iRadiology最新文献

{"title":"Prenatal Ultrasound and Magnetic Resonance Imaging Features and Postnatal Outcomes of Congenital Hepatic Hemangioma: A Retrospective Analysis","authors":"Luyao Yang,&nbsp;Jianbo Teng,&nbsp;Xinhong Wei","doi":"10.1002/ird3.70021","DOIUrl":"https://doi.org/10.1002/ird3.70021","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Congenital hepatic hemangioma (CHH) is a rare benign vascular tumor that occurs prenatally. However, only a few cases have been summarized and evaluated for the prenatal and postnatal imaging features of CHH, and no studies have conducted long-term follow-up on it. This study aimed to explore the ultrasound and magnetic resonance features, growth patterns, and clinical outcomes of CHH.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Thirty-six pregnancies with a prenatal fetal diagnosis and postnatal diagnosis of CHH were studied. CHHs were grouped into those with a diameter ≥ 4 cm and those with a diameter &lt; 4 cm according to the largest diameter. Fisher's exact test was used to compare the imaging characteristics between the groups. The volume of CHHs was measured at each follow-up visit to plot the growth pattern of the tumors, and the volume of CHHs was compared before and after birth using a rank sum test analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Thirty-three cases of CHHs were confirmed by postnatal imaging, and three were confirmed by a biopsy. Mixed echoes were more common in the diameter ≥ 4 cm group than in the diameter &lt; 4 cm group (<i>p</i> = 0.026). Complications were more likely to occur in the large-diameter group. Eighteen (54.5%) cases were classified as rapidly involuting congenital hemangioma, nine (27.3%) as partially involuting congenital hemangioma, and two (6.1%) as noninvoluting congenital hemangioma. A new type of CHH was identified in which four (12.1%) cases continued to proliferate after birth and spontaneously subsided in subsequent months. The CHH volume decreased with age and was significantly decreased at 9 months postnatal compared to birth (<i>p</i> = 0.001).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>This study showed the imaging features of CHH were associated with the lesion size. Based on postnatal follow-up, a new type of CHH was identified. If there are no complications at birth in CHH cases, a good prognosis is indicated.</p>\u0000 </section>\u0000 </div>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 3","pages":"214-221"},"PeriodicalIF":0.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70021","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519819","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":"A Clearer Picture: MRI's Expanding Role in High-Risk Pregnancy Care","authors":"Su-Zhen Dong,&nbsp;Fu-Tsuen Lee,&nbsp;Lianxiang Xiao,&nbsp;Liqun Sun","doi":"10.1002/ird3.70023","DOIUrl":"https://doi.org/10.1002/ird3.70023","url":null,"abstract":"&lt;p&gt;In recent decades, maternal–fetal medicine has undergone substantial advancements in the management of high-risk pregnancies. These include enhanced prenatal screening and diagnosis facilitated by innovations in ultrasound imaging, as well as the advances in fetal medical and interventional therapies informed by the deeper understanding of pathophysiological mechanisms underlying fetal and maternal disease processes. Collectively, these have contributed to measurable reductions in maternal and perinatal morbidity and mortality [&lt;span&gt;1&lt;/span&gt;]. However, the identification of certain fetal conditions using ultrasound remains challenging because of suboptimal acoustic windows, fetal positioning, maternal body habitus, and limited soft tissue contrast [&lt;span&gt;2&lt;/span&gt;]. These challenges can delay diagnosis and management, and potentially impact the timing of interventions, as well as the quality of prenatal counseling regarding the child's future health, development, and quality of life.&lt;/p&gt;&lt;p&gt;Recent advances in fetal magnetic resonance imaging (MRI) have emerged as a feasible alternative when ultrasound findings are inconclusive or limited. Fetal MRI offers superior soft tissue contrast which can enhance the characterization of complex fetal conditions. This was facilitated by the development of accelerated image acquisition techniques and motion-correction algorithms to reduce maternal breathing and fetal movement artifacts, thereby reducing scan times and improving the overall image quality [&lt;span&gt;3&lt;/span&gt;]. Therefore, fetal MRI could serve as a valuable adjunct to clinical assessment, optimizing prenatal management and facilitating targeted interventions in high-risk pregnancies.&lt;/p&gt;&lt;p&gt;This special issue explores the expanding role of fetal MRI in the diagnosis, prognosis, and planning of interventions in complex fetal conditions in high-risk pregnancies.&lt;/p&gt;&lt;p&gt;Fetal MRI offers enhanced anatomical resolution and tissue characterization of the developing fetal brain [&lt;span&gt;4&lt;/span&gt;]. Ren et al. provided a comprehensive review on the utility of fetal MRI on the diagnosis of congenital brain tumors including teratomas, astrocytomas, and choroid plexus tumors [&lt;span&gt;5&lt;/span&gt;]. Key findings include superior tissue contrast to characterize tumor morphology, volume, and mass effect, which may prompt additional investigations for associated pathologies, guide the timing of delivery for postnatal interventions, and aid prenatal counseling [&lt;span&gt;6&lt;/span&gt;]. Liu and Xiao presented a rare case of fetal periventricular nodular heterotopia identified by fetal MRI after ultrasound detection of a posterior fossa cyst [&lt;span&gt;7&lt;/span&gt;]. Fetal MRI detected a gray matter nodule in the right lateral ventricular wall leading to suspicion of fetal gray matter heterotopia, which was confirmed by brain MRI at 7 months of age with no associated abnormal neurological presentation. Although a neuronal migration disorder, these findings highlight some individuals may not ","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 3","pages":"188-190"},"PeriodicalIF":0.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70023","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519845","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":"Automated Color Coding in Musculoskeletal MR Imaging","authors":"Saavi Reddy Pellakuru,&nbsp;Sonal Saran,&nbsp;Syed Alam,&nbsp;Sameer Raniga,&nbsp;David Beale,&nbsp;Rajesh Botchu","doi":"10.1002/ird3.70022","DOIUrl":"https://doi.org/10.1002/ird3.70022","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Magnetic resonance imaging (MRI) is crucial in modern medical diagnostics, providing detailed insights into soft tissue structures and pathological changes. Traditional grayscale images can sometimes obscure critical details, complicating accurate interpretations. Automated color coding of the MRI signal intensities may enhance the visualization of various pathologies, potentially leading to improved diagnostic accuracy and image quality. This paper aims to explore the effectiveness of color-coded MR image reconstruction in enhancing both diagnostic precision and overall image quality in musculoskeletal MRI.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Two fellowship-trained musculoskeletal radiologists evaluated the images reconstructed with color coding, rating their diagnostic value, image quality, and visual appeal using a five-point Likert scale. To assess interrater reliability, Cohen's Kappa statistical analysis was performed. Additionally, descriptive statistics summarizing the Likert scores for diagnostic value, image quality, and visual appeal of the reconstructed images have been described.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Statistical analysis of the data revealed that the diagnostic value, image value, and visual appeal of the color-coded MR images were excellent in almost two-thirds of the data set. The minimum Likert score recorded was 3, signifying a good quality rating.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Our study shows positive results, supporting the efficiency of color-coded MR imaging in aiding the conventional gray scale MR imaging to improve its diagnostic efficiency.</p>\u0000 </section>\u0000 </div>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 3","pages":"248-252"},"PeriodicalIF":0.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70022","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519820","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":"Retroperitoneal Ectopic Pregnancy","authors":"Qingying Song,&nbsp;Dan Li","doi":"10.1002/ird3.70019","DOIUrl":"https://doi.org/10.1002/ird3.70019","url":null,"abstract":"<p>A 35-year-old woman with a history of regular menstruation presented with a positive urine pregnancy test and elevated blood human chorionic gonadotropin concentrations. Color Doppler ultrasound showed multiple slightly hyperechoic areas within the uterine cavity. She was admitted to the hospital with a preliminary outpatient diagnosis of “suspected molar pregnancy, pending further evaluation.” After electrocution and curettage, no villous tissue was identified, and postoperative human chorionic gonadotropin concentrations failed to decline. Pelvic MRI showed a round, thick-walled cystic mass in the anterior sacral region (Figure 1). Color Doppler ultrasound showed that the cystic mass contained a yolk sac, fetal bud, and fetal cardiac activity (Figure 2). Surgical pathology subsequently confirmed the presence of villous tissue, consistent with a diagnosis of ectopic pregnancy.</p><p><b>Qingying Song:</b> writing – original draft preparation (lead), writing – review and editing (lead). <b>Dan Li:</b> writing – original draft preparation (supporting), writing – review and editing (supporting).</p><p>The study was reviewed and approved by the Ethics Committee of Linyi Maternal and Child Health Hospital (QTL-YXLL-2023080).</p><p>Informed consent was waived because the patient’s information has been anonymized, which was approved by the ethics committee.</p><p>The authors declare no conflicts of interest.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 3","pages":"237-238"},"PeriodicalIF":0.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70019","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519818","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":"Value of Magnetic Resonance Spectroscopy for Examining Fetal Brain Development in Mid- to Late Pregnancy","authors":"Dejuan Shan,&nbsp;Yi Zhang,&nbsp;Maobo Wang,&nbsp;Yanyan Liu,&nbsp;Yudong Wang,&nbsp;Lianxiang Xiao","doi":"10.1002/ird3.70012","DOIUrl":"https://doi.org/10.1002/ird3.70012","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Magnetic resonance spectroscopy (MRS) represents a significant advancement in the noninvasive assessment of brain metabolism. MRS can provide valuable metabolic information and facilitate more accurate diagnoses of intrauterine fetal brain development than was previously possible. To obtain information regarding normal intrauterine fetal brain metabolism and to establish gestational age-specific reference values for normal fetal brain metabolites for subsequent use in MRS, we conducted MRS scans of normal fetal brains during mid- to late-term pregnancies, along with related processing.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>In this prospective study, MRS scans were conducted on 109 fetuses, with a total of 54 normal fetal brains enrolled on the basis of specific inclusion and exclusion criteria. We analyzed metabolic ratios, including the sum of N-acetylaspartate (NAA) and total N-acetylaspartate (tNAA), total choline (tCho), inositol (Ins), and total creatine (tCr), in relation to gestational age.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Gestational age was significantly correlated with specific metabolic ratios (Ins/tCr: <i>r</i> = −0.75, <i>p</i> &lt; 0.0001; tCho/tCr: <i>r</i> = −0.50, <i>p</i> &lt; 0.0001), especially tNAA/tCho (tNAA/tCho: <i>r</i> = 0.54, <i>p</i> &lt; 0.0001) and tNAA/Ins (<i>r</i> = 0.56, <i>p</i> &lt; 0.0001), providing a baseline for fetal brain metabolic assessment. Linear regression analysis was used to calculate regression lines for fetal brain metabolite ratios. Slopes were tested at <i>p</i> of 0.05.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The current findings confirmed a significant correlation between fetal brain metabolites and gestational age, supporting the feasibility of establishing standard values for these metabolites in fetal brain assessment.</p>\u0000 </section>\u0000 </div>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 3","pages":"209-213"},"PeriodicalIF":0.0,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144520148","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":"Fetal Gray Matter Heterotopia","authors":"Jiaojiao Liu,&nbsp;Lianxiang Xiao","doi":"10.1002/ird3.70010","DOIUrl":"https://doi.org/10.1002/ird3.70010","url":null,"abstract":"<p>A pregnant woman underwent fetal brain magnetic resonance imaging (MRI) following ultrasound detection of a posterior fossa cyst at 29 weeks' gestation. She presented with no relevant medical history and underwent a routine obstetric examination during pregnancy. The fetal head position, fetal cranial development, and limb development remained normal until 29 weeks. A fetal MRI examination showed a posterior fossa cyst, and another nodular gray matter signal was observed adjacent to the right lateral ventricle. Follow-up MRI at 31 weeks + 3 days showed no major changes (Figure 1). The patient successfully delivered a male neonate at 40 weeks' gestation. A brain MRI was performed at 7 months of age and confirmed the diagnosis of fetal gray matter heterotopia (GMH) (periventricular type) (Figure 2). He showed no neurological abnormalities such as epilepsy. Moreover, his skin manifestations were normal, and his growth and development were consistent with his monthly age.</p><p>Fetal GMH is a relatively uncommon congenital disorder that arises from impaired neuronal migration. The three main types of GMH are periventricular nodular heterotopia, subcortical heterotopia, and subcortical band heterotopia. The most common type is periventricular nodular heterotopia, as found in the present case. GMH can sometimes be accompanied by other abnormalities, such as ventriculomegaly, agenesis of the corpus callosum, and congenital heart disease. Fetal MRI is increasingly being used to diagnose fetal GMH because of its high soft tissue resolution. However, there have been few reports of pathological or postnatally confirmed fetal GMH.</p><p><b>Jiaojiao Liu:</b> writing – original draft (lead). <b>Lianxiang Xiao:</b> conceptualization (lead), supervision (lead).</p><p>This study was approved by Shandong Provincial Maternal and Child Research Ethics Approval (Approval No.: 2024-13).</p><p>The case was retrospectively analysed, the fetal and postnatal imaging data used were from previous medical records, and the images were anonymised, which does not pose a risk of compromising the patient's privacy. Therefore, informed consent was exempted.</p><p>This article belongs to a special issue (SI)—fetal imaging, maternal and children imaging. As the SI's guest editor, Professor Lianxiang Xiao is excluded from all the editorial decisions related to the publication of this article. The remaining author declares no conflicts of interest.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 3","pages":"231-233"},"PeriodicalIF":0.0,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144520070","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":"Performance Review of Meta LLaMa 3.1 in Thoracic Imaging and Diagnostics","authors":"Golnaz Lotfian,&nbsp;Keyur Parekh,&nbsp;Pokhraj P. Suthar","doi":"10.1002/ird3.70013","DOIUrl":"https://doi.org/10.1002/ird3.70013","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The integration of artificial intelligence (AI) in radiology has opened new possibilities for diagnostic accuracy, with large language models (LLMs) showing potential for supporting clinical decision-making. While proprietary models like ChatGPT have gained attention, open-source alternatives such as Meta LLaMa 3.1 remain underexplored. This study aims to evaluate the diagnostic accuracy of LLaMa 3.1 in thoracic imaging and to discuss broader implications of open-source versus proprietary AI models in healthcare.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Meta LLaMa 3.1 (8B parameter version) was tested on 126 multiple-choice thoracic imaging questions selected from <i>Thoracic Imaging: A Core Review</i> by Hobbs et al. These questions required no image interpretation. The model’s answers were validated by two board-certified diagnostic radiologists. Accuracy was assessed overall and across subgroups, including intensive care, pathology, and anatomy. Additionally, a narrative review introduces three widely used AI platforms in thoracic imaging: DeepLesion, ChexNet, and 3D Slicer.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>LLaMa 3.1 achieved an overall accuracy of 61.1%. It performed well in intensive care (90.0%) and terms and signs (83.3%) but showed variability across subgroups, with lower accuracy in normal anatomy and basic imaging (40.0%). Subgroup analysis revealed strengths in infectious pneumonia and pleural disease, but notable weaknesses in lung cancer and vascular pathology.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>LLaMa 3.1 demonstrates promise as an open-source NLP tool in thoracic diagnostics, though its performance variability highlights the need for refinement and domain-specific training. Open-source models offer transparency and accessibility, while proprietary models deliver consistency. Both hold value, depending on clinical context and resource availability.</p>\u0000 </section>\u0000 </div>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 4","pages":"279-288"},"PeriodicalIF":0.0,"publicationDate":"2025-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144910018","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":"Association Between Fetal Myocardial Alterations and Congenital Heart Disease Based on Post-Mortem Myocardial MRI","authors":"Weizeng Zheng,&nbsp;Xia Ying,&nbsp;Yuan Chen,&nbsp;Le Wang,&nbsp;Peiyue Jiang,&nbsp;Ying Jiang,&nbsp;Guohui Yan,&nbsp;Hong Wang,&nbsp;Yimin Zhou,&nbsp;Yun Liang,&nbsp;Yu Zou,&nbsp;Liqun Sun,&nbsp;Qiong Luo","doi":"10.1002/ird3.70011","DOIUrl":"https://doi.org/10.1002/ird3.70011","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Congenital heart disease (CHD) results from abnormal heart development during fetal development, leading to life-threatening complications. This study aimed to evaluate the feasibility of applying myocardial parametric mapping in post-mortem magnetic resonance imaging and to examine differences in the left ventricular myocardium between fetuses with CHD and controls.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This prospective case–control study was conducted on 14 deceased fetuses with CHD (CHD group) and 24 fetuses without CHD (control group). Fetuses with CHD were further stratified into the cyanotic (<i>n</i> = 9) and non-cyanotic (<i>n</i> = 5) CHD groups. T1, T2, and proton density relaxation times of the left ventricular myocardium were calculated and compared using multiple-dynamic multiple-echo post-mortem magnetic resonance imaging technology.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The myocardial T2 relaxation time was significantly different between the groups (<i>p</i> = 0.033), with no difference in T1 or proton density relaxation times between the groups. A one-way analysis of variance with Tukey's test showed that the mean cyanotic CHD group showed a longer myocardial T2 relaxation time than the control group (98.000 ± 13.143 vs. 83.542 ± 9.491 ms, <i>p</i> = 0.003). Additionally, the correlation coefficient in the CHD group was significantly different between the myocardial T2 relaxation time and peak systolic velocity of pulmonary artery on a fetal echocardiogram (<i>r</i>² = 0.681, <i>p</i> = 0.010).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>These results suggest that using myocardial alterations in the T2 relaxation time may provide a accurate early warning for myocardial injury and enable noninvasive recognition of cardiac involvement in fetuses with CHD.</p>\u0000 </section>\u0000 </div>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 3","pages":"222-230"},"PeriodicalIF":0.0,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519973","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":"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}