Current Medical Imaging Formerly Current Medical Imaging Reviews

Using Apparent Diffusion Coefficient (ADC) of Endometrial Cancer MRI to Determine P53 Molecular Subtypes

Background:: Endometrial Cancer (EC) is a highly heterogeneous cancer comprising both histological and molecular subtypes. Using a non-invasive modality method to trigger these subtypes as early as possible can aid clinicians in establishing individualized treatment Purpose:: The study aimed to clarify the value of the Apparent Diffusion Coefficient (ADC) of EC MRI in determining molecular subtypes. Material and Methods:: We retrospectively recruited 109 patients with pathologically proven EC (78 endometrioid cancers and 31 non-endometrioid cancers) with available molecular classification from a tertiary centre. MRI was prospectively performed a month prior to surgery; images were blindly interpreted by two experienced radiologists with consensus reading. The ADC value was measured by an experienced radiologist on the commercially available processing workstation. Interoperator measurement consistency was calculated. Results:: Our sample comprised 17 PLOE, 32 MSI-H, 31 NSMP, and 29 P53abn ECs. Clinical information did not differ significantly among the groups. The maximum diameter and volume of the lesions differed among the groups. The ADC value in the maximal area (ADCarea) or region of interest (ROI, ADCroi) in the P53abn group was higher than that in the other groups (894.0 ±12.6 and 817.5 ± 83.3 x10-6 mm2/s). The ADC mean values were significantly different between the P53abn group and the other groups (P = 0.000). The nomogram showed the highest discriminative ability to distinguish P53abn EC from other types (AUC: 0.859). Conclusion:: Our results have suggested the quantitative MR characteristics (ADC values) derived from preoperative EC MRI to provide useful information in preoperatively determining P53abn cancer.

Clinical and Imaging Characteristics of Non-Gestational Ovarian Choriocarcinoma: A Case Report

Background: Non-gestational Ovarian Choriocarcinoma (NGOC) is an extremely rare and highly malignant ovarian germ cell tumor with nonspecific clinical manifestations, making early diagnosis challenging. At present, detailed reports on the clinical and imaging characteristics of NGOC are scarce. This case report discusses a rare instance of NGOC in a prepubertal adolescent, complemented by a literature review to enhance clinicians’ understanding of its presentation, diagnosis, and treatment. Case Presentation: A 10-year-old female with no history of menstruation or sexual activity presented with persistent lower abdominal pain and vaginal bleeding. Preoperative imaging revealed a large pelvic mass with heterogeneous echogenicity and vascularity. Serum Human Chorionic Gonadotropin (hCG) levels were markedly elevated (>297,000 IU/L). Preoperative Imaging: Ultrasonography and CT demonstrated a large, heterogeneous, hypervascular adnexal mass with features of necrosis and cystic changes, suggesting malignancy. Surgical and Pathological Findings: The mass, originating from the right adnexa, was removed via laparotomy. Histopathology confirmed NGOC, supported by immunohistochemistry, showing strong positivity for markers like CD146, CK18, HCG, and HPL, along with a high Ki-67 index (>90%). Conclusion: In young females with no sexual life, significantly elevated HCG levels and imaging findings of a large heterogeneous adnexal mass should raise suspicion for NGOC. Early recognition and multimodal diagnostic approaches, including imaging, biochemical, and pathological assessments, are essential for timely intervention, reducing metastatic risk and improving prognosis. This report contributes to the understanding of NGOC and emphasizes the importance of accurate diagnosis for better patient outcomes.

MR Imaging of Typical Ovarian Hemangioma: A Case Report

Background: Ovarian hemangioma is an extremely rare tumor with atypical clinical manifestations, often discovered incidentally during autopsy or surgery. Approximately 60 cases have been reported in the past, but no more than 10 cases have been investigated by MRI and ultrasound (US). Case Presentation: ln this paper, we reported a 51-year-old female patient with Ovarian Hemangioma who had no symptoms of abdominal pain, abnormal vaginal bleeding or discharge, or any other discomfort. Laboratory tests revealed an elevated serum carbohydrate antigen (CA125) of 48.99U/ml (reference range: 0-35U/ml). Multiparametric 3.0T magnetic resonance imaging (MRI) showed a cystic solid mass with a clear boundary and regular shape in the left ovarian area and minimal ascites in the abdominal cavity. The histological examination of the mass confirmed an ovarian hemangioma. Conclusion: The MRI findings of ovarian hemangiomas are highly similar to those observed in hepatic hemangiomas, emphasizing the distinctive radiological characteristics specific to this condition in the ovary. This paper presents an overview of the typical MRI findings associated with ovarian hemangioma, which holds great importance for accurate diagnosis and effective treatment.

18F-DGPET/CT Imaging of Ovarian Yolk Sac Tumor in a Woman after Induction of Labor: A Case Report

Introduction:: Ovarian yolk sac tumor (OYST) during pregnancy is rare and usually missed. There are few PET/CT studies on OYST in the literature. We reported a case of OYST detected by 18F-FDG PET/CT in a woman after induction of labor. Case Presentation:: A 19-year-old woman after induction of labor because of severe malformation presented with abdominopelvic mass, laboratory tests revealed significantly elevated serum alpha-fetoprotein (AFP) level and elevated carbohydrate antigen 125 level. Abdomino-pelvic CT showed a cysticsolid mass of 82×152×167mm arising from the right ovary with abundant intratumoral vessels and intense enhancement in the solid part. Further evaluation of 18F-FDG PET/CT imaging showed significantly increased 18FDG uptake (SUVmax7.7) by the solid component of the ovarian mass and slight 18FDG-avid perihepatic effusion. The mass was resected and was confirmed to be the right OYST, After four courses of chemotherapy, the patient was followed up by PET/CT and had a complete metabolic response. Discussion:: 18F-FDG PET/CT is a useful imaging modality for diagnosis and evaluation of OYST.

MR Diffusion-Weighted Imaging in Evaluating Immediate HIFU Treatment Response of Uterine Fibroids

Background:: Nowadays, High Intensity Focused Ultrasound (HIFU) is a common surgery option for the treatment of uterine fibroids in China, the immediate response of which is clinically evaluated using Contrast Enhanced (CE) imaging. However, the injection of gadolinium with its potential adverse effect is of concern in CE and therefore, it deserves efforts to find a better imaging method without the need for contrast agent injection for this task. Objective:: To assess the role of diffusion-weighted imaging (DWI) in evaluating the immediate therapeutic response of HIFU treatment for uterine fibroids in comparison with CE. Methods:: 68 patients with 74 uterine fibroids receiving HIFU treatment were enrolled, and immediate treatment response was assessed using post-surgical DWI images. Semi-quantitative ordinal ablation quality grading and quantitative nonperfusion volume (NPV) measurement based on DWI and CE imaging were determined by two experienced radiologists. Agreement of ablation quality grading between DWI and CE was assessed using the weighted kappa coefficient, while intraobserver, interobserver and interprotocol agreements of NPV measurements within and between DWI and CE were evaluated using the intraclass correlation (ICC) and Bland-Altman analysis. Results:: Grading of immediate HIFU treatment response showed a moderate agreement between DWI and CE (weighted kappa = 0.446, p < 0.001). NPV measured in 65 fibroids with DWI of Grade 3~5 showed very high ICCs for the intraobserver and interobserver agreement within DWI and CE (all ICC > 0.980, p < 0.001) and also for the interprotocol agreement between DWI and CE (ICC = 0.976, p < 0.001). Conclusion:: DWI could provide satisfactory ablation quality grading, and reliable NPV quantification results to assess immediate therapeutic responses of HIFU treatment for uterine fibroids in most cases, which suggests that non-contrast enhanced DWI might be potentially used as a more costeffective and convenient method in a large proportion of patients for this task replacing CE imaging.

The Typical Computed Tomography Findings of Primary Fallopian Tube Carcinoma

Aim: This study aimed to investigate the imaging features of primary fallopian tube carcinoma (PFTC). Methods: Imaging findings of 12 PFTC patients were retrospectively studied. Multi-slice computed tomography (CT, MSCT) was performed to investigate tumor location, size, density, appearance (cystic/solid), enhancement pattern, and metastasis. Results: Twelve women aged 34–67 (mean=54.3) years were presented with pelvic pain (n=6), vaginal discharge (n=5), and incidental pelvic masses (n=3). The tumor diameters of PFTC varied from 3.3 to 6.8 cm (mean=4.7 cm). Ten cases were unilateral, and two were bilateral. The lesions were adnexal tubular-shaped cystic masses with mucosal papillary nodes in six cases, irregular cystic and solid masses in four cases, and sausage-shaped solid masses in two cases. The plain CT values ranged from 15 to 35 HU (mean, 28 HU). On enhanced CT, the enhancement of the solid composition was lower than that of the myometrium in all phases. CT values in arterial and venous phases were 55-62 and 60-63 HU, respectively, with average values of 58.6 and 61 HU. The metastasis sites included the ovary (n=2), omentum (n=3), retroperitoneal lymph nodes (n=5), pelvic lymph nodes (n=5), and inguinal lymph nodes (n=2). Seven cases exhibited pelvic fluid, and seven exhibited round ligament thickening on the lesioned side. Conclusion: In patients presenting with vaginal discharge or genital bleeding and sausage-shaped or tubal-shaped cystic, solid, or solid-cystic complexes in the adnexal portion associated with hydrosalpinx and peritumoral ascites, PFTC should be considered in the diagnosis, especially in tumors associated with round ligament thickening.

Ovarian Granulosa Cell Tumor: A Clinicoradiologic Series with Literature Review

Background: Ovarian granulosa cell tumors that originate from the sex cord-stromal cells represent 2% to 5% of all ovarian cancers. These tumors constitute two subgroups according to their clinical and histopathological features: juvenile granulosa cell tumors (JGCT) and adult granulosa cell tumors (AGCT). Granulosa cell tumor (GCT) is considered to be a low-grade malignancy with a favorable prognosis. Methods: This case series includes four patients who admitted to our university hospital and had an MRI examination within 5 years. Results: The histopathological subtype of granulosa tumor was the adult type in 3 patients and juvenile type in 1 patient. Even though it is extremely rare, bone metastases were present in one of our patients. Liver metastases were also detected in one patient. The MRI examination of tumors revealed a heterogeneous solid mass that contained cystic components in 3 patients. In one of our patients, the tumor had a multiseptated cystic feature, and all of the tumors were ovoid or round with smooth margins. T1 signal hyperintensity, not suppressed on fat saturation sequences, was observed in 3 patients, which represents its hemorrhagic content. Conclusion: Even though granulosa cell tumor shows a wide spectrum in terms of tumor appearance, some common findings have been shown and especially a hemorrhagic content could be a clue for us. The tumor is known to have a good prognosis, but it may have an unpredictable clinical course, so close follow-up is greatly important.

Differentiation of Borderline Epithelial Ovarian Tumors from Benign and Malignant Epithelial Ovarian Tumors by MRI Scoring

Introducstion: The distinction between benign and borderline epithelial ovarian tumors is important because treatment and follow-up strategies differ. Objective: We aimed to evaluate benign, borderline, and malignant epithelial ovarian tumors using MRI features and contributed to the preoperative evaluation. Methods: MRIs of 81 patients (20 bilateral), including 31 benign, 27 borderline, and 23 malignant, who had pelvic imaging between 2013-2020, were evaluated retrospectively. The evaluation was made blindly to the pathology result by two radiologists with MRI scoring and features that we determined. MRI evaluation was performed with T1 TSE, T2 TSE, fat-suppressed T2 TSE, and before and after contrast T1 fat-suppressed and non-fat-suppressed TSE images. The numbers and findings obtained in scoring were evaluated by Chi-Square, ordinal logistic regression, and 2 and 3 category ROC analysis. Results: The total score varied between 7 and 24. Among the three groups, a significant difference was found in terms of T1, T2 signal intensity (p <0.01), size (p = 0.055), solid area (p <0.001), septa number (p <0.05), ovarian parenchyma (p = 0.001), ascites (p <0.001), peritoneal involvement (p <0.001), laterality (p <0.001), contrast enhancement pattern (p <0.001). On the other hand, no significant difference was found in terms of wall thickness, lymph node involvement and endometrial thickness (p> 0.05). Cut-off values were found as 11.5 and 18.5 in the 3-category ROC analysis performed for the score (VUS: 0.8109). Patients with a score below 11.5 were classified as benign, those between 11.5-18.5 as borderline, and those over 18.5 as malignant. Conclusion: The differentiation of borderline tumors from benign and malignant tumors by MRI scoring will contribute to the preoperative diagnosis.

Analysis of the Correlation between MRI Imaging Signs and Lymphovascular Space Invasion in Endometrial Cancer

Background: Determination of LVSI is the recommended criterion for performing lymphatic drainage and is important for the preoperative clinical decisionmaking process; however, Intraoperative Frozen Section (IFS) has limitations for the analysis of LVSI, and there is an urgent need for other indirect methods to predict the presence of LVSI. Aim: This study aimed to investigate the value of Magnetic Resonance Imaging (MRI) features in predicting Lymphovascular Space Invasion (LVSI) in endometrial cancer (EC). Objective: The objective of this study was to analyze MRI features that may be associated with LVSI and to explore their association. Methods: In this study, 179 patients who received treatment for EC confirmed by surgical pathology at two medical institutions from January 2017 to May 2024 were reviewed and grouped according to the presence or absence of vascular cancer embolism in the pathology. The MRI imaging features of the two groups were compared, including the maximum transverse diameter in the sagittal position, myometrial invasion, disruption of the uterine Junctional Zone (JZ), serosal surface, uterine appendages, cervical stromal invasion, lymph node enlargement, and its T2 value, and Diffusion- Weighted Imaging (DWI). The risk factors of the LVSI-positive group were determined by performing logistic regression analysis to analyze the correlation between Apparent Diffusion Coefficient (ADC) values and LVSI in EC. Results: There were 34 cases in the LVSI-positive group and 145 cases in the negative group. The maximum transverse diameter in sagittal position, myometrial invasion, interruption of the uterine JZ, serous surface, uterine appendages, cervical stromal invasion, lymph node enlargement, and their DWI and ADC values were statistically significant between the two groups (P < 0.05). In multivariate logistic regression analysis, lymph node enlargement (P = 0.001) and ADC value (P = 0.041) were identified as independent risk factors for positive LVSI. Conclusion: Lymph node enlargement and reduced ADC values (<0.767*10-3mm2/s) in MR imaging are of high value in predicting the occurrence of LVSI in patients with EC and can be used as an important reference for preoperative clinical diagnostic and therapeutic decisions for patients.

Uterine Tumor Resembling Ovarian Sex Cord Tumors (UTROSCT): Two Case Reports of the Rare Uterine Neoplasm with Literature Review

Introduction: Uterine tumors resembling ovarian sex cord tumors (UTROSCTs) are rare neoplasms with unknown etiology. This type of tumor has low malignant potential and mostly manifests as a benign clinical course. Materials and Methods: This article analyzes the case data, clinical manifestations, and histopathological characteristics of two cases of UTROSCT, and reviews the relevant literature. The diagnosis of UTROSCT is mainly based on histopathological examination. The histological characteristics of granulosa and Sertoli cell tumours are similar to the ovary under the microscope. These cases' clinical and radiological (MRI) findings have also been discussed. Results: The sex cord components are mixed in different proportions. The immunohistochemistry is diverse and can express sex cord markers together with both epithelial and smooth muscle markers. Both two cases revealed the signs of intratumoral cystic degeneration, intratumoral hemorrhage, and necrosis under MRI. These MRI features were helpful to prompt UTROSCT, which is histologically similar to granular cell tumors and is conducive to the differential diagnosis. Conclusion: The current recommended treatment is total hysterectomy, but its biological behavior is not yet clear, and long-term follow-up is needed.

Thermal Imaging Techniques for Breast Screening - A Survey

Breast cancer is the second leading cause of cancer death among women preceded by cervix cancer. It has been reported that at the early stage of detection there is 85% chance of getting cured, whereas only 10% chance at later stage diagnosis. The current screening modalities are expensive, they have intricate imaging measures and they are unhealthy due to radiation exposure. Therefore, a screening tool that is non-invasive, has no connection with the body, free from radiation, such as Medical Thermography is necessary. It is reported that the sensitivity and specificity of medical thermography are high largely in dense breast tissues. The clinical interpretation primarily depends on the asymmetrical analysis of these thermograms subjectively. The appearance of an asymmetric thermal image may indicate the pathological conditions. For earlier detection of breast cancer, it is essential to identify the advanced methods in image processing techniques which enhance the significance of diagnostics. In that analysis, the required breast region is unglued from the background image. The segmented image is separated into symmetrical left and right breast tissues. The statistical and histogram features extracted from both regions are used to identify the abnormal thermograms using machine learning algorithms. From literature, it is reported that the thermal images are inherently low contrast images and have low single to noise ratio. Moreover, they are amorphous in nature and no clear edges are seen. The difficulty lies in the detection of lower breast boundaries and inframammary folds. So, in general, the first attempt is made in improving the signal to noise ratio and contrast of the image which helps to extract the true regions of breast tissues. Then, asymmetry analysis of the normal and abnormal breast tissues is performed using different techniques. This work demonstrates the review of a few image processing methods or the development which are elaborated in the detection of breast cancer from thermal images.

Recognition of Cervical Precancerous Lesions Based on Probability Distribution Feature Guidance

Introduction: Cervical cancer is a high incidence of cancer in women and cervical precancerous screening plays an important role in reducing the mortality rate. Methods: In this study, we proposed a multichannel feature extraction method based on the probability distribution features of the acetowhite (AW) region to identify cervical precancerous lesions, with the overarching goal to improve the accuracy of cervical precancerous screening. A k-means clustering algorithm was first used to extract the cervical region images from the original colposcopy images. We then used a deep learning model called DeepLab V3+ to segment the AW region of the cervical image after the acetic acid experiment, from which the probability distribution map of the AW region after segmentation was obtained. This probability distribution map was fed into a neural network classification model for multichannel feature extraction, which resulted in the final classification performance. Results: Results of the experimental evaluation showed that the proposed method achieved an average accuracy of 87.7%, an average sensitivity of 89.3%, and an average specificity of 85.6%. Compared with the methods that did not add segmented probability features, the proposed method increased the average accuracy rate, sensitivity, and specificity by 8.3%, 8%, and 8.4%, respectively. Conclusion: Overall, the proposed method holds great promise for enhancing the screening of cervical precancerous lesions in the clinic by providing the physician with more reliable screening results that might reduce their workload.

CERVIXNET: An Efficient Approach for the Detection and Classifications of the Cervigram Images Using Modified Deep Learning Architecture

Introduction: The earlier detection of cervical cancer in women patients can save human life. This article proposes a novel methodology for detecting abnormal cervigram images from healthy cervigram images and segments the cancer regions in the abnormal cervigram images using the deep learning method. The conventional deep learning architecture has been modified into the proposed CervixNet architecture to improve the cervical cancer detection rate. Methods: This methodology is constituted of a training and testing process, where the training process generates the training sequences individually for healthy cervigram images and the cancer case cervigram images. The testing process tests the cervigram images into either a healthy or cancer cases using the training sequences generated through the training process. During the testing process of the proposed system, the cancer segmentation algorithm was applied on the abnormal cervigram image to detect and segment the pixels belonging to cancer. Finally, the performance has been carried out on the segmented cancer cervical images for the ground truth images. This proposed methodology has been evaluated on the cervigrams on IMODT and Guanacaste databases. Its performance has been analyzed concerning cancer pixel sensitivity, cancer pixel specificity and cancer pixel accuracy. Results: This research work obtains 98.69% Cancer Pixel Sensitivity (CPS), 98.76% Cancer Pixel Specificity (CPSP), and 99.27% Cancer Pixel Accuracy (CPA) for the set of cervigram images in the IMODT database. This research work obtains 99.22% CPS, 99.03% CPSP, and 99.01% CPA for the set of cervigram images in Guanacaste database. Conclusion: These experimental results of the proposed work have been significantly compared with the state-of-the-art methods and show the significance and novelty of the proposed works.

Fallopian Tube Leiomyoma Presenting as a Huge Abdominopelvic Cystic Mass: A Case Report and Literature Review

Introduction:: Fallopian tube leiomyoma is an uncommon, benign gynecologic tumor that originates from the smooth muscle of the fallopian tube or vascular cells supplying the fallopian tube. Case Presentation:: In this study, we report a case of a patient with fallopian tube leiomyoma. What makes this instance even more unique is the association of the leiomyoma with cystic degeneration, manifesting as a large abdominopelvic cystic mass. CT scan suspected that the mass might be an ovarian cystadenoma. However, ultrasonography, a widely used diagnostic tool, effectively assisted the clinicians in confidently ruling out the possibility that the tumor was originating from the ovaries. Ultimately, the patient underwent exploratory laparoscopy and the pathologic diagnosis was fallopian tube leiomyoma with cystic degeneration. To our knowledge, no instance of a fallopian tube leiomyoma of this size with cystic degeneration has been reported. Thus, it is worth mentioning. Conclusion:: In summary, fallopian tube leiomyomas are classified as uncommon benign gynecologic tumors, which pose challenges in clinical diagnosis. The combined use of multiple imaging modalities may be more helpful in the proper diagnosis of this disease entity.

Histogram Feature Analysis of Tumor Body on Diffusion-weighted MR Imaging in Differentiation between Granulosa Cell Tumors and Other Sex-cord Tumors in Ovary: Comparison with Histological Results

Objective:: We aimed to differentiate granulosa cell tumors (GCT) from other ovarian sex-cord tumors (OSCs) based on feature analysis of the tumor body on MR imaging. Methods:: We retrospectively enrolled 27 patients with pathologically proven sex-cord tumours (14 GSTs, 8 fibromas, 4 fibrothecomas, and 1 sclerosing stromal tumour) from our institution. All MRI examinations were performed at least one month prior to surgery. MR image features were recorded by two radiologists with consensus readings. Histogram analysis was performed using FeAture Explorer software. The differences in histogram parameters between GCT (38.1 ± 14.6 years) and OSC (43.7 ± 18.0 years) groups were compared. Fourteen randomly selected cellular-type myomas who also underwent MRI in our hospital were considered as the control group. The intra-operator consistency of ADC value was evaluated across measurements twice. Results:: The repeatability of conventional ADC measurements on the tumor body was good. The values of ADC-mean, ADC-min, and ADC-max significantly differed across three groups (p < 0.001). The histogram variance on DWI, histogram percentage on T2WI, and ADC min showed the best discriminative performance in determining GCTs from other OSCs with an area under the receiver operator curve (AUC) of 0.997, 0.882, and 0.795, respectively. The histogram variance on DWI yielded a sensitivity of 92.3%, a specificity of 100%, and an accuracy of 96.6% in discriminating GSTs from other OSCs. Conclusion:: In the present study, feature analysis of tumor body MR imaging has helped to differentiate GST from OSC with better performance than conventional ADC measurements.

Endometrial Adenofibroma in a Patient Receiving Toremifene: A Case Report

Introduction: Adenofibroma is a rare benign Müllerian mixed tumor composed of epithelial and mesenchymal cells. This tumor may occasionally be associated with toremifene therapy which is used as an adjuvant drug for breast cancer. Case Presentation: We describe a case of a 55-year-old woman with adenofibroma of the endometrium. This patient was receiving toremifene after surgery and neoadjuvant chemotherapy for breast cancer. She underwent a total abdominal hysterectomy and bilateral salpingectomy. There was no evidence of tumor residual or recurrence at 32 months of MRI follow-up. Conclusion: In conclusion, we report a rare case of endometrial adenofibroma in a patient receiving toremifene. It must be borne in mind that long-term toremifene therapy may increase the frequency of endometrial neoplasms.

MBLEformer: Multi-Scale Bidirectional Lesion Enhancement Transformer for Cervical Cancer Image Segmentation

Background: Accurate segmentation of lesion areas from Lugol's Iodine Staining images is crucial for screening pre-cancerous cervical lesions. However, in underdeveloped regions lacking skilled clinicians, this method may lead to misdiagnosis and missed diagnoses. In recent years, deep learning methods have been widely applied to assist in medical image segmentation. Objective: This study aims to improve the accuracy of cervical cancer lesion segmentation by addressing the limitations of Convolutional Neural Networks (CNNs) and attention mechanisms in capturing global features and refining upsampling details. Methods: This paper presents a Multi-Scale Bidirectional Lesion Enhancement Network, named MBLEformer, which employs the Swin Transformer encoder to extract image features at multiple stages and utilizes a multi-scale attention mechanism to capture semantic features from different perspectives. Additionally, a bidirectional lesion enhancement upsampling strategy is introduced to refine the edge details of lesion areas. Results: Experimental results demonstrate that the proposed model exhibits superior segmentation performance on a proprietary cervical cancer colposcopic dataset, outperforming other medical image segmentation methods, with a mean Intersection over Union (mIoU) of 82.5%, accuracy, and specificity of 94.9% and 83.6%. Conclusion: MBLEformer significantly improves the accuracy of lesion segmentation in iodine-stained cervical cancer images, with the potential to enhance the efficiency and accuracy of pre-cancerous lesion diagnosis and help address the issue of imbalanced medical resources.

Differentiation of Endometriomas from Hemorrhagic Cysts at Magnetic Resonance: The Role of Quantitative Signal Intensity Measurements

Background: Endometriomas and functional hemorrhagic cysts (FHCs) are a common gynecological encounter. Objective: This study aimed to assess the diagnostic efficiency of magnetic resonance imaging (MRI) using signal intensity measurements in differentiating endometriomas from FHCs. Methods: Forty-six patients who underwent pelvic MRI examinations (endometriomas, n=28; FHCs, n=18) were retrospectively included. The “T2 shading” sign was evaluated subjectively and quantitatively by measuring the T1-T2 signal intensity difference and calculating the percentage of signal decrease between T1 and T2-weighted sequences. The resulted values, along with the measurement of the Apparent Diffusion Coefficient (ADC) and the signal intensity on three diffusion- weighted sequences (DWI) (b50, b400, and b800), were compared between groups by using the Mann–Whitney U test. Also, the receiver operating characteristic analysis was performed for the statistically significant results (P<0.016), and the area under the curve (AUC) was also calculated. Results: The two quantitative assessment methods showed similar efficiency in detecting endometriomas (P<0.001; sensitivity, 100%; specificity, 81.82%; AUC>0.86), outperforming the classic subjective evaluation of the “T2 shading” sign (sensitivity, 92.86%; specificity, 66.67%). ADC (P=0.52) and DWI measurements (P=0.49, P=0.74, and P=0.78) failed to distinguish between the two entities. Conclusion: The quantitative analysis and interpretation of the “T2 shading” sign can significantly improve the differential diagnosis between endometriomas and FHCs.

Sonographic and Clinicopathological Characterization of Struma Ovarii: A Retrospective Analysis for Enhanced Preoperative Diagnosis

Introduction: Struma ovarii (SO) is a rare ovarian teratoma composed predominantly of thyroid tissue, often misdiagnosed due to its non-specific clinical manifestations and low prevalence. Methods: The ultrasound and clinical features of 16 histologically confirmed cases of SO (mean age 45 ± 10 years) were analyzed. Key ultrasound parameters evaluated included tumor size, internal echo patterns, calcification, blood flow (Adler grading), and pelvic effusion. Results: Half of patients with SO have been found to be postmenopausal women over 50 years of age, and that most tumors are discovered incidentally during routine examination. The large cystic components with regular margins, accompanied by calcified and vascularized solid elements, are ultrasound characteristics of SO. In particular, the presence of calcification and distinct vascular patterns on Doppler imaging (as per Adler classification) has been identified as a critical marker distinguishing SO from other adnexal masses. Discussion: Compared to existing SO research, this study has found the ultrasound characteristics of SO to mostly manifest as a large cystic echo, regular boundaries, and calcification. At the same time, compared to the existing imaging techniques, such as CT and MRI, characteristic ultrasonography has been found to be a good complement to the diagnosis of SO. Conclusion: When an adnexal tumor is classified as O-RADS 3-5 and exhibits features, such as a large cystic echo, regular boundaries, and calcification, SO should be considered in the differential diagnosis. These findings can enhance the accuracy of preoperative assessment, facilitate individualized surgical planning, and contribute to improved clinical management by reducing the likelihood of misdiagnosis.