iRadiology最新文献

{"title":"Application of Artificial Intelligence in Medical Imaging: Current Status and Future Directions","authors":"Yixin Yang,&nbsp;Lan Ye,&nbsp;Zhanhui Feng","doi":"10.1002/ird3.70008","DOIUrl":"https://doi.org/10.1002/ird3.70008","url":null,"abstract":"<p>A revolution in medical diagnosis and treatment is being driven by the use of artificial intelligence (AI) in medical imaging. The diagnostic efficacy and accuracy of medical imaging are greatly enhanced by AI technologies, especially deep learning, that performs image recognition, feature extraction, and pattern analysis. Furthermore, AI has demonstrated significant promise in assessing the effects of treatments and forecasting the course of diseases. It also provides doctors with more advanced tools for managing the conditions of their patients. AI is poised to play a more significant role in medical imaging, especially in real-time image processing and multimodal fusion. By integrating multiple forms of image data, multimodal fusion technology provides more comprehensive disease information, whereas real-time image analysis can assist surgeons in making more precise decisions. By tailoring treatment regimens to each patient's unique needs, AI enhances both the effectiveness of treatment and the patient experience. Overall, AI in medical imaging promises a bright future, significantly enhancing diagnostic precision and therapeutic efficacy, and ultimately delivering higher-quality medical care to patients.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 2","pages":"144-151"},"PeriodicalIF":0.0,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143861523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Utilizing Radiomics as Predictive Factor in Brain Metastasis Treated With Stereotactic Radiosurgery: Systematic Review and Radiomic Quality Assessment","authors":"Abdulrahman Umaru,&nbsp;Hanani Abdul Manan,&nbsp;Ramesh Kumar Athi Kumar,&nbsp;Siti Khadijah Hamsan,&nbsp;Noorazrul Yahya","doi":"10.1002/ird3.70007","DOIUrl":"https://doi.org/10.1002/ird3.70007","url":null,"abstract":"<p>Radiomics and machine learning (ML) are increasingly utilized to predict treatment response by uncovering latent information in medical images. This study systematically reviews radiomics studies on brain metastasis treated with stereotactic radiosurgery (SRS) and quantifies their radiomic quality score (RQS). A systematic search on Scopus, Web of Science, and PubMed was conducted to identify original studies on radiomics for predicting treatment response, adhering to predefined patient, intervention, comparator, and outcome (PICO) criteria. No restrictions were placed on language or publication date. Two independent reviewers assessed eligible studies, and the RQS was calculated based on Lambin’s guidelines. The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020 guidelines were followed. Seventeen studies involving 2744 patients met the inclusion criteria out of 200 identified. All studies were retrospective and utilizing various MRI scanners models with different field strength. The average RQS across studies was low (39.2%), with a maximum score of 19 points (52.7%). Radiomic-based models demonstrated superior predictive accuracy compared to clinical or visual assessment, with AUC values ranging from 0.74 to 0.92. Integration of clinical features such as Karnofsky performance status, dose, and isodose line further improved model performance. Deep learning models achieved the highest predictive accuracy, with AUC of 0.92. Radiomics demonstrate significant potential in predicting treatment outcomes with high accuracy, offering opportunities to advance personalized management for BM. To facilitate clinical adoption, future studies must prioritize adherence to standardized guidelines and robust model validation to ensure reproducibility.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 2","pages":"132-143"},"PeriodicalIF":0.0,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143861743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implications of Artificial Intelligence in Stroke Intervention and Care","authors":"Jyoti Yadav,&nbsp;Aditya More,&nbsp;Bijoyani Ghosh,&nbsp;Doni Sinha,&nbsp;Nikita Chavane,&nbsp;Anita Kumari,&nbsp;Aishika Datta,&nbsp;Anupom Borah,&nbsp;Pallab Bhattacharya","doi":"10.1002/ird3.70005","DOIUrl":"https://doi.org/10.1002/ird3.70005","url":null,"abstract":"<p>Artificial intelligence (AI) technology is expanding at a rapid pace, offering means of improving the precision of judgments made by medical professionals. AI-driven machine learning (ML) facilitates rapid and effective data processing for diagnosis and treatment of different diseases including stroke. This technology has vastly improved the patient classification based on their predicted stroke outcome. It helps in quicker decision-making, improves diagnosis precision, and enhances patient care. ML techniques have occasionally been applied extensively to address complex issues related to stroke such as the prediction of stroke prevalence at an early stage. The ability of deep learning (DL) algorithms, a crucial element of AI, is becoming popular in stroke imaging analysis because it automatically extracts features without requiring domain expertise. In the preclinical setup for stroke studies, ML/DL models are commendably used for the detection of vascular thrombi, stroke core, and penumbra size, to identify artery occlusion, compute perfusion maps, detect intracranial hemorrhage (ICH), prediction of infarct, assessing the severity of hemorrhagic transformation, and forecasting patient outcomes. The robust automatic data processing, excellent generalization, self-learning, and precise decision-making abilities of such models have contributed immensely to the advancement of stroke therapy. In the preclinical setup, the time-investing behavioral studies of the animals are also effectively analyzed by AI based algorithms. Understanding the algorithms and models based on AI is yet to be simplified for its application in stroke therapy in present clinical settings, thus, in the present review attempts have been made to present it in a simplified manner to facilitate translation.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 2","pages":"115-131"},"PeriodicalIF":0.0,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143861645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Low-Intensity Focused Ultrasound Ameliorates Cisplatin-Induced Cognitive Impairment by Attenuating Hippocampal Neuroinflammation and Enhancing Synaptic Plasticity in Rats","authors":"Xiaowei Han,&nbsp;Hagiwara Akifumi,&nbsp;Pin Lv,&nbsp;Jiahuan Liu,&nbsp;Xiaowei Huang,&nbsp;Renyuan Liu,&nbsp;Xiaojing Long,&nbsp;Yang Liu,&nbsp;Jiangong Zhang,&nbsp;Guolin Ma,&nbsp;Bing Zhang","doi":"10.1002/ird3.70003","DOIUrl":"https://doi.org/10.1002/ird3.70003","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Platinum can cause chemotherapy-related cognitive impairment. Low-intensity focused ultrasound (LIFUS) is a promising noninvasive physical stimulation method with a unique advantage in neurological rehabilitation. We aimed to investigate whether LIFUS can alleviate cisplatin-induced cognitive impairment in rats and explore the related neuropathological mechanisms.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;After confirming the target position for LIFUS treatment in 18 rats, 64 rats were randomly divided into four groups: control, model, sham, and LIFUS groups. Before and after LIFUS treatment, detailed biological behavioral assessments and magnetic resonance imaging were performed. Finally, the rats were euthanized, and relevant histopathological and molecular biological experiments were conducted and analyzed.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;In the Morris water maze, the model group showed fewer platform crossings (1.25 ± 0.93 vs. 5.69 ± 1.58), a longer escape latency (41.65 ± 36.55 s vs. 6.38 ± 2.11 s), and a lower novel object recognition index (29.77 ± 11.83 vs. 83.69 ± 5.67) than the control group. LIFUS treatment improved these metrics, with more platform crossings (3.13 ± 0.34), a higher recognition index (65.58 ± 8.71), and a shorter escape latency (6.45 ± 2.27 s). Longitudinal analysis of the LIFUS group further confirmed these improvements. Neuroimaging revealed significant differences in diffusion tensor imaging metrics of specific brain regions pre- and post-LIFUS. Moreover, neuropathology showed higher dendritic spine density, less myelin loss, fewer apoptotic cells, more synapses, and less mitochondrial autophagy after LIFUS treatment. The neuroimaging indicators were correlated with behavioral improvements, highlighting the potential of LIFUS for alleviating cognitive impairment (as demonstrated through imaging and analysis). Our investigation of the molecular biological mechanisms revealed distinct protein expression patterns in the hippocampus and its subregions. In the model group, glial fibrillary acidic protein (GFAP) and ionized calcium-binding adaptor molecule 1 (IBA1) expression levels were elevated across the hippocampus, whereas neuronal nuclei (NeuN) expression was reduced. Subregional analysis revealed higher GFAP and IBA1 and lower NeuN, especially in the dentate gyrus subregion. Moreover, positive cell areas were larger in the cornu ammonis (CA)1, CA2, CA3, and dentate gyrus regions. In the CA2 and CA3, significant differences among the groups were observed in GFAP-positive cell counts and areas, and there were variations in NeuN expression.&lt;/p&gt;\u0000 &lt;/s","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 2","pages":"152-167"},"PeriodicalIF":0.0,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143861570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced Optical Microscopic Imaging Techniques for Imaging Amyloid Beta and Deciphering Alzheimer's Disease Pathogenesis","authors":"Shiju Gu,&nbsp;Chongzhao Ran","doi":"10.1002/ird3.70002","DOIUrl":"https://doi.org/10.1002/ird3.70002","url":null,"abstract":"<p>Alzheimer's disease (AD) is a neurodegenerative disease characterized by a progressive decline in cognitive functions. Given that AD undermines the quality of life for millions and has an extended asymptomatic period, exploring the full AD pathogenesis and seeking the optimal therapeutic solution have become critical and imperative. This allows researchers to intervene, delay, and potentially prevent AD progression. Several clinical imaging methods are utilized routinely to diagnose and monitor AD, such as magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), positron emission tomography (PET), and single photon emission computed tomography (SPECT). Nevertheless, due to their intrinsic drawbacks and restrictions, such as radiation concerns, high cost, long acquisition time, and low spatial resolution, their applications in AD research are limited, especially at the cellular and molecular levels. In contrast, optical microscopic imaging methods overcome these limitations, offering researchers a variety of approaches with distinct advantages to explore AD pathology on diverse models. In this review, we provide a comprehensive overview of commonly utilized optical microscopic imaging techniques in AD research and introduce their contributions to image amyloid beta (Aβ) species. These techniques include fluorescence microscopy (FM), confocal microscopy (CM), two-photon fluorescence microscopy (TPFM), super-resolution microscopy (SRM), expansion microscopy (ExM), and light-sheet fluorescence microscopy (LSFM). In addition, we introduce some related topics, such as the development of near-infrared (NIR) Aβ probes, the Aβ plaque hypothesis, and Aβ oligomer hypothesis, and the roles of microglia and astrocytes in AD progression. We believe optical microscopic imaging methods continue to play an indispensable role in deciphering the full pathogenesis of AD and advancing therapeutic strategies.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 2","pages":"95-114"},"PeriodicalIF":0.0,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143861741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aorta–Right Atrial Tunnel in Conjunction With Patent Ductus Arteriosus and Atrial Septal Defect","authors":"Bo Wang,&nbsp;Rongpin Wang","doi":"10.1002/ird3.70001","DOIUrl":"https://doi.org/10.1002/ird3.70001","url":null,"abstract":"<p>Congenital aorta–right atrial tunnel (ARAT) is a rare congenital cardiovascular malformation characterized by an abnormal tunnel-like connection between the aorta and the right atrium. Patients with ARAT frequently have other congenital heart malformations and require diagnosis through a variety of imaging examinations. We report a 1-month-old female infant with multiple congenital cardiac malformations who was diagnosed with ARAT using low-dose multislice spiral computed tomography because echocardiography was unclear.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 2","pages":"180-182"},"PeriodicalIF":0.0,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143861380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"White Matter Hyperintensities: Cerebral Small-Vessel Diseases and White Matter Microstructural Impairments","authors":"Hui Huang,&nbsp;Wei Song,&nbsp;Pengyu Wang,&nbsp;Ye Zhu,&nbsp;Lei Zheng,&nbsp;Chenzhen Shen,&nbsp;Hui Xu,&nbsp;Jianfeng Qiu","doi":"10.1002/ird3.121","DOIUrl":"https://doi.org/10.1002/ird3.121","url":null,"abstract":"<p>White matter hyperintensities (WMH) are very widespread in older adults and are imaging features of both cerebral small-vessel disease and white matter microstructural impairments. Recent studies have demonstrated a close association between WMH and some common diseases in older adults, including Alzheimer's disease and hypertension. Thus, studies of WMH are important for avoiding the occurrence of these diseases and improving the health status of older adults. This review summarizes the literature relating to WMH in terms of epidemiology, clinical presentation, pathogenesis, imaging features, and therapy. It also analyzes the limitations of present studies and provides perspectives on future directions.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 1","pages":"5-25"},"PeriodicalIF":0.0,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.121","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143521980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing Contrast-Enhanced Magnetic Resonance Neurography of the Brachial Plexus With Delayed Scanning","authors":"Jun Xu,&nbsp;Xiaoli Hu,&nbsp;Xiaoyun Su,&nbsp;Shen Gui,&nbsp;Ziqiao Lei,&nbsp;Xiaoming Liu,&nbsp;Xiangzhi Zhou,&nbsp;Lixia Wang,&nbsp;Wenjun Wu,&nbsp;Xiangchuang Kong","doi":"10.1002/ird3.120","DOIUrl":"https://doi.org/10.1002/ird3.120","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Contrast-enhanced magnetic resonance neurography (ceMRN) can enhance brachial plexus visualization and quality of imaging. However, the interval between contrast injection and scanning that provides the highest-quality images is not known.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Fifteen patients underwent brachial plexus imaging using the 3D T2-NerveView sequence with a scanning duration of 5 min. A consecutive six-phase scan was initiated immediately at the start of contrast agent injection. Subsequently, all patients' images were classified into six groups according to the phases: group A (phase 1, delay 0 min), group B (phase 2, delay 5 min), group C (phase 3, delay 10 min), group D (phase 4, delay 15 min), group E (phase 5, delay 20 min), and group F (phase 6, delay 25 min). The image quality in each group was assessed based on nerve signal (signal_nerve), muscle signal (signal_muscle), lymph node signal (signal_{lymph node}), background noise (BN), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and subjective score.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Signal_nerve, signal_muscle, BN, and SNR did not significantly differ among the six groups (<i>p</i> &gt; 0.05). However, significant differences (<i>p</i> &lt; 0.05) were observed in signal_{lymph node} (<i>F</i> = 16.067), CNR (<i>F</i> = 9.495), and subjective score (<i>χ</i>² = 23.586). As the scanning delay increased, signal_{lymph node} intensity gradually increased whereas the CNR gradually decreased. The subjective score was significantly higher in groups B (4.83 ± 0.24), C (4.90 ± 0.21), D (4.87 ± 0.30), E (4.83 ± 0.31), and F (4.83 ± 0.31) than in group A (4.47 ± 0.30).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>We recommend performing brachial plexus ceMRN 5 min after contrast injection. With this delay, the brachial plexus can be visualized optimally with minimal interference from background signals.</p>\u0000 </section>\u0000 </div>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 2","pages":"168-175"},"PeriodicalIF":0.0,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.120","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143861667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biphasic Synovial Sarcoma in the Abdominal Cavity","authors":"Yubo Wang,&nbsp;Jiageng Li,&nbsp;Yang Fu,&nbsp;Bin Yang","doi":"10.1002/ird3.118","DOIUrl":"https://doi.org/10.1002/ird3.118","url":null,"abstract":"<p>A 63-year-old man was admitted to the hospital with a &gt; 1-year history of repeated acid reflux and belching and a 1-month history of an abdominal mass. On admission, the patient was in good condition, and his vital signs were stable. Laboratory examinations revealed no significant abnormalities. Abdominal computed tomography (CT) revealed a soft tissue mass with uneven density, measuring approximately 13.3 cm × 9.0 cm and extending from the right abdomen into the pelvic cavity. Enhanced CT showed mild uneven enhancement of the mass during the arterial phase, with significant wall enhancement and visible septa. Significant enhancement of the solid components within the mass was observed during the venous and delayed phases with a CT value of approximately 50.3 HU, indicating “progressive enhancement.” Curved blood vessels were visible around the mass, and the surrounding structures were compressed and displaced (Figure 1). During the operation, a tumor measuring approximately 15 cm × 10 cm was observed in the lower right retroperitoneum. It was tightly adhered to the small intestine, ascending colon, and greater omentum, and showed invasive growth. No metastasis was found in the liver, gallbladder, or stomach during the surgical exploration. The pathological diagnosis was synovial sarcoma (SS) with extensive necrosis. Immunohistochemistry revealed epithelial–mesenchymal biphasic differentiation of the tumor cells.</p><p>SS is a rare malignant soft tissue tumor originating from primitive mesenchymal cells. It most commonly affects the limb joints, particularly those of the lower limbs. Cases of SS arising from the abdominal cavity, especially involving the ascending colon and small intestine, are rare and prone to preoperative misdiagnosis. This case exhibited unique imaging features, including significant arterial phase enhancement of the tumor wall, consistent with progressive enhancement. Magnetic resonance imaging further revealed characteristic signs, such as the “triple signal sign,” “liquid–liquid plane,” and “grape bowl sign,” which can help differentiate SS from other abdominal tumors.</p><p><b>Yubo Wang:</b> writing–original draft (lead), resources (equal). <b>Jiageng Li:</b> writing–original draft (equal). <b>Yang Fu:</b> writing–original draft (equal). <b>Bin Yang:</b> resources (equal), writing–review and editing (lead).</p><p>The authors have nothing to report.</p><p>The patient provided written informed consent at the time of entering this study.</p><p>The authors declare no conflicts of interest.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 2","pages":"178-179"},"PeriodicalIF":0.0,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.118","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143861447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Imaging Features of Rare Ovarian Adenomyoma","authors":"Haitao Liu,&nbsp;Weishun Lan","doi":"10.1002/ird3.117","DOIUrl":"https://doi.org/10.1002/ird3.117","url":null,"abstract":"<p>A 42-year-old single woman presented to the Department of Gynecology with irregular vaginal bleeding with blood clots for the previous 2 months. She had no abdominal pain. Since the onset of symptoms, she had remained cheerful, and her general physical condition had not changed significantly. She reported no history of sexual activity, surgical procedures, or trauma. Tumor markers, including alpha-fetoprotein, carcinoembryonic antigen, CA19-9, and CA15-3, were within normal limits, with the exception of a mildly elevated serum CA125 concentration of 37.34 U/mL. All other laboratory tests returned normal results. Magnetic resonance imaging revealed a mass with both cystic and solid components in the left adnexal area. The mass was Grade 3 according to the Ovarian-Adnexal Reporting and Data System. Its features are shown in Figure 1. There was no evidence of invasion of the surrounding organs or retroperitoneal lymphadenopathy. The final pathological diagnosis was ovarian adenomyoma as evidenced by tubal metaplasia of the endometrium with some edema (Figure 2). The patient was discharged from the hospital in good condition after surgery.</p><p>Ovarian adenomyoma, a rare benign tumor of the female reproductive system, was first reported in 1981. The mechanism of the development of extrauterine adenomyomas is unclear. The main symptom of ovarian adenomyomas is abdominal pain, which may be related to endometriosis. The imaging features of ovarian myomas vary considerably, the differential diagnosis being granulosa cell tumor, fibrothecoma, and cystadenoma. The following features support a diagnosis of ovarian adenomyoma. First, the presence of endometriosis or a history of pelvic surgery, including cesarean section. Second, the solid component of the mass shows marked enhancement. Finally, the diffusion sequence of the mass is not limited.</p><p><b>Haitao Liu:</b> writing–original draft (Lead). <b>Weishun Lan:</b> writing–review and editing.</p><p>Approval from our institutional ethics committee was not required because this was a retrospective observational study.</p><p>The patient provided written informed consent at the time of entering this study.</p><p>The authors declare no conflicts of interest.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 2","pages":"176-177"},"PeriodicalIF":0.0,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.117","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143861749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}