Tomography最新文献

{"title":"Computer-Assisted Evaluation of Zygomatic Fracture Outcomes: Case Series and Proposal of a Reproducible Workflow.","authors":"Simone Benedetti, Andrea Frosolini, Flavia Cascino, Laura Viola Pignataro, Leonardo Franz, Gino Marioni, Guido Gabriele, Paolo Gennaro","doi":"10.3390/tomography11020019","DOIUrl":"10.3390/tomography11020019","url":null,"abstract":"<p><strong>Background: </strong>Zygomatico-maxillary complex (ZMC) fractures are prevalent facial injuries with significant functional and aesthetic implications. Computer-assisted surgery (CAS) offers precise surgical planning and outcome evaluation. The study aimed to evaluate the application of CAS in the analysis of ZMC fracture outcomes and to propose a reproducible workflow for surgical outcome assessment using cephalometric landmarks.</p><p><strong>Methods: </strong>A retrospective cohort study was conducted on 16 patients treated for unilateral ZMC fractures at the Maxillofacial Surgery Unit of Siena University Hospital (2017-2024). Inclusion criteria included ZMC fractures classified as Zingg B or C, treated via open reduction and internal fixation (ORIF). Pre- and post-operative CT scans were processed for two- and three-dimensional analyses. Discrepancies between CAS-optimized reduction and achieved surgical outcomes were quantified using cephalometric landmarks and volumetric assessments.</p><p><strong>Results: </strong>Out of the 16 patients (69% male, mean age 48.1 years), fractures were predominantly on the right side (81%). CAS comparison between the post-operative and the contralateral side revealed significant asymmetries along the X and Y axes, particularly in the fronto-zygomatic suture (FZS), zygo-maxillary point (MP), and zygo-temporal point (ZT). Computer-assisted comparison between the post-operative and the CAS-simulated reductions showed statistical differences along all three orthonormal axes, highlighting the challenges in achieving ideal symmetry despite advanced surgical techniques. CAS-optimized reductions demonstrated measurable improvements compared to traditional methods, underscoring their utility in outcome evaluation.</p><p><strong>Conclusions: </strong>CAS technology enhances the precision of ZMC fracture outcome evaluation, allowing for detailed comparison between surgical outcomes and virtual simulations. Its application underscores the potential for improved surgical planning and execution, especially in complex cases. Future studies should focus on expanding sample size, refining workflows, and integrating artificial intelligence to automate processes for broader clinical applicability.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"11 2","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11860590/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143494614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Negative Bronchoscopy or Computed Tomography Radiation in Children with Suspected Foreign Body Aspiration? Pros and Cons.","authors":"Mehmet Emin Çelikkaya, Ahmet Atıcı, İnan Korkmaz, Mehmet Karadağ, Çiğdem El, Bülent Akçora","doi":"10.3390/tomography11020017","DOIUrl":"10.3390/tomography11020017","url":null,"abstract":"<p><strong>Background: </strong>The aim of this study was to analyse patients who underwent bronchoscopy for suspected foreign body aspiration (FBA) and to evaluate the properties of computed tomography (CT) in preventing unnecessary bronchoscopy, which carries the risk of serious complications.</p><p><strong>Methods: </strong>All patients younger than 18 years of age who were evaluated for FBA at a tertiary children's hospital between June 2014 and February 2023.</p><p><strong>Results: </strong>A total of 165 children were included in this study. In Group I (only bronchoscopy), the detection rate of FBA was 77.9%, whereas in Group II (CT ± bronchoscopy), the detection rate of FBA was 93%. Additionally, the negative diagnosis rate in Group II (7%) was significantly higher compared to Group I (22.1%).</p><p><strong>Conclusions: </strong>Low-dose chest CT is a highly effective and reliable imaging method for the diagnosis of FBA due to its rapid performance, minimal radiation exposure, and high sensitivity and specificity; therefore, it can prevent unnecessary bronchoscopies in suspicious cases and increase the positive bronchoscopy rate.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"11 2","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11860685/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143494712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Magnetic Resonance Elastography of Invasive Breast Cancer: Evaluating Prognostic Factors and Treatment Response.","authors":"Jin Joo Kim, Jin You Kim, Yeon Joo Jeong, Suk Kim, In Sook Lee, Nam Kyung Lee, Taewoo Kang, Heeseung Park, Seokwon Lee","doi":"10.3390/tomography11020018","DOIUrl":"10.3390/tomography11020018","url":null,"abstract":"<p><p><b>Objectives:</b> To assess the elasticity values in breast tissues using magnetic resonance elastography (MRE) and examine the association between elasticity values of invasive breast cancer with prognostic factors and the pathologic response to neoadjuvant systemic therapy (NST). <b>Methods:</b> A total of 57 patients (mean age, 54.1 years) with invasive breast cancers larger than 2 cm in diameter on ultrasound were prospectively enrolled. The elasticity values (mean, minimum, and maximum) of invasive breast cancers, normal fibroglandular tissues, and normal fat tissues were measured via MRE using a commercially available acoustic driver and compared. Elasticity values of breast cancers were compared according to prognostic factors and pathologic responses in patients who received NST before surgery. Receiver operating curve analysis was performed to evaluate the predictive efficacy of elasticity values in terms of pathological response. <b>Results:</b> Among the 57 patients, the mean elasticity value of invasive breast cancers was significantly higher than that of normal fibroglandular tissue and normal fat tissue (7.90 ± 5.80 kPa vs. 2.54 ± 0.80 kPa vs. 1.32 ± 0.33 kPa, all <i>p</i>s < 0.001). Invasive breast cancers with a large diameter (>4 cm) exhibited significantly higher mean elasticity values relative to tumors with a small diameter (≤4 cm) (11.65 ± 7.22 kPa vs. 5.87 ± 3.58 kPa, <i>p</i> = 0.002). Among 24 patients who received NST, mean, minimum, and maximum elasticity values significantly differed between the pathologic complete response (pCR) and non-pCR groups (all <i>p</i>s < 0.05). For the mean elasticity value, the area under the curve value for distinguishing pCR and non-pCR groups was 0.880 (95% confidence interval, 0.682, 0.976; <i>p</i> < 0.001). <b>Conclusions:</b> The elasticity values of invasive breast cancers measured via breast MRE showed a positive correlation with tumor size and showed potential in predicting the therapeutic response in patients receiving NST.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"11 2","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11860845/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143494708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Utilizing Vision Transformers for Predicting Early Response of Brain Metastasis to Magnetic Resonance Imaging-Guided Stage Gamma Knife Radiosurgery Treatment.","authors":"Simona Ruxandra Volovăț, Diana-Ioana Boboc, Mădălina-Raluca Ostafe, Călin Gheorghe Buzea, Maricel Agop, Lăcrămioara Ochiuz, Dragoș Ioan Rusu, Decebal Vasincu, Monica Iuliana Ungureanu, Cristian Constantin Volovăț","doi":"10.3390/tomography11020015","DOIUrl":"10.3390/tomography11020015","url":null,"abstract":"<p><strong>Background/objectives: </strong>This study explores the application of vision transformers to predict early responses to stereotactic radiosurgery in patients with brain metastases using minimally pre-processed magnetic resonance imaging scans. The objective is to assess the potential of vision transformers as a predictive tool for clinical decision-making, particularly in the context of imbalanced datasets.</p><p><strong>Methods: </strong>We analyzed magnetic resonance imaging scans from 19 brain metastases patients, focusing on axial fluid-attenuated inversion recovery and high-resolution contrast-enhanced T1-weighted sequences. Patients were categorized into responders (complete or partial response) and non-responders (stable or progressive disease).</p><p><strong>Results: </strong>Despite the imbalanced nature of the dataset, our results demonstrate that vision transformers can predict early treatment responses with an overall accuracy of 99%. The model exhibited high precision (99% for progression and 100% for regression) and recall (99% for progression and 100% for regression). The use of the attention mechanism in the vision transformers allowed the model to focus on relevant features in the magnetic resonance imaging images, ensuring an unbiased performance even with the imbalanced data. Confusion matrix analysis further confirmed the model's reliability, with minimal misclassifications. Additionally, the model achieved a perfect area under the receiver operator characteristic curve (AUC = 1.00), effectively distinguishing between responders and non-responders.</p><p><strong>Conclusions: </strong>These findings highlight the potential of vision transformers, aided by the attention mechanism, as a non-invasive, predictive tool for early response assessment in clinical oncology. The vision transformer (ViT) model employed in this study processes MRIs as sequences of patches, enabling the capture of localized tumor features critical for early response prediction. By leveraging patch-based feature learning, this approach enhances robustness, interpretability, and clinical applicability, addressing key challenges in tumor progression prediction following stereotactic radiosurgery (SRS). The model's robust performance, despite the dataset imbalance, underscores its ability to provide unbiased predictions. This approach could significantly enhance clinical decision-making and support personalized treatment strategies for brain metastases. Future research should validate these findings in larger, more diverse cohorts and explore the integration of additional data types to further optimize the model's clinical utility.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"11 2","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11860310/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143494721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiparametric Magnetic Resonance Imaging Findings of the Pancreas: A Comparison in Patients with Type 1 and 2 Diabetes.","authors":"Mayumi Higashi, Masahiro Tanabe, Katsuya Tanabe, Shigeru Okuya, Koumei Takeda, Yuko Nagao, Katsuyoshi Ito","doi":"10.3390/tomography11020016","DOIUrl":"10.3390/tomography11020016","url":null,"abstract":"<p><strong>Background/objectives: </strong>Diabetes-related pancreatic changes on MRI remain unclear. Thus, we evaluated the pancreatic changes on MRI in patients with both type 1 diabetes (T1D) and type 2 diabetes (T2D) using multiparametric MRI.</p><p><strong>Methods: </strong>This prospective study involved patients with T1D or T2D who underwent upper abdominal 3-T MRI. Additionally, patients without impaired glucose metabolism were retrospectively included as a control. The imaging data included pancreatic anteroposterior (AP) diameter, pancreas-to-muscle signal intensity ratio (SIR) on fat-suppressed T1-weighted image (FS-T1WI), apparent diffusion coefficient (ADC) value, T1 value on T1 map, proton density fat fraction (PDFF), and mean secretion grade of pancreatic juice flow on cine-dynamic magnetic resonance cholangiopancreatography (MRCP). The MR measurements were compared using one-way analysis of variance and the Kruskal-Wallis test.</p><p><strong>Results: </strong>Sixty-one patients with T1D (<i>n</i> = 7) or T2D (<i>n</i> = 54) and 21 control patients were evaluated. The pancreatic AP diameters were significantly smaller in patients with T1D than in patients with T2D (<i>p</i> < 0.05). The average SIR on FS-T1WI was significantly lower in patients with T1D than in controls (<i>p</i> < 0.001). The average ADC and T1 values of the pancreas were significantly higher in patients with T1D than in patients with T2D (<i>p</i> < 0.01) and controls (<i>p</i> < 0.05). The mean secretion grade of pancreatic juice flow was significantly lower in patients with T1D than in controls (<i>p</i> = 0.019). The average PDFF of the pancreas was significantly higher in patients with T2D than in controls (<i>p</i> = 0.029).</p><p><strong>Conclusions: </strong>Patients with T1D had reduced pancreas size, increased pancreatic T1 and ADC values, and decreased pancreatic juice flow on cine-dynamic MRCP, whereas patients with T2D had increased pancreatic fat content.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"11 2","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11861380/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143494710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Graph Neural Network Learning on the Pediatric Structural Connectome.","authors":"Anand Srinivasan, Rajikha Raja, John O Glass, Melissa M Hudson, Noah D Sabin, Kevin R Krull, Wilburn E Reddick","doi":"10.3390/tomography11020014","DOIUrl":"10.3390/tomography11020014","url":null,"abstract":"<p><strong>Purpose: </strong>Sex classification is a major benchmark of previous work in learning on the structural connectome, a naturally occurring brain graph that has proven useful for studying cognitive function and impairment. While graph neural networks (GNNs), specifically graph convolutional networks (GCNs), have gained popularity lately for their effectiveness in learning on graph data, achieving strong performance in adult sex classification tasks, their application to pediatric populations remains unexplored. We seek to characterize the capacity for GNN models to learn connectomic patterns on pediatric data through an exploration of training techniques and architectural design choices.</p><p><strong>Methods: </strong>Two datasets comprising an adult BRIGHT dataset (N = 147 Hodgkin's lymphoma survivors and N = 162 age similar controls) and a pediatric Human Connectome Project in Development (HCP-D) dataset (N = 135 healthy subjects) were utilized. Two GNN models (GCN simple and GCN residual), a deep neural network (multi-layer perceptron), and two standard machine learning models (random forest and support vector machine) were trained. Architecture exploration experiments were conducted to evaluate the impact of network depth, pooling techniques, and skip connections on the ability of GNN models to capture connectomic patterns. Models were assessed across a range of metrics including accuracy, AUC score, and adversarial robustness.</p><p><strong>Results: </strong>GNNs outperformed other models across both populations. Notably, adult GNN models achieved 85.1% accuracy in sex classification on unseen adult participants, consistent with prior studies. The extension of the adult models to the pediatric dataset and training on the smaller pediatric dataset were sub-optimal in their performance. Using adult data to augment pediatric models, the best GNN achieved comparable accuracy across unseen pediatric (83.0%) and adult (81.3%) participants. Adversarial sensitivity experiments showed that the simple GCN remained the most robust to perturbations, followed by the multi-layer perceptron and the residual GCN.</p><p><strong>Conclusions: </strong>These findings underscore the potential of GNNs in advancing our understanding of sex-specific neurological development and disorders and highlight the importance of data augmentation in overcoming challenges associated with small pediatric datasets. Further, they highlight relevant tradeoffs in the design landscape of connectomic GNNs. For example, while the simpler GNN model tested exhibits marginally worse accuracy and AUC scores in comparison to the more complex residual GNN, it demonstrates a higher degree of adversarial robustness.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"11 2","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11861995/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143494705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Deep Learning 3D CT Super-Resolution on AI-Based Pulmonary Nodule Characterization.","authors":"Dongok Kim, Chulkyun Ahn, Jong Hyo Kim","doi":"10.3390/tomography11020013","DOIUrl":"10.3390/tomography11020013","url":null,"abstract":"<p><strong>Background/objectives: </strong>Correct pulmonary nodule volumetry and categorization is paramount for accurate diagnosis in lung cancer screening programs. CT scanners with slice thicknesses of multiple millimetres are still common worldwide, and slice thickness has an adverse effect on the accuracy of the pulmonary nodule volumetry.</p><p><strong>Methods: </strong>We propose a deep learning based super-resolution technique to generate thin-slice CT images from thick-slice CT images. Analysis of the lung nodule volumetry and categorization accuracy was performed using commercially available AI-based lung cancer screening software.</p><p><strong>Results: </strong>The accuracy of pulmonary nodule categorization increased from 72.7 percent to 94.5 percent when thick-slice CT images were converted to generated-thin-slice CT images.</p><p><strong>Conclusions: </strong>Applying the super-resolution-based slice generation on thick-slice CT images prior to automatic nodule evaluation significantly increases the accuracy of pulmonary nodule volumetry and corresponding pulmonary nodule category.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"11 2","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11860810/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143494707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ultrashort Echo Time Magnetic Resonance Morphology of Discovertebral Junction in Chronic Low Back Pain Subjects.","authors":"Palanan Siriwananrangsun, Tim Finkenstaedt, Karen C Chen, Won C Bae","doi":"10.3390/tomography11020012","DOIUrl":"10.3390/tomography11020012","url":null,"abstract":"<p><p><i>Background:</i> Chronic low back pain (LBP) has been associated with intervertebral disc (IVD) degeneration, but its association with abnormal morphology at the discovertebral junction (DVJ) is unclear. The goal of this study was to evaluate the DVJ morphology in asymptomatic (Asx) and symptomatic (Sx) subjects for LBP using ultrashort echo time (UTE) MRI. <i>Methods:</i> We recruited 42 subjects (12 Asx and 32 Sx). Lumbar IVD degeneration was assessed using Pfirrmann grading (1 to 5), while the abnormality of DVJ (0 = normal; 1 = focal; 2 = broad abnormality) was assessed using UTE MRI. The effects of LBP and level on the mean IVD and DVJ grades, the correlation between IVD and DVJ grade, and the effect of LBP and age on the number of abnormal DVJs within a subject were determined. <i>Results:</i> IVD grade was higher in Sx subjects (<i>p</i> = 0.013), varying with disc level (<i>p</i> = 0.033), adjusted for age (<i>p</i> < 0.01). Similarly, DVJ grade was also significantly higher in Sx subjects (<i>p</i> = 0.001), but it did not vary with DVJ level (<i>p</i> = 0.7), adjusted for age (<i>p</i> = 0.5). There was a weak positive (rho = 0.344; <i>p</i> < 0.001) correlation between DVJ and IVD grade. The total number of abnormal DVJs within a subject was higher in Sx subjects (<i>p</i> < 0.001), but not with respect to age (<i>p</i> = 0.6) due to a large spread throughout the age range. <i>Conclusions:</i> These results demonstrate the feasibility of using in vivo UTE MRI of the lumbar spine to evaluate the DVJ and the correlation of DVJ with LBP. This study highlights the need for a better understanding of DVJ pathology and the inclusion of DVJ assessment in routine lumbar MRI.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"11 2","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11860485/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143494720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correlation of Coronary Calcium Measured on Conventional Computed Tomography with Coronary Angiography Findings in Lung Transplant Patients.","authors":"Sergio Tapia Concha, Concepción Fariñas-Álvarez, Pedro Muñoz Cacho, José Manuel Cifrian Martínez, Javier Zueco Gil, José Antonio Parra Blanco","doi":"10.3390/tomography11020011","DOIUrl":"10.3390/tomography11020011","url":null,"abstract":"<p><p><b>Introduction and objective:</b> The pre-transplant protocol for lung transplant candidates includes a chest CT scan to assess disease progression and often coronary angiography (CA) to rule out coronary artery disease (CAD). Coronary artery calcium is commonly observed in these pre-transplant CT scans. This study aims to evaluate the relationship between coronary calcium detected on CT and findings from CA to determine whether calcium presence could serve as an additional criterion for selecting patients for CA. <b>Material and Methods</b>: We included 252 consecutive lung transplant patients who had both a CT scan and CA within 365 days of each other. Coronary calcium quantification was performed using artery-based, segment artery-based, and visual assessment methods. CA findings were classified by stenosis severity: ≤20%, 21-70%, and >70%. <b>Results:</b> This study showed very high concordance (kappa = 0.896; 95% CI: 0.843-0.948) between the three methods, especially in distinguishing patients without and with coronary calcium (kappa = 1.000; 95% CI: 0.929-1.071). ROC analysis identified the absence of coronary calcium as the best cutoff to differentiate patients with ≤20% stenosis from those with >21%, with a sensitivity of 73.5%, specificity of 55.7%, PPV of 28.5%, and NPV of 90%. Only 11 patients (8.7%) without coronary calcium had stenosis of 21-70%, and only 2 (1.6%) had stenosis > 70%. <b>Conclusions:</b> The visual assessment method yielded results similar to the other two quantification methods. The absence of coronary calcium in pre-transplant CT may be a useful criterion for selecting patients for CA.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"11 2","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11860483/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143494704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 Residual Breast Cancer Post-Excisional Biopsy: Comparative Analysis of Contrast-Enhanced MRI with and Without Diffusion-Weighted Imaging.","authors":"Han Song Mun, Bong Joo Kang, Sung Hun Kim, Ga Eun Park","doi":"10.3390/tomography11010010","DOIUrl":"10.3390/tomography11010010","url":null,"abstract":"<p><strong>Objectives: </strong>To evaluate the effectiveness of breast MRI, including diffusion-weighted imaging (DWI), in detecting residual lesions in patients with malignancy after excisional biopsy.</p><p><strong>Methods: </strong>From January 2018 to December 2023, 3T breast MRI was performed to assess lesion morphology, residual size, and enhancement kinetics. The apparent diffusion coefficient (ADC) values were measured, and the diagnostic outcomes of CE-MRI, CE-MRI with DWI, mammography (MG), and ultrasound (US) were compared with clinical and histopathological data.</p><p><strong>Results: </strong>A total of 152 lesions were analyzed, with 36.2% showing residual malignancy. Both CE-MRI and CE-MRI with DWI effectively identified residual lesions, with significant differences in morphology, size, kinetic patterns, and ADC values (all <i>p</i> < 0.001). CE-MRI with DWI showed a sensitivity of 90.9% and an NPV of 93.6%, compared with 89.1% sensitivity and 92.2% NPV for CE-MRI alone. Sensitivities for MG and US were 57.1% and 38.7%, with NPVs of 64.7% and 59.6%, respectively. Diagnostic accuracy was highest for CE-MRI with DWI (80.9%), followed by CE-MRI (79.0%), MG (60.3%), and US (59.7%). The AUC for CE-MRI with DWI (0.831) was slightly higher than CE-MRI alone (0.811), though not significant (<i>p</i> = 0.095). AUCs for MG and US were lower at 0.623 and 0.563, with no significant difference between MG and US (<i>p</i> = 0.234).</p><p><strong>Conclusions: </strong>CE-MRI with DWI and CE-MRI alone were comparable and demonstrated excellent performance in discriminating between women with and without residual disease. Integrating CE-MRI with DWI could become a standard protocol for patients with suspected residual malignancy after excisional biopsy.</p>","PeriodicalId":51330,"journal":{"name":"Tomography","volume":"11 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11769435/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143034830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}