iRadiology最新文献

{"title":"A Pilot Study on the Accuracy of Large Language Models (ChatGPT, Google Bard, and Microsoft Copilot) for Selecting the Correct Modality for Musculoskeletal Clinical Cases According to the ACR's Appropriateness Criteria","authors":"Thomas Saliba,&nbsp;Patrick Omoumi,&nbsp;Grammatina Boitsios","doi":"10.1002/ird3.70049","DOIUrl":"https://doi.org/10.1002/ird3.70049","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Large language models (LLMs) are becoming more commonly used in many aspects of radiology. Some authors have previously tested the capacity of various LLMs to suggest the correct imaging modality according to the guidelines of various associations, such as the American College of Radiology. This study aims to test whether free LLMs can suggest the most appropriate imaging modality in various musculoskeletal radiological cases.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We tested ChatGPT 3.5, Google Bard, and Copilot (Precise) to see if they could correctly suggest the appropriate imaging modality per the American College of Radiology's Appropriateness Criteria, using clinical vignettes from the musculoskeletal section. Seventy-six vignettes were submitted to each chatbot, with the answer only being considered correct if it was the most appropriate according to the guidelines.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>ChatGPT 3.5 was correct in 82% of cases, Bard in 66%, and Copilot in 89% of cases. Bard was unable to answer in four cases, claiming that as a LLM, it was not capable of answering the question.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>We found that all three LLMs were able to suggest the correct modality in a majority of cases. However, there was variability in the performance of the LLMs, with Copilot performing the best overall, with an accuracy of 89%.</p>\u0000 </section>\u0000 </div>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"4 1","pages":"35-39"},"PeriodicalIF":0.0,"publicationDate":"2026-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70049","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147637137","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":"From X-Rays to Intelligence: The Evolution of Medical Imaging in the AI Era","authors":"Zhen Cheng","doi":"10.1002/ird3.70055","DOIUrl":"https://doi.org/10.1002/ird3.70055","url":null,"abstract":"&lt;p&gt;At the start of 2026, &lt;i&gt;iRADIOLOGY&lt;/i&gt; is thrilled to spotlight the transformative journey of artificial intelligence (AI) in medical imaging, a field that is revolutionizing and reshaping modern healthcare practice. When we look back at the long river of history, the historical convergence between medical imaging and machine intelligence can be seen to be rooted in the groundbreaking work of pioneers such as Wilhelm Röntgen, Alan Turing, and many others. Their legacies, though separated by disciplines and decades, now intersect in the realm of intelligent imaging, remolding how we diagnose, treat, and manage diseases.&lt;/p&gt;&lt;p&gt;The story begins in 1895, when Wilhelm Röntgen's discovery of X-rays revolutionized medicine. For the first time, humans could peer inside the living body without surgery, revealing anatomical structures with unprecedented clarity. This breakthrough laid the foundation for medical imaging, a field that would soon become indispensable in diagnosing and treating diseases. Röntgen's work was not only a technical achievement but also a philosophical leap; a recognition that light, when harnessed appropriately, can unveil the invisible.&lt;/p&gt;&lt;p&gt;This spirit of exploration would later be echoed in the work of Alan Turing, whose publication in 1936 [&lt;span&gt;1&lt;/span&gt;] on computable numbers, and the conception of the “Turing machine,” laid the foundation for modern computing. Another masterpiece by Turing, titled “Computing Machinery and Intelligence” [&lt;span&gt;2&lt;/span&gt;] published in 1950, introduced the concept of machines thinking, such as humans, paving the way for advancements in machine learning and pattern recognition. The Turing test proposed in that paper challenged the boundaries between human and machine intelligence, a question that would later resonate deeply in medical AI.&lt;/p&gt;&lt;p&gt;The mid-20th century saw the first convergence of computing and medicine. The development of digital imaging in the 1970s, marked by the invention of computed tomography (CT) by Nobel Prize laureates Godfrey Hounsfield and Allan Cormack, bridged the gap between radiology and digital data. This era also witnessed the emergence of important technologies, including magnetic resonance imaging, positron emission tomography, single-photon emission CT, optical imaging, and ultrasound, which could noninvasively provide information not only on 3D anatomy from multiple aspects but also on key functional and molecular events of desired targets, offering unprecedented insight about how diseases occur and develop.&lt;/p&gt;&lt;p&gt;Turing's vision of machines mimicking human intelligence was partially realized in the 1980s and 1990s as machine learning algorithms began to perform pattern recognition tasks. However, these early works' further application in industries and medical imaging was constrained by the “black-box” nature of their algorithms, insufficient computational capacity, and the lack of large, annotated datasets; challenges that would persist for decades.&lt;/p&gt;&lt;p&gt;","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"4 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2026-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70055","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147637153","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":"Periostitis as Initial Sign of Pediatric Acute Lymphoblastic Leukemia","authors":"Siddhi Chawla,&nbsp;Gajanand Singh Tanwar","doi":"10.1002/ird3.70056","DOIUrl":"https://doi.org/10.1002/ird3.70056","url":null,"abstract":"&lt;p&gt;A 5-year-old girl presented with 15 days of insidious-onset pain in the lower legs (left &gt; right) and mild forearm pain with gradual worsening. Examination showed normal limb bulk with tenderness along the lateral forearms and legs. Laboratory evaluation revealed leukocytosis (28,760/mm&lt;sup&gt;3&lt;/sup&gt;), elevated erythrocyte sedimentation rate (29 mm/h), and elevated C-reactive protein (24 mg/L). A radiograph of the left leg was normal. Magnetic resonance imaging of both legs demonstrated diffuse hypointense marrow signal on T1- and T2-weighted images (Figure 1a), bilateral symmetrical short-tau inversion recovery hyperintensity around the fibular shafts with postcontrast enhancement consistent with periostitis (Figure 1b), and multiple irregular peripherally enhancing tibial meta-diaphyseal lesions with nonenhancing fibular shafts, consistent with bone infarcts. Bone marrow biopsy confirmed B-cell acute lymphoblastic leukemia (ALL) with BCR::ABL1 [t (9; 22) (q34.1; q11.2)].&lt;/p&gt;&lt;p&gt;The patient began induction therapy with weekly vincristine and daunorubicin, intrathecal methotrexate, and daily prednisolone for 4–6 weeks. Pegylated asparaginase and daily dasatinib were added from week 2 of treatment. After 1 month, bone marrow examination was normocellular with 3% blast cells, and immunophenotyping showed only 0.18% residual B-cell lymphoblastic leukemia.&lt;/p&gt;&lt;p&gt;Multifocal periostitis as an initial manifestation of ALL is rare. Skeletal involvement occurs in 41%–70% of pediatric ALL and may be associated with better survival, supporting the role of skeletal surveys at diagnosis. In pediatric ALL, leukemic blasts infiltrate the bone marrow, leading to medullary cavity expansion, increased intraosseous pressure, and endosteal disruption. This mechanical stress, along with cytokine-mediated periosteal irritation (e.g., interleukins and tumor necrosis factor-α), stimulates subperiosteal new bone formation, appearing radiologically as periostitis. Thus, periostitis may be the initial radiographic manifestation of ALL, even before hematologic abnormalities.&lt;/p&gt;&lt;p&gt;Differential diagnoses for pediatric periostitis include psoriatic or reactive arthritis, hypervitaminosis A, prostaglandin therapy, hypertrophic pulmonary osteoarthropathy, pachydermoperiostosis, scurvy, infections, malignancy, and fractures, including traumatic and nonaccidental injury (e.g., battered child syndrome).&lt;/p&gt;&lt;p&gt;Persistent or unexplained bone pain in children, even with subtle radiographic findings, carries a risk of misdiagnosis. In such cases, magnetic resonance imaging can detect marrow infiltration earlier than radiography, and hematologic evaluation is essential to exclude acute leukemia. Early recognition prevents diagnostic delay and improves outcomes.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Siddhi Chawla:&lt;/b&gt; conceptualization (equal), investigation (equal), methodology (equal), project administration (equal), validation (equal), writing – original draft (equal), writing – review and editing (equal). &lt;b","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"4 1","pages":"68-69"},"PeriodicalIF":0.0,"publicationDate":"2026-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70056","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147637155","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":"Virtual Magnetic Resonance Elastography Using a Deep Generative Model for Liver Fibrosis Staging","authors":"Longyu Sun,&nbsp;Yikun Wang,&nbsp;Yan Li,&nbsp;Xumei Hu,&nbsp;Wenyue Mao,&nbsp;Mengting Sun,&nbsp;Zian Wang,&nbsp;Fuhua Yan,&nbsp;Ruokun Li,&nbsp;Chengyan Wang","doi":"10.1002/ird3.70045","DOIUrl":"https://doi.org/10.1002/ird3.70045","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Liver biopsy is invasive, which presents many limitations in clinical settings. Magnetic resonance elastography (MRE) has significant value in non-invasively diagnosing liver fibrosis. However, its use is currently uncommon because it requires specialized equipment. This study aimed to propose and assess the reliability of virtual MRE (vMRE) using diffusion weighted imaging (DWI) and evaluate its effectiveness in diagnosing liver fibrosis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We proposed a Registration-based Generative Adversarial Network-convolutional Block Attention Model (RegGAN-CBAM) to synthesize stiffness (cMap) and viscosity (phiMap) using DWI data acquired from 128 patients diagnosed with liver fibrosis or cirrhosis. Correlation and agreement between native MRE (nMRE)- and vMRE-derived measurements were assessed using Spearman correlation coefficients and Bland–Altman analysis. Receiver operating characteristic curves were constructed to evaluate the diagnostic performance of these measures for cirrhosis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The proposed RegGAN-CBAM model demonstrated favorable performance in image synthesis and estimation. vMRE measures had high consistency with nMRE for images; moreover, they correlated significantly with cMap (<i>r</i> = 0.77) and phiMap (<i>r</i> = 0.58) measurements. Staging based on predicted cMap and phiMap demonstrated excellent performance (<i>p</i> &lt; 0.01), with considerable accuracy for diagnosing cirrhosis (area under the curve: cMap = 0.75 and phiMap = 0.74) among the test set (<i>n</i> = 40), which included 21 patients with histologically confirmed cirrhosis (52.5%).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our study highlights the reliability of our proposed model for liver fibrosis diagnosis. Furthermore, the non-invasive approach may serve as a practical alternative to conventional clinical MRE, particularly in healthcare facilities without access to MRE equipment.</p>\u0000 </section>\u0000 </div>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"4 1","pages":"23-34"},"PeriodicalIF":0.0,"publicationDate":"2026-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70045","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147637203","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":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"4 2","pages":"180-181"},"PeriodicalIF":0.0,"publicationDate":"2026-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148088115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the Capability of Spectral Detector Computed Tomography to Identify Zinc and Magnesium in the Prostate Gland: A Proof-of-Concept Study","authors":"Jacqueline Scheicher,&nbsp;Peter Riley,&nbsp;Karen Dobeli,&nbsp;Paul Yielder,&nbsp;Giovanni Mandarano","doi":"10.1002/ird3.70039","DOIUrl":"https://doi.org/10.1002/ird3.70039","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Prostate cancer is one of the most common diagnosed cancers globally, with early detection crucial for reducing mortality and morbidity. However existing screening methods have limitations, such as invasiveness and patient discomfort. Spectral detector computed tomography (SDCT) could be an alternative or complementary test for prostate cancer diagnosis because of its material decomposition capabilities. The purpose of this experimental study was to explore the capability of SDCT to accurately measure zinc (Zn) and magnesium (Mg) levels in solutions that simulate clinically relevant concentrations of these elements.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Solutions of zinc and magnesium chloride (50–1200 μg/g) were prepared in 10 mL test tubes and scanned using SDCT. A region of interest was selected, and average effective atomic numbers (<i>Z</i>-effective [<i>Z</i>-eff]) were obtained using IntelliSpace Discovery. Linear regression assessed the relationship between concentration and <i>Z</i>-eff, with <i>p</i> &lt; 0.05. Regression lines, <i>R</i>² values, and 95% prediction intervals evaluated measurement variability and precision.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>A strong positive correlation was observed between Zn concentration and <i>Z</i>-eff (<i>R</i>² = 0.99), with the regression equation <i>Z</i>-eff = 7.17 + 0.0010 × concentration. Similarly, Mg concentration demonstrated a positive correlation with <i>Z</i>-eff (<i>R</i>² = 0.97), with the regression equation <i>Z</i>-eff = 7.14 + 0.0002 × concentration. The 95% prediction interval showed minimal variability in the data.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>SDCT effectively differentiates between Zn and Mg within clinically relevant concentration ranges, providing a foundation for further research into its clinical application for prostate cancer diagnosis.</p>\u0000 </section>\u0000 </div>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 5","pages":"362-369"},"PeriodicalIF":0.0,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70039","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145385179","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":"Breakthroughs in the Application of Instruments and Equipment in Medical Molecular Imaging to Neuropsychiatric Disorders","authors":"James Robert Brašić,&nbsp;Ali Cahid Civelek","doi":"10.1002/ird3.70038","DOIUrl":"https://doi.org/10.1002/ird3.70038","url":null,"abstract":"&lt;p&gt;This special issue of &lt;i&gt;iR&lt;/i&gt;&lt;i&gt;ADIOLOGY&lt;/i&gt; on the application of instruments and equipment in medical imaging documents the groundbreaking strides to develop optimal imaging modalities, particularly X-ray, ultrasound, computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and single-photon emission computed tomography (SPECT), to diagnose, treat, cure, and ultimately prevent medical disorders. This special issue continues the outstanding contributions of prior special issues on ultra-high field MRI [&lt;span&gt;1&lt;/span&gt;], ultra-high field MRI in the theranostics of mental disorders [&lt;span&gt;2&lt;/span&gt;], artificial intelligence in medical imaging [&lt;span&gt;3&lt;/span&gt;], imaging of fetuses, children, and mothers [&lt;span&gt;4&lt;/span&gt;], and the use of large language models in radiology [&lt;span&gt;5&lt;/span&gt;] to provide readers updates on the state-of-the-art of the application of instruments and equipment in medical imaging to utilize the promising hardware available for optimal interventions in medicine.&lt;/p&gt;&lt;p&gt;This editorial will focus specifically on the means that novel application of instruments and equipment in molecular medical imaging provide the framework for breakthroughs in neuropsychiatric disorders. Medical molecular imaging constitutes a crucial component of the path to identify the abnormalities in anatomy and physiology that lead to the correct diagnosis of neuropsychiatric and other disorders and the utilization of preventive medicine to formulate a comprehensive treatment plan to target the specific needs of each individual patient. Innovations in the development of instruments, equipment, and other hardware, provide the means for optimal visualization of the structure and function of the nervous system and other organ systems in health and disease. The state-of-the-art descriptions of instruments and equipment reported in this special issue constitute the foundation for providers to incorporate precision medicine to construct comprehensive treatments plans to tailor interventions for the unique needs of each individual patient. This editorial will focus on groundbreaking investigations utilizing innovative medical molecular imaging tools (CT, micro positron emission tomograpy/computed tomography [microPET/CT] [&lt;span&gt;6&lt;/span&gt;], MRI, and PET) for neuropsychiatric disorders, including human immunodeficiency virus (HIV) infections [&lt;span&gt;7&lt;/span&gt;] and Parkinson's disease (PD) [&lt;span&gt;8&lt;/span&gt;].&lt;/p&gt;&lt;p&gt;People with infections with the HIV may develop a spectrum of disorders including cognitive dysfunction. The causes of cognitive impairment among older HIV seropositive (HIV+) individuals may overlap with causes among elderly HIV seronegative (HIV−) individuals without HIV infections. Providers are then faced with the urgent need to determine if cognitive function in people who are HIV+ is due to other infections, malignancies, and other conditions requiring immediate interventions. Additionally, providers also must cons","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 5","pages":"327-329"},"PeriodicalIF":0.0,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70038","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145385060","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":"Central Nervous System Involvement as the Initial Manifestation of Transthyretin Amyloidosis: A Case Report and Literature Review","authors":"Fen Li,&nbsp;Mingsheng Wan,&nbsp;Benjian Sun,&nbsp;Lijia Zou,&nbsp;Huan Yang,&nbsp;Jing Li,&nbsp;Si Chen","doi":"10.1002/ird3.70026","DOIUrl":"https://doi.org/10.1002/ird3.70026","url":null,"abstract":"<p>Transthyretin amyloidosis (ATTR), a rare systemic disorder characterized by misfolded transthyretin (TTR) protein aggregation, predominantly affects the heart and peripheral nervous system. Central nervous system (CNS) involvement in ATTR, especially widespread leptomeningeal amyloidosis (LA), is exceedingly rare. Early diagnosis of CNS-predominant ATTR is difficult due to nonspecific symptoms and low awareness. This study adopted a dual-methodology: A single-case analysis of a CNS-predominant hereditary ATTR(CNS-ATTR) patient at a tertiary referral center and a systematic literature review following PRISMA guidelines. PubMed and Embase were systematically searched from the start to March 2025 using controlled vocabulary (MeSH/Emtree terms) and Boolean operators for reported CNS-involved ATTR cases. A systematic review of 79 CNS-ATTR cases revealed universal leptomeningeal enhancement on magnetic resonance imaging (MRI) (77/79, 97%) and cerebrospinal fluid (CSF) protein elevation (66/79, 84%). The index case (p. Gly73Ala) showed diffuse leptomeningeal enhancement, grade 3 PYP uptake, and CSF protein 1.88 g/L. In summary, LA associated with ATTR is extremely scarce. A four-tiered, protocolbased diagnostic algorithm is crucial for patients with unexplained leptomeningeal disorders.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 5","pages":"388-396"},"PeriodicalIF":0.0,"publicationDate":"2025-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70026","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145385091","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":"The Expanding Role of Instruments and Equipment in Medical Imaging","authors":"Arturo Chiti","doi":"10.1002/ird3.70029","DOIUrl":"https://doi.org/10.1002/ird3.70029","url":null,"abstract":"&lt;p&gt;This editorial introduces a special issue dedicated to the technical advancements in medical imaging. Medical imaging is an essential component of modern medicine, enabling the detection and analysis of structures and functions within the human body. Among the key imaging modalities are X-ray, ultrasound, computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and single-photon emission computed tomography. Each of these technologies plays a vital role in diagnostics and research, and their continued development drives progress in diagnostic imaging and related disciplines.&lt;/p&gt;&lt;p&gt;This special issue invites submissions on the following: (1) Applications of recent advancements in imaging instruments and equipment. (2) Integration of imaging devices with molecular imaging and nuclear medicine approaches. (3) The role of instrumentation and radiomics in systemic diseases. (4) Case studies highlighting diagnostic and therapeutic use of imaging technologies.&lt;/p&gt;&lt;p&gt;Modern diagnostics rely significantly on imaging modalities such as CT, MRI, PET, and optical imaging. Each has witnessed transformative technical advances, enhancing clinical precision and diagnostic roles.&lt;/p&gt;&lt;p&gt;CT imaging remains pivotal due to ongoing innovations such as photon-counting detector (PCD) technology. Unlike traditional CT scanners, PCD converts X-ray photons directly into electrical signals, offering resolutions down to 0.2 mm. This high resolution enables clear visualization of intricate structures, such as inner ear bones. PCD inherently provides spectral imaging, delivering simultaneous multi-energy data. These advances yield lower radiation doses (30%–50% reduction), significantly reduced noise, and rapid scan times. AI-driven software enhances image reconstruction, facilitating clearer, lower-dose images. CT's strengths lie in rapid anatomical assessment, crucial in emergencies for trauma or acute neurological conditions. It is vital in lung cancer screening, cardiac imaging (via electrocardiograph-gated CT angiography), and dual-energy CT's material characterization. Globally, approximately 375 million scans occur annually, reflecting widespread integration and increasing adoption, particularly in middle-income regions. Photon-counting CT, recently approved, represents a trend toward spectral imaging becoming routine, whereas AI facilitates workflow efficiency.&lt;/p&gt;&lt;p&gt;MRI, known for exceptional soft tissue contrast, has advanced significantly with ultrahigh field systems like 7 Tesla MRI. These scanners offer superior resolution and sensitivity, critical in neurological imaging for detecting minute lesions and microvascular changes. Hardware advancements include parallel transmit technology to improve image uniformity at ultrahigh fields and digital gradient coils for rapid, high-resolution imaging. Techniques such as parallel imaging and compressed sensing have significantly shortened scan durations, and AI further reduces acqu","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 5","pages":"325-326"},"PeriodicalIF":0.0,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70029","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145385048","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":"Positron Emission Tomography/Computed Tomography in Ovarian Cancer: Current Status and Future Potential","authors":"Caiyun Xu,&nbsp;Jing Peng,&nbsp;Jinyan Chen,&nbsp;Lixia Zhang,&nbsp;Jing Wang","doi":"10.1002/ird3.70034","DOIUrl":"https://doi.org/10.1002/ird3.70034","url":null,"abstract":"<p>Ovarian cancer (OC) is the most lethal gynecological malignancy. Diagnosis usually occurs late, and even with the most effective treatment relapses are frequent. Early diagnosis and precise staging are critical for achieving better treatment outcomes and prognoses. Conventional imaging methods such as ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI) are the main imaging techniques supporting management decisions. However, advancements in molecular imaging have made positron emission tomography/computed tomography (PET/CT) a promising noninvasive imaging option for better management of OC. The literature provides evidence indicating that fluorine-18-fluorodeoxyglucose (¹⁸F-FDG) PET/CT (FDG-PET/CT) is effective in primary tumor diagnosis, staging, prognosis evaluation, treatment response assessment, and relapse surveillance. Looking ahead, significant attention should be paid to tracers beyond FDG, integrated PET/MRI, dynamic PET, and artificial intelligence (AI)-based radiomics. This review examines the application of PET/CT in OC management at each disease stage and discusses its future potential.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"3 5","pages":"337-352"},"PeriodicalIF":0.0,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70034","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145384962","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}