Quantitative Imaging in Medicine and Surgery最新文献

{"title":"Complications of synchronous microwave ablation and biopsy versus microwave ablation alone for pulmonary sub-solid nodules: a retrospective, large sample, case-control study.","authors":"Pikun Cao, Zhigang Wei, Guoliang Xue, Nan Wang, Zhichao Li, Yanting Hu, Gang Wang, Xin Ye","doi":"10.21037/qims-24-906","DOIUrl":"10.21037/qims-24-906","url":null,"abstract":"<p><strong>Background: </strong>This was a retrospective, large-sample, case-control study assessing the complications associated with synchronous microwave ablation (MWA) and biopsy for pulmonary sub-solid nodules or ground-glass nodules (GGNs) versus MWA alone. We aimed to verify the safety of synchronous MWA and biopsy for treating GGNs.</p><p><strong>Methods: </strong>From May 2020 to December 2021, 326 patients with GGNs were enrolled. Among them, 164 patients underwent MWA alone (group A) and 162 patients underwent synchronous MWA and biopsy (group B). We assessed the complications, technical success, and positivity rate of the biopsy.</p><p><strong>Results: </strong>The major complications were similar between the two groups, and included pneumothorax (group A <i>vs.</i> group B, 19.5% <i>vs.</i> 13.6%; P=0.150), hemothorax (0.6% <i>vs.</i> 1.2%; P=1.000), pleural effusion (1.2% <i>vs.</i> 0.6%; P=1.000), and pulmonary infection (4.9% <i>vs.</i> 6.2%; P=0.609). No massive hemoptysis, bronchopleural fistula, or air embolism developed. Minor complications including intrapulmonary hemorrhage (group A <i>vs.</i> group B, 28.7% <i>vs.</i> 62.3%, P<0.001), mild pneumothorax (20.7% <i>vs.</i> 29.6%, P=0.587), mild ipsilateral pleural effusion (30.5% <i>vs.</i> 27.8%, P=0.590), mild bilateral pleural effusion (16.5% <i>vs.</i> 22.2%, P=0.188), and subcutaneous emphysema (4.3% <i>vs.</i> 5.6%, P=0.498) were observed. The side effects, including pain, cough, post-ablation syndrome, and post-ablation chronic pain syndrome, were similar between the two groups. The positive diagnosis rate of biopsy in group B was 88.3%.</p><p><strong>Conclusions: </strong>Compared with MWA alone, synchronous MWA and biopsy did not increase the risk of major complications. Although some minor complications developed, synchronous MWA and biopsy is safe for treating pulmonary GGNs.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11485351/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced detection of skull-base bone invasion in nasopharyngeal carcinoma: the supplementary diagnostic value of ¹⁸fluorine-sodium fluoride (¹⁸F-NaF) positron emission tomography/computed tomography (PET/CT) combined with magnetic resonance imaging (MRI).","authors":"Meina Liang, Xufeng Guo, Chengmao Guo, Jingxing Xiao","doi":"10.21037/qims-24-265","DOIUrl":"10.21037/qims-24-265","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Nasopharyngeal carcinoma (NPC) originates in the nasopharyngeal mucosa, the lateral wall of the nasopharynx. A significant challenge in NPC management is skull-base bone invasion (SBBI), which affects prognosis and treatment planning. Magnetic resonance imaging (MRI) is the primary diagnostic tool for SBBI in NPC patients; however, the detection of SBBI can be challenging due to skull-base complexity and overlapping MRI signals. &lt;sup&gt;18&lt;/sup&gt;fluorine-sodium fluoride (&lt;sup&gt;18&lt;/sup&gt;F-NaF) positron emission tomography/computed tomography (PET/CT) is an emerging imaging technique that has shown promise in detecting osseous lesions. This cohort study aimed to assess the supplementary diagnostic value of &lt;sup&gt;18&lt;/sup&gt;F-NaF PET/CT in detecting SBBI in NPC patients compared to that of MRI alone.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Imaging data were retrospectively collected from &lt;sup&gt;18&lt;/sup&gt;F-NaF PET/CT and head-and-neck MRI examinations conducted within a 7-day period. The sensitivity, specificity, and accuracy of &lt;sup&gt;18&lt;/sup&gt;F-NaF PET/CT, MRI, and the combination of both modalities in detecting SBBI were individually assessed. Both lesion- and patient-based analyses were employed for the comparison. Cochran's Q test was used to compare the accuracy of these methods, while the Bonferroni-corrected McNemar test was used for the pairwise comparisons. The data analysis was performed using the R software package, and a significance level of P&lt;i&gt;&lt;&lt;/i&gt;0.05 was considered statistically significant.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 164 patients were enrolled in the study. Using &lt;sup&gt;18&lt;/sup&gt;F-NaF PET/CT, MRI, and the combined modality of &lt;sup&gt;18&lt;/sup&gt;F-NaF PET/CT with MRI, 97, 84, and 94 cases of SBBI were diagnosed, respectively. At the patient level, the diagnostic efficacy (sensitivity, specificity, and accuracy) was as follows: &lt;sup&gt;18&lt;/sup&gt;F-NaF PET/CT had 100% sensitivity, 93.1% specificity, and 97.0% accuracy; MRI had 90.2% sensitivity, 98.6% specificity, and 93.9% accuracy; and the combination of &lt;sup&gt;18&lt;/sup&gt;F-NaF PET/CT and MRI had 100% sensitivity, 97.2% specificity, and 98.8% accuracy. The accuracy rate of &lt;sup&gt;18&lt;/sup&gt;F-NaF PET/CT combined with MRI were significantly higher than that of MRI alone (P&lt;i&gt;=&lt;/i&gt;0.034). A total of 284, 243, and 276 SBBI lesions were diagnosed using &lt;sup&gt;18&lt;/sup&gt;F-NaF PET/CT, MRI, and &lt;sup&gt;18&lt;/sup&gt;F-NaF PET/CT combined with MRI, respectively. The diagnostic efficacy (sensitivity, specificity, and accuracy) at the lesion level was as follows: &lt;sup&gt;18&lt;/sup&gt;F-NaF PET/CT had 99.6% sensitivity, 75.9% specificity, and 95.4% accuracy; MRI had 88.2% sensitivity, 93.1% specificity, and 89.1% accuracy; and the combination of &lt;sup&gt;18&lt;/sup&gt;F-NaF PET/CT with MRI had 100% sensitivity, 91.4% specificity, and 98.5% accuracy. The combination of &lt;sup&gt;18&lt;/sup&gt;F-NaF PET/CT with MRI significantly improved the accuracy rate compared to that of MRI alone, and the difference was statistically significant (","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11485363/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Left main coronary artery spasm detected by intravascular ultrasound: a case description and literature analysis.","authors":"Wei Wang, Tuya Lai, Ningyuan Wang, Jianyong Hao, Lei Gao","doi":"10.21037/qims-24-921","DOIUrl":"10.21037/qims-24-921","url":null,"abstract":"","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11485330/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pediatric intussusception: innovative reduction.","authors":"Junshan Long, Qi Dong","doi":"10.21037/qims-24-668","DOIUrl":"10.21037/qims-24-668","url":null,"abstract":"","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11485333/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The value of blood flow velocity and pressure gradient in differentiating patients with different types of heart failure.","authors":"Jiaxuan Guo, Xiuzheng Yue, Wenying Liang, Lirong Ma, Xiao Sun, Huairong Zhang, Li Zhu","doi":"10.21037/qims-24-311","DOIUrl":"10.21037/qims-24-311","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Patients with different types of heart failure (HF) exhibit varying rates of blood flow through cardiac chambers and pressure gradients across the aortic valve, attributed to differing degrees of myocardial contractility. Assessment of these dynamics offers insights into early HF diagnosis. This study aimed to analyze left ventricular outflow tract (LVOT) blood flow parameters, specifically peak blood flow velocity and pressure gradient derived from four-dimensional flow cardiovascular magnetic resonance (4D flow CMR), and to evaluate 4D flow CMR's utility in distinguishing HF types.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This prospective cross-sectional study recruited 115 HF patients from January 2019 to May 2022 at the General Hospital of Ningxia Medical University, classified by the New York Heart Association Cardiac Function Classification of Heart Failure as class II-IV, alongside a control group (n=30). Participants underwent cardiovascular magnetic resonance (CMR), including 4D flow. HF patients were categorized into heart failure with reduced ejection fraction (HFrEF, n=55), heart failure with mildly reduced ejection fraction (HFmrEF, n=30), and heart failure with preserved ejection fraction (HFpEF, n=30), based on ejection fraction. The cardiac functional parameters and aortic valve flow indices were measured using Circle Cardiovascular Imaging. LVOT 4D flow data were obtained 3 mm below the junction of the aortic valve leaflets, assessing peak velocities above and below the valve. Differences in cardiac function and blood flow parameters between groups were analyzed using one-way analysis of variance (ANOVA). The accuracy of these parameters in identifying subgroups was assessed using the receiver operating characteristic (ROC) curve.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Analysis of conventional cardiac function parameters revealed that left ventricular ejection fraction (LVEF) was significantly lower in the HFrEF and HFmrEF groups compared to the HFpEF and control groups (P&lt;0.01). Additionally, end-diastolic volume and end-systolic volume were significantly higher in the HFrEF and HFmrEF groups than in the HFpEF and control groups (P&lt;0.01). However, there were no significant differences in cardiac function parameters between the HFpEF and control groups (P&gt;0.05). Significant differences were observed in aortic valve peak pressure gradients (Supra-APGmax) among the four study groups (5.01±1.09 &lt;i&gt;vs&lt;/i&gt;. 6.23±2.94 &lt;i&gt;vs&lt;/i&gt;. 7.63±1.81 &lt;i&gt;vs&lt;/i&gt;. 8.89±2.97 mmHg, P&lt;0.05). Aortic valve peak velocities in the HFrEF group differed significantly from the HFpEF and control groups (111.31±12.05 cm/s &lt;i&gt;vs&lt;/i&gt;. 137.2±16 &lt;i&gt;vs&lt;/i&gt;. 147.15±24.55 cm/s, P&lt;0.001). The ROC curve for the pressure gradient below the aortic valve had an area under the curve (AUC) of 0.728 [95% confidence interval (CI): 0.591-0.864, P=0.002], with an optimal threshold of 4.72 mmHg (sensitivity: 0.8, specificity: 0.7, Youden index: 0.5).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11485376/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using CT features of cystic airspace to predict lung adenocarcinoma invasiveness.","authors":"Yu Zhang, Bo-Wen Ding, Lu-Na Wang, Wei-Ling Ma, Li Zhu, Qun-Hui Chen, Hong Yu","doi":"10.21037/qims-24-912","DOIUrl":"10.21037/qims-24-912","url":null,"abstract":"<p><strong>Background: </strong>Lung adenocarcinoma associated with cystic airspace (LACA) was once considered an uncommon manifestation of lung adenocarcinoma (LUAD), and understandings of it are limited; however, it is being observed more frequently in clinical practice. This study sought to assess the prevalence of LACA, and compare the high-resolution computed tomography (HRCT) features of LACA in patients with varying degrees of invasiveness.</p><p><strong>Methods: </strong>This study retrospectively reviewed the HRCT scans of 1,525 patients with LUAD ≤3 cm in diameter at the Shanghai Chest Hospital between January 2016 and May 2016. Each nodule was examined to detect the presence of cystic airspace. Additionally, we analyzed the qualitative HRCT findings of the cystic airspaces, including the pattern, number, wall component density, distribution, inner surface, mural nodules, septa, and vessels passing through the cystic airspace using the Pearson χ² test or Fisher's exact test as appropriate. We also analyzed the quantitative measurements, such as the cystic airspace diameter, wall thickness, and thin-wall proportion, using a one-way analysis of variance or the Kruskal-Wallis rank-sum test as appropriate.</p><p><strong>Results: </strong>LACAs were observed on HRCT in 11.5% (176/1,525) of the patients, of whom 7.1% (36/505) had pure ground-glass nodules, 13.5% (112/830) had mixed ground-glass nodules, and 14.7% (28/190) had solid nodules (P=0.001). The surgical procedures for LACAs varied (P=0.012). The incidence of LACAs increased as nodule diameter and invasiveness increased (both P<0.001). Statistically significant differences were observed in the wall component density, distribution, septa, vessels passing through the cystic airspace, cystic airspace diameter, wall thickness, and thin-wall proportion among the preinvasive lesion (PL), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) groups (P<0.001, P=0.024, P=0.001, P=0.025, P=0.001, P<0.001, and P<0.001, respectively). Wall component density increased as invasiveness increased (P<0.001). Unlike those in the MIAs and IACs, cystic airspaces in PLs typically lacked septa (P=0.001, and P<0.001, respectively). The IACs had larger cystic airspace diameters than the PLs (6.5 <i>vs.</i> 3.7 mm) (P<0.001). The IACs also had thicker wall thickness (11.8 <i>vs.</i> 6.8 mm, 11.8 <i>vs.</i> 8.3 mm) (P<0.001, and P<0.001, respectively) and smaller thin-wall proportions (181.5° <i>vs.</i> 264.8°, 181.5° <i>vs.</i> 223.8°) (P<0.001, and P=0.039, respectively) than the PLs and MIAs.</p><p><strong>Conclusions: </strong>The prevalence and characteristics of cystic airspaces on HRCT can be used to predict invasiveness in patients with LUADs ≤3 cm in diameter.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11485387/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using the GoogLeNet deep-learning model to distinguish between benign and malignant breast masses based on conventional ultrasound: a systematic review and meta-analysis.","authors":"Jinli Wang, Jin Tong, Jun Li, Chunli Cao, Sirui Wang, Tianyu Bi, Peishan Zhu, Linan Shi, Yaqian Deng, Ting Ma, Jixue Hou, Xinwu Cui","doi":"10.21037/qims-24-679","DOIUrl":"10.21037/qims-24-679","url":null,"abstract":"<p><strong>Background: </strong>Breast cancer is one of the most common malignancies in women worldwide, and early and accurate diagnosis is crucial for improving treatment outcomes. Conventional ultrasound (CUS) is a widely used screening method for breast cancer; however, the subjective nature of interpreting the results can lead to diagnostic errors. The current study sought to estimate the effectiveness of using a GoogLeNet deep-learning convolutional neural network (CNN) model to identify benign and malignant breast masses based on CUS.</p><p><strong>Methods: </strong>A literature search was conducted of the Embase, PubMed, Web of Science, Wanfang, China National Knowledge Infrastructure (CNKI), and other databases to retrieve studies related to GoogLeNet deep-learning CUS-based models published before July 15, 2023. The diagnostic performance of the GoogLeNet models was evaluated using several metrics, including pooled sensitivity (PSEN), pooled specificity (PSPE), the positive likelihood ratio (PLR), the negative likelihood ratio (NLR), the diagnostic odds ratio (DOR), and the area under the curve (AUC). The quality of the included studies was evaluated using the Quality Assessment of Diagnostic Accuracy Studies Scale (QUADAS). The eligibility of the included literature were independently searched and assessed by two authors.</p><p><strong>Results: </strong>All of the 12 studies that used pathological findings as the gold standard were included in the meta-analysis. The overall average estimation of sensitivity and specificity was 0.85 [95% confidence interval (CI): 0.80-0.89] and 0.86 (95% CI: 0.78-0.92), respectively. The PLR and NLR were 6.2 (95% CI: 3.9-9.9) and 0.17 (95% CI: 0.12-0.23), respectively. The DOR was 37.06 (95% CI: 20.78-66.10). The AUC was 0.92 (95% CI: 0.89-0.94). No obvious publication bias was detected.</p><p><strong>Conclusions: </strong>The GoogLeNet deep-learning model, which uses a CNN, achieved good diagnostic results in distinguishing between benign and malignant breast masses in CUS-based images.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11485374/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Congenital uterine arteriovenous malformation treated by hysterectomy: a description of two cases.","authors":"Beichen Zhang, Xianqing Wu, Tianyu Zhu, Xiaoshan Chai","doi":"10.21037/qims-24-96","DOIUrl":"10.21037/qims-24-96","url":null,"abstract":"","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11485339/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generative pre-trained transformer (GPT)-4 support for differential diagnosis in neuroradiology.","authors":"Vera Sorin, Eyal Klang, Tamer Sobeh, Eli Konen, Shai Shrot, Adva Livne, Yulian Weissbuch, Chen Hoffmann, Yiftach Barash","doi":"10.21037/qims-24-200","DOIUrl":"10.21037/qims-24-200","url":null,"abstract":"<p><strong>Background: </strong>Differential diagnosis in radiology relies on the accurate identification of imaging patterns. The use of large language models (LLMs) in radiology holds promise, with many potential applications that may enhance the efficiency of radiologists' workflow. The study aimed to evaluate the efficacy of generative pre-trained transformer (GPT)-4, a LLM, in providing differential diagnoses in neuroradiology, comparing its performance with board-certified neuroradiologists.</p><p><strong>Methods: </strong>Sixty neuroradiology reports with variable diagnoses were inserted into GPT-4, which was tasked with generating a top-3 differential diagnosis for each case. The results were compared to the true diagnoses and to the differential diagnoses provided by three blinded neuroradiologists. Diagnostic accuracy and agreement between readers were assessed.</p><p><strong>Results: </strong>Of the 60 patients (mean age 47.8 years, 65% female), GPT-4 correctly included the diagnoses in its differentials in 61.7% (37/60) of cases, while the neuroradiologists' accuracy ranged from 63.3% (38/60) to 73.3% (44/60). Agreement between GPT-4 and the neuroradiologists, and among the neuroradiologists was fair to moderate [Cohen's kappa (kw) 0.34-0.44 and kw 0.39-0.54, respectively].</p><p><strong>Conclusions: </strong>GPT-4 shows potential as a support tool for differential diagnosis in neuroradiology, though it was outperformed by human experts. Radiologists should remain mindful to the limitations of LLMs, while harboring their potential to enhance educational and clinical work.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11485343/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prostate magnetic resonance imaging (MRI) in patients with hip implants-presetting a protocol using a phantom.","authors":"Yuriy A Vasilev, Olga Yu Panina, Dmitry S Semenov, Ekaterina S Akhmad, Kristina A Sergunova, Stanislav A Kivasev, Alexey V Petraikin","doi":"10.21037/qims-24-604","DOIUrl":"10.21037/qims-24-604","url":null,"abstract":"<p><strong>Background: </strong>Metal structures are a source of artifacts that significantly complicate the interpretation of magnetic resonance imaging (MRI). The use of prostate MRI as a preliminary test in men with a suspicion on prostate cancer leads to an increased use of the test. The aim of this study was to solve a clinically significant problem: to ensure the reduction of artifacts from metal hip implants during prostate MRI. Another goal was to evaluate the impact of artifact reduction methods on quantitative measurements.</p><p><strong>Methods: </strong>The prostate gland (PG) phantom model was a cylinder filled with an aqueous solution of polyvinylpyrrolidone at the concentrations of 40%, 30%, and 20% [central zone (CZ), peripheral zone (PZ), and \"lesion\", respectively]. Phantom MRI study was conducted on Philips Ingenia 1.5T and Philips Ingenia 3T scanners.</p><p><strong>Results: </strong>For 1.5 T, the reduction in the influence of artifacts inside region of interest (ROI) was observed, expressed in a decrease in the average apparent diffusion coefficient (ADC) (CZ, PZ, \"lesion\") for the manual artifact reduction (MAR) and ZOOM (title of software artifact reduction) techniques compared to the standard method. For 3T this effect was not detected. The same ADC results were obtained for Standard and MAR techniques, and increased ADC values for ZOOM. Despite the fact that the spread of ADC values on 3.0T scanners was minimal, there was a significant deviation of ADC values from the reference ones (up to 30.4%). Therefore, it is necessary to use a correction coefficient in the ADC calculation for the 3.0 T device. In the presented clinical case, high-quality tomograms were obtained without any artifacts, despite the presence of two hip replacement devices in the scanning area.</p><p><strong>Conclusions: </strong>The accurate prostate MRI in the presence of implants is essential for an accurate diagnosis. This approach allows to reduce artifacts from hip implants, to visualize PG and periprostatic tissue in the best way, and to detect malignant and benign changes.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11485349/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}