iRadiology最新文献

{"title":"Compressed Sensing-Accelerated 3.0 T Noncontrast-Enhanced CMRA: Diagnostic Efficacy for Coronary Artery Stenosis","authors":"Zhengfu Wang,&nbsp;Yue Zhu,&nbsp;Yi Yin,&nbsp;Zewang Li,&nbsp;Mingming Huang,&nbsp;Bo Gao","doi":"10.1002/ird3.70070","DOIUrl":"https://doi.org/10.1002/ird3.70070","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Coronary artery disease is a leading cause of cardiovascular death. Conventional noncontrast-enhanced 3.0 T coronary magnetic resonance angiography (CMRA) is safe but limited by long scan times and motion artifacts. Compressed sensing (CS) can accelerate imaging, yet the optimal acceleration factor remains undefined. This study aimed to evaluate the diagnostic accuracy of 4.5-fold CS (4.5 × CS)-accelerated 3.0 T noncontrast-enhanced CMRA for detecting coronary artery stenosis, using invasive coronary angiography as the reference standard.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Thirty patients with suspected coronary artery disease who underwent CMRA, coronary computed tomography angiography, and invasive coronary angiography at the Affiliated Hospital of Guizhou Medical University from December 2022 to November 2024 were enrolled. The diagnostic performance of CMRA for detecting ≥ 50.00% stenosis was evaluated using the kappa test (agreement), Wilcoxon signed-rank test (continuous variables), and calculations of sensitivity, specificity, and accuracy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The 4.5 × CS protocol shortened CMRA scan time by 52.30% (to [7.2 ± 1.3] min) while maintaining image quality (signal-to-noise ratio, 25.3–30.2; contrast-to-noise ratio, 19.6–24.5). CMRA showed excellent agreement with invasive coronary angiography (kappa = 0.905, <i>p</i> &lt; 0.001), with strong diagnostic performance at the segment level (sensitivity 86.90%, specificity 99.01%, accuracy 95.45%), the vessel level (sensitivity 94.59%, accuracy 79.17%), and the patient level (sensitivity 92.00%, accuracy 90.00%).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>4.5 × CS-accelerated 3.0 T noncontrast-enhanced CMRA achieves a favorable balance between efficiency, image quality, and diagnostic accuracy. As a radiation- and contrast-free modality, it may be particularly valuable for coronary artery disease screening and follow-up (e.g., in contrast-allergic or renally impaired patients) and shows strong potential for clinical translation.</p>\u0000 </section>\u0000 </div>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"4 4","pages":"329-337"},"PeriodicalIF":2.4,"publicationDate":"2026-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70070","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148848753","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 Molecular Pathology to Cognitive Phenotypes: The Emerging Role of Artificial Intelligence in Neuroimaging","authors":"Xiaohui Zhang,&nbsp;Yan Zhong,&nbsp;Rui Zhou,&nbsp;Chentao Jin,&nbsp;Jing Wang,&nbsp;Mei Tian,&nbsp;Hong Zhang","doi":"10.1002/ird3.70074","DOIUrl":"https://doi.org/10.1002/ird3.70074","url":null,"abstract":"&lt;p&gt;Molecular imaging has transformed contemporary neuroscience by enabling in vivo assessment of disease-relevant biology, including abnormal protein aggregation, altered metabolism, neuroinflammation, and neurotransmitter dysfunction [&lt;span&gt;1&lt;/span&gt;]. However, the ability to visualize molecular pathology does not by itself explain how such pathology disrupts brain organization and, ultimately, causes clinical cognitive symptoms. This translational gap remains a central challenge in neurology, psychiatry, and cognitive neuroscience [&lt;span&gt;2&lt;/span&gt;]. We argue that artificial intelligence (AI) is beginning to close this gap. More than a tool for image processing or classification, AI is repositioning molecular imaging as a framework for interpreting cognitive phenotypes by linking biomarkers, brain networks, and clinical manifestations across biological scales [&lt;span&gt;3&lt;/span&gt;].&lt;/p&gt;&lt;p&gt;Neurological diseases are intrinsically multiscale, with molecular alterations occurring within cells and synapses, propagating through distributed neural circuits, and ultimately manifesting as cognitive decline, neuropsychiatric symptoms, or functional impairments [&lt;span&gt;4&lt;/span&gt;]. Molecular imaging holds unique value as it investigates biological processes more closely aligned with pathophysiology compared with conventional structural imaging alone. Nevertheless, its current application predominantly focuses on detection and quantification, such as identifying amyloid burden, measuring tau accumulation, estimating metabolic changes, or characterizing receptor availability. Although these measurements are crucial, they do not inherently elucidate why patients with seemingly similar pathological burdens may exhibit significantly different symptoms, disease trajectories, or treatment responses [&lt;span&gt;5&lt;/span&gt;]. Consequently, the development of analytical approaches that transition from mere molecular signal detection to the interpretation of phenotypic expressions is necessary.&lt;/p&gt;&lt;p&gt;AI presents significant opportunities in the field of medical imaging. At the technical level, advancements in deep learning have enhanced various aspects of imaging processes, including reconstruction, denoising, motion correction, low-dose enhancement, and multimodal registration for positron emission tomography, single-photon emission computed tomography, magnetic resonance imaging (MRI), and hybrid imaging workflows [&lt;span&gt;6, 7&lt;/span&gt;]. AI-assisted positron emission tomography imaging has demonstrated promising diagnostic capabilities in neurodegenerative diseases, such as Parkinson's disease and Alzheimer's disease [&lt;span&gt;8&lt;/span&gt;]. Furthermore, multimodal AI frameworks are being developed to estimate amyloid and tau burden using routine clinical and imaging data, which could facilitate broader access to biologically informed patient stratification [&lt;span&gt;9&lt;/span&gt;]. These advancements are crucial not only for improving image quality but also for enhancing the reliability, scalability,","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"4 3","pages":"185-187"},"PeriodicalIF":2.4,"publicationDate":"2026-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70074","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148373519","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 Molecular Imaging Probes for Skeletal Diseases: Current Progress and Future Perspectives","authors":"Shuo Guo,&nbsp;Yuling Cui,&nbsp;Zhiye Fan,&nbsp;Chenxin Jiang,&nbsp;Bowen Fu,&nbsp;Guangbin Cui,&nbsp;Yanli He","doi":"10.1002/ird3.70080","DOIUrl":"https://doi.org/10.1002/ird3.70080","url":null,"abstract":"<p>Trauma, osteoporosis (OP), degenerative joint disorders, spinal pathologies, and bone tumors impose a profound burden on patients' health and global healthcare. Conventional anatomical imaging modalities rely heavily on macroscopic structural alterations, which are often observed in a late stage of the disease. These limitations hinder early diagnosis and the timely assessment of therapeutic response. Over the past decades, molecular imaging probes have become powerful tools in clinical practice for the noninvasive visualization of biological and pathophysiological processes at the cellular and molecular levels. This is important for deepening understanding of the intrinsic pathogenesis of the corresponding disease, which can facilitate early diagnosis and treatment. This review evaluates the current status of targeted molecular imaging probes for skeletal diseases. On the basis of the clinical location and disease, we divide the molecular probes for bone diseases into five types: bone trauma and the dynamic repair process, OP, joint diseases, spinal disorders, and bone oncology. In addition, we discuss the frontiers of probe development, including the design of multimodal imaging platforms, the paradigm shift of bone-targeted therapy, and the integration of artificial intelligence (AI) in accelerating probe discovery. The next generation of clinical probes, combining basic radiochemistry and clinical radiology, has great potential and can provide a reference for future orthopedic precision medicine.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"4 3","pages":"206-218"},"PeriodicalIF":2.4,"publicationDate":"2026-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70080","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148373401","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":"Diffusion Weighted Imaging-Negative Cerebellar Hypoperfusion on Arterial Spin Labeling","authors":"Sanjay M. Khaladkar,&nbsp;Prakash Singh Vasan","doi":"10.1002/ird3.70083","DOIUrl":"https://doi.org/10.1002/ird3.70083","url":null,"abstract":"<p></p><p>A 74-year-old hypertensive woman presented with 10 days of left limb ataxia, gait difficulty, and right hemiparesis. (Panels A,B) Axial diffusion weighted imaging (DWI) and apparent diffusion coefficient (ADC) at the cerebellar level show no restricted diffusion in the symptomatic left cerebellar region (acute DWI-positive supratentorial infarcts were present elsewhere, not shown). (Panel C) Axial fluid-attenuated inversion recovery (FLAIR) at the same level shows no established focal cerebellar infarct. (Panels D,E) Sequential 3D pseudo-continuous arterial spin labeling (ASL) cerebral blood flow (CBF) maps acquired on a 3T Siemens MAGNETOM Vida scanner (Siemens Healthineers, Erlangen, Germany) (postlabeling delay 1900–2100 ms; labeling duration 1800–2000 ms) demonstrate focal left cerebellar hypoperfusion. CBF color scale 0–100 mL/100 g/min; matched region of interest (ROI) measurements were approximately 15–25 mL/100 g/min in the affected left cerebellar region versus 34–45 mL/100 g/min contralaterally (approximate 50% relative reduction). (Panel F) Time-of-flight MR angiography (TOF-MRA) shows a hypoplastic left vertebral artery with poor basilar contribution. The patient improved after antiplatelet therapy and secondary prevention; findings support hemodynamic compromise without established cerebellar infarction. Interpretive caution is required because posterior fossa ASL may be influenced by arterial transit delay, lower signal-to-noise ratio, motion, and technical variability, including color-scale and windowing effects. Therefore, ASL abnormality is interpreted as supportive evidence of hemodynamic compromise rather than standalone proof of established infarction. Although the spatial concordance between symptoms, vascular findings, and ASL hypoperfusion is suggestive, a direct causal relationship cannot be definitively established from a single case, particularly in the presence of chronic small-vessel ischemic changes.</p><p><b>Sanjay M. Khaladkar:</b> conceptualization, writing – original draft, methodology, validation, supervision. <b>Prakash Singh Vasan:</b> conceptualization, investigation, writing – review and editing, data curation, project administration.</p><p>The authors have nothing to report.</p><p>This work was conducted in accordance with the principles of the Declaration of Helsinki. Institutional approval was obtained where required.</p><p>Written informed consent for publication of clinical details and imaging findings was obtained from the patient prior to submission.</p><p>The authors declare no conflicts of interest.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"4 3","pages":"285-286"},"PeriodicalIF":2.4,"publicationDate":"2026-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70083","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148373206","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":"Dopamine Transporter Imaging-Based Radiomics for Predicting 4-Year Motor Progression (Unified Parkinson's Disease Rating Scale Part III) in Parkinson's Disease","authors":"Xiaoxuan Fan,&nbsp;Yanghan Chen,&nbsp;Junfeng Lin,&nbsp;Zenwen Han,&nbsp;Jianqiang Ye,&nbsp;Lili Lin,&nbsp;Hong Zhang,&nbsp;Ang Li,&nbsp;Han Jiang","doi":"10.1002/ird3.70079","DOIUrl":"https://doi.org/10.1002/ird3.70079","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Parkinson's disease (PD) shows substantial heterogeneity in motor progression, and reliable early prediction remains challenging. Dopamine transporter (DAT) imaging reflects presynaptic dopaminergic degeneration but is typically analyzed using simplified metrics that may not capture spatial heterogeneity. This study aims to evaluate whether magnetic resonance imaging (MRI)-guided DAT radiomics combined with machine learning can predict 4-year motor progression in PD.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>In this retrospective study, 120 patients from the Parkinson's Progression Markers Initiative were included. Motor progression was defined using the 4-year change in Movement Disorder Society–Unified Parkinson's Disease Rating Scale part III (UPDRS-III) score. Bilateral caudate nuclei and putamina were manually delineated on T1-weighted MRI and transferred to co-registered DAT images. Radiomics features were extracted using PyRadiomics. Twenty base models were constructed by combining two feature-selection methods with 10 classifiers, and Top-2 voting fusion models were developed. Clinical-variable, levodopa equivalent daily dose (LEDD)-adjusted, and clinical-radiomics models were also evaluated.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The best-performing base model achieved a mean area under the receiver operating characteristic curve (AUROC) of 0.736. Fusion models improved discrimination, with the best soft-voting model achieving an AUROC of 0.920 and balanced accuracy (BACC) of 0.734. A more balanced fusion model achieved an AUROC of 0.902 with higher sensitivity (0.818). The clinical-radiomics model showed only a slight AUROC increase over the clinical-only model, and adding Year-4 LEDD did not materially alter radiomics performance. Stable radiomics features were predominantly texture-based, particularly gray-level co-occurrence matrix (GLCM) and gray-level run-length matrix (GLRLM) features derived from original and wavelet-filtered images.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>MRI-guided DAT radiomics combined with ensemble learning may provide prognostically relevant information for predicting 4-year motor progression in PD. Fusion strategies improved discrimination, and stable texture features may reflect striatal dopaminergic heterogeneity.</p>\u0000 </section>\u0000 </div>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"4 3","pages":"246-260"},"PeriodicalIF":2.4,"publicationDate":"2026-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70079","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148373402","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":"Diagnostic Performance of Baseline FDG-PET/CT for Detecting Bone Marrow Involvement in Classic Follicular Lymphoma","authors":"Haoying Huang,&nbsp;Yingying Zhang,&nbsp;Jiajia Dong,&nbsp;Yeye Zhou,&nbsp;Jihui Li,&nbsp;Xin Xu,&nbsp;Na Dai,&nbsp;Bin Zhang","doi":"10.1002/ird3.70082","DOIUrl":"https://doi.org/10.1002/ird3.70082","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Bone marrow involvement (BMI) is a key determinant of treatment strategies and clinical prognosis in classic follicular lymphoma (cFL). The diagnostic performance of baseline positron emission tomography/computed tomography (PET/CT) for identifying BMI remains unclear, and its consistency with bone marrow biopsy (BMB) results varies greatly across studies. Such diagnostic uncertainty hinders accurate clinical risk stratification. This study aimed to assess the diagnostic performance of PET/CT and explore associated diagnostic risk factors.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A total of 176 patients with newly diagnosed classic follicular lymphoma were included. Clinical data, hematological parameters, and PET imaging findings were recorded for all patients and compared with the BMB report. Univariate and multivariate analyses were performed to identify risk factors associated with BMB-confirmed BMI, and corresponding receiver operating characteristic (ROC) curves were plotted to evaluate their diagnostic efficacy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Taking BMB as the reference standard for detecting BMI, sensitivity and specificity of PET/CT were 57.9% and 70.0%. PET/CT-derived BMI (<i>p =</i> 0.023), bulky mass (&gt; 6 cm) (<i>p &lt;</i> 0.001), and spleen involvement (<i>p &lt;</i> 0.001) were identified as independent risk factors for BMB-confirmed BMI with the diagnostic performance (AUC) as 0.639 (<i>p =</i> 0.002), 0.635 (<i>p =</i> 0.002), and 0.702 (<i>p &lt;</i> 0.001), respectively. Furthermore, the combined diagnostic performance of these three factors reached 0.788 (<i>p &lt;</i> 0.001).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Baseline PET/CT provides critical insights into the assessment of BMI in cFL. For patients with PET/CT images of focal with or without diffuse components, BMB may yield false-negative results due to sampling limitations. For patients with a diffuse component, the presence of bulky disease and spleen involvement is strongly predictive of BMB-confirmed BMI. Conversely, the absence of PET/CT-detected BMI, bulky disease, and splenic involvement suggests a low likelihood of BMB-confirmed BMI.</p>\u0000 </section>\u0000 </div>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"4 3","pages":"273-280"},"PeriodicalIF":2.4,"publicationDate":"2026-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70082","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148373454","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":"Dual-Tracer Positron Emission Tomography in Autoimmune Parkinsonism","authors":"Xiaofeng Dou,&nbsp;Chentao Jin","doi":"10.1002/ird3.70078","DOIUrl":"https://doi.org/10.1002/ird3.70078","url":null,"abstract":"<p></p><p>A 75-year-old man presented with 6 months of Parkinsonism and cognitive decline and 4 months of rapid eye movement sleep behavior disorder. T2 fluid-attenuated inversion recovery magnetic resonance imaging was unremarkable (Panel a). ¹⁸F-fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET) revealed bilateral hippocampal hypermetabolism (Panel b). Baseline N-3-[¹⁸F]fluoropropyl-2β-carbomethoxy-3β-4-iodophenyl nortropane PET (¹⁸F-FP-CIT PET) demonstrated diffusely reduced striatal dopamine transporter binding (Panels c and d; specific binding ratio: right 2.14, left 2.33). ¹⁸F-AV-45 (florbetapir) PET revealed mild cortical amyloid deposition (Panel e). Cerebrospinal fluid was positive for cerebellar astrocyte antibody, supporting a probable diagnosis of autoimmune encephalitis with Parkinsonism. After 2 months of methylprednisolone, motor and cognitive symptoms improved. Follow-up ¹⁸F-FDG PET revealed decreased hippocampal hypermetabolism (Panel f), and ¹⁸F-FP-CIT PET demonstrated increased bilateral striatal uptake (Panel g and h; specific binding ratio: right 4.17, left 4.33), suggesting a favorable therapeutic response. Panels b and f (displayed value: 12) and panels d and h (displayed value: 8.4) are displayed using the same color scale (SUVbw [g/mL], 0–30).</p><p><b>Xiaofeng Dou:</b> conceptualization, investigation, formal analysis, data curation, writing – original draft. <b>Chentao Jin:</b> conceptualization, investigation, formal analysis, data curation, writing – review and editing.</p><p>This work was supported by the National Key Research and Development Program of China (Grant 2021YFA1101700) and the Fundamental Research Funds for the Central Universities (Grant 226-2024-00059).</p><p>This study was approved by the Ethics Committee of the Second Affiliated Hospital of Zhejiang University School of Medicine (Approval Number: 2025-0127).</p><p>The requirement for informed consent was waived by the Ethics Committee because this retrospective report used anonymized clinical and imaging data and involved no additional intervention.</p><p>The authors declare no conflicts of interest.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"4 3","pages":"281-282"},"PeriodicalIF":2.4,"publicationDate":"2026-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70078","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148373026","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":"Rare Clear Cell Chondrosarcoma Detected on PET/CT in a Patient With Von Hippel–Lindau Disease","authors":"Kun Tang,&nbsp;Ling Wang","doi":"10.1002/ird3.70077","DOIUrl":"https://doi.org/10.1002/ird3.70077","url":null,"abstract":"<p>The use of ¹⁸F-ALF-NOTA-octreotide in detecting clear cell chondrosarcoma of the rib has rarely been reported. We present a 51-year-old man with suspected von Hippel–Lindau (VHL) disease who had previously undergone surgical resection of a cerebellar hemangioblastoma. All laboratory examination results, including tumor markers, were within normal ranges. ¹⁸F-ALF-NOTA-octreotide PET/CT imaging performed as part of the disease evaluation revealed increased uptake in multiple sites with low-density foci in the pancreas, cerebellum, spinal canal, and kidneys (upper panel A–M, arrow). A spindle-shaped mass near the right 7th rib, which showed partial bone erosion, showed intense uptake with an SUVmaximum of 15.1 (upper panel N–P, arrow). The lesion was resected and confirmed to be a clear cell chondrosarcoma (lower panel). Subsequently, the patient underwent genetic testing that confirmed the diagnosis of VHL disease.</p><p>There are few reports of ¹⁸F-ALF-NOTA-octreotide PET/CT imaging being used to identify clear cell chondrosarcoma. This malignancy is extremely rare and usually occurs in long and flat bones, whereas rib involvement and coexistence with VHL disease are uncommon. VHL disease is a rare inherited tumor syndrome that arises because of mutations in the <i>VHL</i> gene that disrupt the hypoxia-inducible factor signaling pathway. As the hypoxia-inducible factor pathway plays an important role in bone formation and remodeling, these mutations alter bone metabolism and promote the development of clear cell chondrosarcoma. The mechanism by which clear cell chondrosarcoma takes up ¹⁸F-ALF-NOTA-octreotide may be associated with the expression of somatostatin receptors; however, this hypothesis warrants further investigation. This case underscores the vital role of octreotide PET/CT in the management of VHL disease. Clinicians should consider the possibility of clear cell chondrosarcoma in patients with VHL disease associated with bone tumors and uptake of ¹⁸F-ALF-NOTA-octreotide.</p><p></p><p></p><p><b>Kun Tang:</b> conceptualization, writing – original draft. <b>Ling Wang:</b> methodology, supervision, writing – review and editing, funding acquisition.</p><p>The work was supported by the China Scholarship Council (Grant 202509580022).</p><p>The authors have nothing to report.</p><p>The patient provided written informed consent for the examinations.</p><p>The authors declare no conflicts of interest.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"4 3","pages":"283-284"},"PeriodicalIF":2.4,"publicationDate":"2026-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70077","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148373027","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":"Phenomics: The Magnificent Chapter of Life","authors":"Yidan Gao,&nbsp;Christopher Chen,&nbsp;Hong Zhang,&nbsp;Mei Tian","doi":"10.1002/ird3.70089","DOIUrl":"https://doi.org/10.1002/ird3.70089","url":null,"abstract":"<p>The cover of this special issue of iRadiology presents a profound artistic tableau: under the spotlight, a conductor leads a symphony orchestra composed of diverse instrumental sections in the performance of a grand musical movement. Such rendering is not merely a tribute to art; rather, it serves as a metaphor for the current developmental paradigm in the life sciences.</p><p>The biological mechanisms underlying life are inherently multidimensional. Just as a solo instrument, whether a melodic violin or a resonant brass horn, cannot independently generate the rich harmony of a full symphony, isolated “omics” technologies are fundamentally insufficient to capture the comprehensive physiological landscape of living systems. Within this orchestral framework, distinct instrumental sections correspond to diverse biological data modalities, including genomics, transcriptomics, proteomics, metabolomics, and spatial omics, which constitute the precise “measurement” of living systems. Distinct from physical measurements, artificial intelligence (AI) serves as the powerful cognitive engine of “computation” The “conductor” at the podium embodies the scientific investigators, who are tasked with orchestrating the integration of these massive datasets, enabling the information to transcend spatiotemporal scales and synthesize into a cohesive, systems-level biological narrative. Ultimately, leveraging these technologies to explore the profound mysteries of life empowers scientists to move beyond passive observation, transitioning toward the active “Modulation” of biological processes and the intelligent “Engineering” of novel theranostics. While “Measurement” and “Computation” focus on deciphering the existing biological state, “Modulation” refers to the precise and dynamic control of physiological systems. “Engineering,” conversely, embodies the rational design of targeted solutions, encompassing the development of innovative diagnostic or therapeutic technologies. Together, these four pillars—Measurement, Computation, Modulation, and Engineering—complete the translational loop from molecular mapping to clinical cure.\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure>\u0000 </p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"4 3","pages":"i-v"},"PeriodicalIF":2.4,"publicationDate":"2026-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70089","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148373059","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":"Crossing the Blood–Brain Barrier: Molecular Imaging Illuminates Transplanted Stem Cells in the Brain","authors":"Peili Cen,&nbsp;Yan Zhong,&nbsp;Rui Zhou,&nbsp;Jing Wang,&nbsp;Han Jiang,&nbsp;Mei Tian,&nbsp;Hong Zhang","doi":"10.1002/ird3.70075","DOIUrl":"https://doi.org/10.1002/ird3.70075","url":null,"abstract":"&lt;p&gt;Stem cell therapy offers a unique opportunity to repair the damaged brain in neurological conditions such as stroke, Parkinson's disease, Alzheimer's disease, and traumatic brain injury [&lt;span&gt;1&lt;/span&gt;]. This strategy of replacing lost neurons and supporting surviving tissue with transplanted cells is compelling because of its potential to reconstruct both the structure and function of the injured brain. Preclinical studies and early-phase clinical trials have yielded encouraging results, demonstrating functional improvements and evidence of graft survival in animal models and initial human cohorts [&lt;span&gt;2&lt;/span&gt;]. However, translating these promising findings into reliable and approved therapies for clinical practice demands a deeper understanding of the in vivo processes that transplanted cells undergo after entering the brain.&lt;/p&gt;&lt;p&gt;Molecular imaging represents an important strategy for visualizing transplanted stem cells in vivo. By transferring cell behaviors into imaging data, it may solve the key issues in stem cell therapy, including cell fate tracking, functional recovery evaluation, and safety monitoring [&lt;span&gt;3&lt;/span&gt;]. Benefitting from different modalities including optical imaging, magnetic resonance imaging, positron emission tomography (PET), and hybrid multimodal imaging, imaging agent labeling strategies contribute to the in vivo tracking of grafted stem cells within the brain. However, the blood–brain barrier (BBB) severely restricts the application of existing molecular imaging methods for the visualization of transplanted stem cells within the brain. The BBB protects the brain but also prevents the entry of most contrast agents, radiotracers, and reporter probes designed to track transplanted stem cells in the brain parenchyma [&lt;span&gt;4&lt;/span&gt;]. Consequently, once stem cells are transplanted into the brain, they cannot be tracked, which prevents any observations of their in vivo behavioral processes. To advance stem cell therapy for neurological diseases, there is an urgent need to develop new molecular imaging tools or strategies that can cross the BBB to visualize transplanted stem cells in the brain.&lt;/p&gt;&lt;p&gt;Direct in vitro labeling of stem cells prior to transplantation offers a straightforward way to avoid BBB issues. Imaging agents, commonly including superparamagnetic iron oxide nanoparticles for magnetic resonance imaging [&lt;span&gt;5&lt;/span&gt;], radionuclides such as 2-deoxy-2-[&lt;sup&gt;18&lt;/sup&gt;F]fluoro-D-glucose for PET [&lt;span&gt;6&lt;/span&gt;], and organic fluorophores for optical imaging, can be loaded before cell transplantation, with no need to cross the BBB. However, several inherent shortcomings of these techniques limit their reliability for long-term in vivo tracking. For example, the intracellular label is continuously diluted with each round of cell division, eventually falling below the detection threshold. Critically, when labeled cells die, the imaging agent (particularly superparamagnetic iron oxide) is often retained a","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"4 3","pages":"188-191"},"PeriodicalIF":2.4,"publicationDate":"2026-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.70075","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148373535","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}