iRadiology最新文献

{"title":"Alpha-emitters and targeted alpha therapy in cancer treatment","authors":"Jiajia Zhang,&nbsp;Shanshan Qin,&nbsp;Mengdie Yang,&nbsp;Xiaoyi Zhang,&nbsp;Shenghong Zhang,&nbsp;Fei Yu","doi":"10.1002/ird3.30","DOIUrl":"https://doi.org/10.1002/ird3.30","url":null,"abstract":"<p>Alpha emitters are radionuclides with good pharmacological characteristics for the treatment of cancer because they decay by emitting high linear energy transfer particles. Recent advancements in isotope production and purification and the generation of novel techniques for optimum targeting have led to the development of targeted alpha therapy (TAT). The great cytotoxic potential of α-particle emissions combined with monoclonal antibodies, peptides, small compounds, or nanoparticles has led to investigations of TAT in the pre-clinical context and more recently, in oncology clinical trials. Numerous studies have shown that TAT is effective both in vitro and in vivo. The first α-emitter to obtain FDA approval for the treatment of prostate cancer with metastatic bone lesions was radium-223 dichloride. Many clinical trials are being conducted to evaluate the efficiency and safety of several radionuclides in cancer treatment, including radium-223, astatine-211, actinium-225, bismuth-213, lead-212, and thorium-227. This review provides an overview of the therapeutic use of these radionuclides and a summary of the studies that lay the groundwork for future clinical advancement.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"1 3","pages":"245-261"},"PeriodicalIF":0.0,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.30","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50140788","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":"Optical imaging of in vivo adoptive T-cell therapy: State of the art and challenges","authors":"Qingshuang Li,&nbsp;Dehong Hu,&nbsp;Duyang Gao,&nbsp;Guanhui Gao,&nbsp;Can Zhang,&nbsp;Zonghai Sheng","doi":"10.1002/ird3.28","DOIUrl":"https://doi.org/10.1002/ird3.28","url":null,"abstract":"<p>Adoptive T-cell therapy (ACT), which is an important type of live cell therapy, has achieved unprecedented success in treating hematological malignancies. Recent studies have shown that ACT is also a promising treatment for solid tumors. Visualizing the in vivo fates (distribution, homing, infiltration, proliferation, and exhaustion) of the immune cells used for ACT (ACT immune cells) is of great importance to promote basic research and clinical translation of ACT. Optical imaging techniques, including bioluminescence, fluorescence, and photoacoustic imaging, have the advantages of high sensitivity, high spatiotemporal resolution, minimal exposure to harmful radiation, and simple instrumentation. Recently, various types of optical imaging probes, including bioluminescence, fluorescence, and photoacoustic imaging probes, have been used to visualize ACT immune cells in vivo and evaluate the molecular mechanism, efficacy, and side effects of ACT. In this review, the optical imaging probes and labeling methods that have been used for in vivo visualization of ACT immune cells are summarized, and the opportunities and challenges of using optical imaging to visualize ACT immune cells in vivo are discussed.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"1 3","pages":"225-235"},"PeriodicalIF":0.0,"publicationDate":"2023-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.28","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50124494","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":"Ultrasonic follow-up of a methotrexate-treated patient with Riedel's thyroiditis","authors":"Xinlong Shi,&nbsp;Yu Xia","doi":"10.1002/ird3.27","DOIUrl":"https://doi.org/10.1002/ird3.27","url":null,"abstract":"<p>A 48-year-old woman was admitted to our hospital because of neck tightness, cough, hoarseness, and nocturnal dyspnea. Physical examination revealed left neck swelling, but her thyroid gland was small on ultrasound examination. A clear demarcation of the thyroid gland depicting fibrotic invasion was difficult to find and positron emission tomography/computed tomography suggested chronic thyroiditis (Figure 1a–e). The parathyroid hormone and calcium levels were within normal limits. Biopsy revealed some fibrocytes and lymphocytes but no signs of malignancy. The patient was finally diagnosed with Riedel's thyroiditis. She was treated with prednisone and methotrexate. Cervical ultrasonography performed throughout follow-up showed no significant change in the thyroid volume; however, the compressive symptoms disappeared and hoarseness was relieved. The hypoechoic areas surrounding the carotid arteries gradually decreased after treatment (Figure 1f–h). No further changes were obvious beyond 1 year.</p><p>Xinlong Shi analyzed the data and prepared the first draft of the manuscript. Xinlong Shi and Yu Xia participated in the conception and design of the study, Xinlong Shi constructively revised the manuscript; Yu Xia participated in and supervised the study throughout, and he shared corresponding authorship. All authors commented on previous versions of the manuscript and approved the final version.</p><p>The authors declare no conflicts of interest.</p><p>Not applicable.</p><p>Not applicable.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"1 3","pages":"281-282"},"PeriodicalIF":0.0,"publicationDate":"2023-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.27","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50151332","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 review of biomodified or biomimetic polymer dots for targeted fluorescent imaging and disease treatments","authors":"Jintong Guo,&nbsp;Meng Du,&nbsp;Zhiyi Chen,&nbsp;Xueli Chen,&nbsp;Zhen Yuan","doi":"10.1002/ird3.26","DOIUrl":"https://doi.org/10.1002/ird3.26","url":null,"abstract":"<p>Due to their inherent tunable spectrum, high brightness, excellent biostability and biocompatibility, and functionalization of surfaces, semiconducting polymer dots (Pdots) are now playing an essential role in fluorescent (FL) imaging and disease treatment through bioconjugation with peptides or biomimetic materials. In particular, biomimetic Pdots exhibit their capability in targeted imaging of lesion and increased efficacy for targeting disease treatment. This review will inspect the recent advances in the design and functionalization strategies of biomodified and biomimetic Pdots for enhanced disease detection and therapy. More importantly, the application of these two modifications in targeted FL imaging and cancer treatment is to be addressed in detail. Meanwhile, the main challenges and prospects of biomimetic and biomodified Pdots are to be discussed, which will pave a new avenue for improved disease detection and imaging-guided treatment.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"1 3","pages":"209-224"},"PeriodicalIF":0.0,"publicationDate":"2023-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.26","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50151043","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":"Graph neural networks for image-guided disease diagnosis: A review","authors":"Lin Zhang,&nbsp;Yan Zhao,&nbsp;Tongtong Che,&nbsp;Shuyu Li,&nbsp;Xiuying Wang","doi":"10.1002/ird3.20","DOIUrl":"https://doi.org/10.1002/ird3.20","url":null,"abstract":"<p>Medical imaging is playing an increasingly crucial role in disease diagnosis. Numerous deep learning-based methods have been developed for image-guided automatic disease diagnosis. Most of the methods have harnessed conventional convolutional neural networks, which are directly applied in the regular image domain. However, some irregular spatial patterns revealed in medical images are also critical to disease diagnosis, since they can describe latent relations in different image regions of a subject (e.g., different focal lesions in an image) or between different groups (e.g., Alzheimer's disease and healthy control). Therefore, how to exploit and analyze irregular spatial patterns and their relations has become a research challenge in the field of image-guided disease diagnosis. To address this challenge, graph neural networks (GNNs) are proposed to perform the convolution operation on graphs. Graphs can naturally represent irregular spatial structures. Because of their ability to aggregate node features, edge features, and graph structure information to capture and learn hidden spatial patterns in irregular structures, GNN-based algorithms have achieved promising results in the detection of various diseases. In this paper, we introduce commonly used GNN-based algorithms and systematically review their applications to disease diagnosis. We summarize the workflow of GNN-based applications in disease diagnosis, ranging from localizing the regions of interest and edge construction to modeling. Furthermore, we discuss the limitations and outline potential research directions for GNNs in disease diagnosis.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"1 2","pages":"151-166"},"PeriodicalIF":0.0,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.20","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50146183","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":"Prognostic and discriminatory abilities of imaging scoring systems in predicting COVID-19 adverse outcomes","authors":"Omneya Kandil,&nbsp;Anas Elgenidy,&nbsp;Patrick Saba,&nbsp;Mohamed Tarek Hasan,&nbsp;Kenneth Galbraith,&nbsp;Mark Spooner,&nbsp;Demi Ajao,&nbsp;Omar Yaipen,&nbsp;Elyas Ayad,&nbsp;Abdelrahman Nassar,&nbsp;Khalil Hamka,&nbsp;Walaa Hasan,&nbsp;Jaffer Shah,&nbsp;Ahmed Shawkat,&nbsp;Diaa Hakim,&nbsp;Hani Aiash","doi":"10.1002/ird3.23","DOIUrl":"https://doi.org/10.1002/ird3.23","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>To evaluate the discriminatory ability of imaging modalities' scoring systems in the prediction of COVID-19 adverse outcomes like ICU admission, ventilatory support, or mortality.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We searched PUBMED, EBSCO, WEB OF SCIENCE, and SCOPUS. Two authors independently screened the resulting papers for fulfillment criteria. Meta-DiSc version 1.4, RevMan version 5.4, and MedCalc version 19.1 were used for test accuracy analysis, sensitivity and specificity analysis, and pooling Area under the curve for discriminatory assessment, respectively.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Regarding mortality prediction, the computed tomography (CT) showed significantly higher sensitivity [80%; 95% CI 0.74–0.85] and positive likelihood ratio (PLR) [4.41 95% CI 2.94–6.61] relative to the Lung Ultrasound Score (LUS) approach, while the LUS approached the CT scan with specificity of 81% [95% CI 0.78–0.83] and negative likelihood ratio (NLR) of [0.32; 95% CI 0.16–0.64]. The pooled area under ROC for LUS was [AUC = 0.777, 95% CI 0.701–0.852; <i>p</i> &lt; 0.001, <i>I</i>² = 74.86%, <i>p</i> = 0.019] while the pooled area under ROC for CT severity score was [AUC = 0.855, 95% CI 0.78–0.93; <i>p</i> &lt; 0.001, <i>I</i>² = 93.73%, <i>p</i> &lt; 0.001]. Regarding adverse outcomes prediction, the LUS had a slightly higher specificity of [78%; 95% CI 0.75–0.80] and PLR of [3.60; 95% CI 2.28–5.68] compared to CT score. The pooled AUC using LUS was (0.77, 95% CI 0.719–0.832; <i>p</i> &lt; 0.001), while using CT severity score was (0.843, 95% CI 0.787–0.898; <i>p</i> &lt; 0.001), and using X-ray scores was (0.814, 95% CI 0.751–0.878; <i>p</i> &lt; 0.001).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>CT severity score showed a better discriminatory ability in predicting COVID-19 adverse outcomes, as in-hospital mortality, ICU admission, and need for ventilatory support compared to LUS and X-RAY scores, while the LUS, being more specific, had a slightly better prognostic value.</p>\u0000 </section>\u0000 </div>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"1 2","pages":"128-140"},"PeriodicalIF":0.0,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.23","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50146184","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":"Fully automated radiosynthesis of [18F]mG4P027 for mGluR4 imaging","authors":"Sung-Hyun Moon,&nbsp;Georges El Fakhri,&nbsp;Zhaoda Zhang,&nbsp;Anna-Liisa Brownell,&nbsp;Junfeng Wang","doi":"10.1002/ird3.25","DOIUrl":"https://doi.org/10.1002/ird3.25","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Fluorine-18 labeled N-(4-chloro-3-(((fluoro-¹⁸F)methyl-d₂)thio)phenyl)picolinamide, [¹⁸F]mG4P027, is a potent positron emission tomography (PET) radiotracer for mGluR4. Our previous in vitro and in vivo evaluations have demonstrated that this tracer is promising for further translational studies. However, automated radiosynthesis process poses significant challenges that need to be addressed.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The automated radiosynthesis was performed using the TRACERlab FX2N module, which comprises two distinct reactors capable of accommodating the two-step reactions. Several problem-solving strategies were employed to overcome challenges during the automation process. This included modifications to the reaction solvents, reaction conditions, use of a scavenger, drying methods, and the handling of the precursor.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The use of <i>n</i>-Bu₄NN₃ for scavenging excess compound <b>1</b> along with an efficient drying procedure played a key role in the success of the radiosynthesis. The water was successfully removed by using a different duct to overcome the water sensitivity for the second reaction.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Significant modifications were made to the manual process by carefully examining this process and addressing the root causes of the challenges associated with its automation. We successfully implemented automated radiosynthesis using the TRACERlab FX2N module and consequently, obtained a high-purity radiolabeled [¹⁸F]<b>mG4P027</b> in high yield, meeting the requirements for future human studies.</p>\u0000 </section>\u0000 </div>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"1 2","pages":"120-127"},"PeriodicalIF":0.0,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.25","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50138953","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":"Radiobioinformatics: A novel bridge between basic research and clinical practice for clinical decision support in diffuse liver diseases","authors":"Pinggui Lei,&nbsp;Na Hu,&nbsp;Yuhui Wu,&nbsp;Maowen Tang,&nbsp;Chong Lin,&nbsp;Luoyi Kong,&nbsp;Lingfeng Zhang,&nbsp;Peng Luo,&nbsp;Lawrence Wing-Chi Chan","doi":"10.1002/ird3.24","DOIUrl":"https://doi.org/10.1002/ird3.24","url":null,"abstract":"<p>The liver is a multifaceted organ that is responsible for many critical functions encompassing amino acid, carbohydrate, and lipid metabolism, all of which make a healthy liver essential for the human body. Contemporary imaging methodologies have remarkable diagnostic accuracy in discerning focal liver lesions; however, a comprehensive understanding of diffuse liver diseases is a requisite for radiologists to accurately diagnose or predict the progression of such lesions within clinical contexts. Nonetheless, the conventional attributes of radiological features, including morphology, size, margin, density, signal intensity, and echoes, limit their clinical utility. Radiomics is a widely used approach that is characterized by the extraction of copious image features from radiographic depictions, which gives it considerable potential in addressing this limitation. It is worth noting that functional or molecular alterations occur significantly prior to the morphological shifts discernible by imaging modalities. Consequently, the explication of potential mechanisms by multiomics analyses (encompassing genomics, epigenomics, transcriptomics, proteomics, and metabolomics) is essential for investigating putative signal pathway regulations from a radiological viewpoint. In this review, we elaborate on the principal pathological categorizations of diffuse liver diseases, the evaluation of multiomics approaches pertaining to diffuse liver diseases, and the prospective value of predictive models. Accordingly, the overarching objective of this review is to scrutinize the interrelations between radiological features and bioinformatics as well as to consider the development of prediction models predicated on radiobioinformatics as integral components of clinical decision support systems for diffuse liver diseases.</p>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"1 2","pages":"167-189"},"PeriodicalIF":0.0,"publicationDate":"2023-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.24","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50152085","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":"Super-stable homogeneous embolic agents advance the treatment of hepatocellular carcinoma","authors":"Yisheng Peng,&nbsp;Hongwei Cheng,&nbsp;Hui Liu,&nbsp;Yang Zhang,&nbsp;Gang Liu","doi":"10.1002/ird3.22","DOIUrl":"https://doi.org/10.1002/ird3.22","url":null,"abstract":"<p>Hepatocellular carcinoma (HCC) is globally the sixth most prevalent and the third most fatal malignancy [<span>1</span>]. Although radical surgical resection is the optimal treatment strategy for HCC, it is not feasible for approximately 80% of HCC patients who present at intermediate or advanced stages [<span>2</span>]. Conversion therapy, particularly preoperative transcatheter arterial embolization/chemoembolization (TAE/TACE), enables unresectable HCC patients to undergo radical resection; this transition from palliative care to curative surgery enhances overall prognosis of HCC patients [<span>3</span>]. Many treatment guidelines recommend TACE as the first-line conversion therapy for patients with HCC [<span>4</span>]; however, its success rate remains low (11.9%–24.0%) [<span>5, 6</span>]. Traditional manual and three-way tube mixing methods for preparing iodized oil and drug emulsions are limited by the relatively low drug-loading capacity and poor physical stability of the hydrophobic iodized oil and hydrophilic drug formulations. As a result, the drugs are quickly released into circulation, leading to poor therapeutic effects and severe adverse events [<span>7, 8</span>]. The alternative method of drug-loaded microsphere embolization is costly and less effective due to microsphere size limitations [<span>9</span>]. Therefore, finding ways to improve the success rate of conversion therapy is a major challenge that needs to be urgently addressed.</p><p>The long-term survival of HCC patients relies on them undergoing radical surgical resection after successful conversion therapy. Despite postoperative, high-recurrence risk factors, such as large tumors, vascular invasion, metastases, and portal vein tumor thrombus, accurate surgical resection with no residual lesions has been shown to improve treatment efficacy in high-risk liver cancer patients [<span>4</span>]. Indocyanine green (ICG)-fluorescence-guided surgery can help to accurately determine tumor boundaries, identify small tumor metastases, and facilitate precise tumor resection [<span>10</span>]. Severe tumor necrosis and local inflammation caused by TACE conversion therapy markedly limit the operating space of laparoscopic surgery [<span>11, 12</span>]. In laparoscopic surgery without tactile feedback, sensitive fluorescence navigation technology greatly increases the precision of tumor resection [<span>13</span>]. However, because over 90% of the blood supplying liver lesions comes from the hepatic artery, interventional embolization conversion therapy leads to the destruction of almost all the tumor arterial blood supply [<span>14</span>]. Moreover, traditional fluorescence navigation methods cannot be effectively implemented intraoperatively as the fluorescent probes have difficulty accessing the tumor area [<span>12</span>]. Overcoming these obstacles and achieving precise liver tumor resection after conversion therapy is key to prolonging patient survival and reducing posto","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"1 2","pages":"190-194"},"PeriodicalIF":0.0,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.22","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50133480","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":"Metabolic and textural changes in the brain of non-small cell lung cancer patients: A total-body positron emission tomography/computed tomography study","authors":"Xue Xie,&nbsp;Weizhao Lu,&nbsp;Depeng Ma,&nbsp;Sijin Liu,&nbsp;Yanhua Duan,&nbsp;Kun Li,&nbsp;Zhaoping Cheng,&nbsp;Jianfeng Qiu","doi":"10.1002/ird3.21","DOIUrl":"https://doi.org/10.1002/ird3.21","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Brain metastases are frequent complications for lung cancer patients. However, changes in the brain of lung cancer patients have received little attention. We aimed to explore whether alterations in brain glucose uptake and brain texture occur in non-small cell lung cancer (NSCLC) patients and to investigate associations between brain alterations and NSCLC via the uEXPLORER positron emission tomography/computed tomography (PET/CT) system.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>In total, 105 participants were enrolled, including 55 healthy controls and 50 NSCLC patients. Images were acquired using the PET/CT system. Standardized uptake values normalized by lean body mass were calculated as indicators of glucose uptake. Correlation analysis was conducted between aberrant brain glucose uptake, glucose uptake of cancer lesions, and concentrations of serum lung cancer markers. Radiomics was used to investigate whether features extracted from regions with altered brain glucose uptake could serve as biomarkers of lung cancer progression.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Compared with healthy controls, NSCLC patients showed decreased standardized uptake values normalized by lean body mass in the left insula, medial frontal gyrus, and anterior cingulate. Correlation analysis demonstrated that glucose uptake of the anterior cingulate was negatively correlated with serum lung cancer marker concentrations. Radiomic features on PET/CT images of the above brain regions could classify NSCLC patients and healthy controls with an accuracy of 79%.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>NSCLC patients exhibited altered brain glucose uptake and changes in brain textures. These alterations may reflect alterations in behavioral domains in NSCLC and may be related to altered lung-brain interactions and potential brain metastasis of NSCLC.</p>\u0000 </section>\u0000 </div>","PeriodicalId":73508,"journal":{"name":"iRadiology","volume":"1 2","pages":"109-119"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ird3.21","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50134316","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}