-0.004), and peripheral CE (p = 0.02-0.05) were significantly more common in LMS/STUMP than LM for both radiologists. 10/11 (Reader 2) and 11/11 (Reader 1) LMS/STUMP displayed restricted diffusion but so did 63-80% of LM. Agreement was greatest for margin characteristics (κ = 0.73-0.81).

CONCLUSION

Irregular/ill-defined lesion margin best distinguished LMS/STUMP from LM with good interrater reliability.

ADVANCES IN KNOWLEDGE

Assessment of agreement regarding MR parameters distinguishing LM from LMS and STUMP has not previously been undertaken in a cohort including a large number of patients with LMS. This will help inform evaluation of females considering minimally invasive LM treatment.

Inoperable Left Renal Vein Leiomyosarcoma Refractory to Chemotherapy Invades Inferior Vena Cava and Right Atrium: A Case Report

Mesenchymal stem cells differentiate into a plethora of cell types. These differentiated cell types include osteoblasts, chondrocytes, myocytes, and adipocytes. Sarcomas occur secondary to malignant transformation of these mesenchymal, pluripotent stem cells. Involuntary smooth muscle is responsible for the make up of hollow organs and vasculature in our body and is regulated by our autonomic nervous system, hormones, as well as chemical and local mediators. Cancer involving smooth muscle cells is designated as leiomyosarcoma (LMS). LMS can arise from any location in the body where smooth muscle is present and is frequently reported in the abdomen and pelvis, as well as the trunk, extremities, and throughout the retroperitoneum. 

A combined radiomics and clinical variables model for prediction of malignancy in T2 hyperintense uterine mesenchymal tumors on MRI

OBJECTIVE

This study aims to develop a machine learning model for prediction of malignancy in T2 hyperintense mesenchymal uterine tumors based on T2-weighted image (T2WI) features and clinical information.

METHODS

This retrospective study included 134 patients with T2 hyperintense uterine mesenchymal tumors (104 patients in training cohort and 30 in testing cohort). A total of 960 radiomics features were initially computed and extracted from each 3D segmented tumor depicting on T2WI. The support vector machine (SVM) classifier was applied to build computer-aided diagnosis (CAD) models by using selected clinical and radiomics features, respectively. Finally, an observer study was conducted by comparing with two radiologists to evaluate the diagnostic performance. The area under the receiver operating characteristic (ROC) curve (AUC) was computed to assess the performance of each model.

RESULTS

Comparing with the T2WI-based radiomics model (AUC: 0.76 ± 0.09) and the clinical model (AUC: 0.79 ± 0.09), the combined model significantly improved the AUC value to 0.91 ± 0.05 (p < 0.05). The clinical-radiomics combined model yielded equivalent or higher performance than two radiologists (AUC: 0.78 vs. 0.91, p = 0.03; 0.90 vs.0.91, p = 0.13). There was a significant difference between the AUC values of two radiologists (p < 0.05).

CONCLUSIONS

It is feasible to predict malignancy risk of T2 hyperintense uterine mesenchymal tumors by combining clinical variables and T2WI-based radiomics features. Machine learning-based classification model may be useful to assist radiologists in decision-making.

KEY POINTS

• Radiomics approach has the potential to distinguish between benign and malignant mesenchymal uterine tumors. • T2WI-based radiomics analysis combined with clinical variables performed well in predicting malignancy risk of T2 hyperintense uterine mesenchymal tumors. • Machine learning-based classification model may be useful to assist radiologists in characterization of a T2 hyperintense uterine mesenchymal tumor.

MRI Findings and Differential Diagnosis of Benign and Malignant Tumors of the Uterine Corpus

자궁은 크게 자궁체부와 자궁경부로 나뉜다. 이 중 자궁내막과 자궁근층으로 이루어진 자궁체부에는 양성에서 악성 종양까지 다양한 질환이 발생한다. 비침습적인 일차적 평가로 초음파와 컴퓨터단층촬영이 있으나 비특이적인 영상 소견으로 감별이 어려운 경우가 있다. 반면높은 해상도와 병리학적 특성 파악이 가능한 자기공명영상은 병변의 위치 확인뿐만 아니라 조직학적 특징, 그 리고 악성 종양의 병기 설정에도 도움을 준다. 이 종설에서는 영상의학과의사들이 알아야 할 자궁체부에서 볼 수 있는 다양한 양성과 악성 종양들의 특징적인 자기공명영상 소견들과 이들의 감별점에 대해 정리했다.