Quantitative Imaging in Medicine and Surgery最新文献

{"title":"Insights into structural deviations in attention deficit hyperactivity disorder (ADHD) and comorbidities using big data-derived brain charts: a cross-sectional study.","authors":"Min Chen, Dong Liu, Jun Feng, Tian Tian","doi":"10.21037/qims-2024-2707","DOIUrl":"10.21037/qims-2024-2707","url":null,"abstract":"<p><strong>Background: </strong>Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder that often coexists with other neurodevelopmental disorders. The intricate comorbidity of ADHD with depression, Tourette syndrome (TS), and autism spectrum disorder (ASD) presents substantial challenges in the screening, diagnosis, and management of these conditions. The aim of this study was to utilize big data-derived brain charts as an objective standard to assess brain development, comparing regional brain development differences between children with pure ADHD and those with comorbidities, and to explore the presumed correlation between specific structural deviations and the severity of ADHD symptoms.</p><p><strong>Methods: </strong>This is a large, population-based cross-sectional study with an observational design that prospectively enrolled 459 children with ADHD, using big data-derived brain charts as an objective standard for assessing brain development. Through normative brain chart modeling, we investigated regional brain development disparities between children with pure ADHD and those with comorbidities, exploring the associations between structural deviations and clinical symptoms.</p><p><strong>Results: </strong>Significant intergroup differences were observed in cortical thickness in the left cuneus gyrus (<i>F</i>=6.50, P_FDR =0.03) and medial occipito-temporal gyrus (<i>F</i>=5.75, P_FDR =0.04). The ADHD + TS group had the highest number of brain regions with extreme deviations compared to the other groups. Especially, the study found that the ADHD + TS group had a significantly higher proportion of negative deviations in the left middle frontal sulcus than the ADHD + Depression group (P_FDR <0.01). Principal component 1 of structural deviations showed significant negative correlations with inattention (r=-0.17, P<0.001) and oppositional defiant disorder (r=-0.10, P=0.04). Deviation scores across multiple cortical brain regions exhibited significant correlations with the inattention score (P_FDR <0.05).</p><p><strong>Conclusions: </strong>Brain charts effectively unveil structural variations in ADHD and comorbid groups, aiding in the prediction of inattention severity. These insights advance our understanding of ADHD's neurobiology and pave the way for personalized diagnostics and therapies.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"8320-8332"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397625/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978664","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":"Value of grayscale histogram analysis based on ultrasound images in diagnosing sarcopenia.","authors":"Kezhen Qin, Wen Chen, Hengtao Qi, Tiezheng Wang, Yeting Wang, Huawei Zhang, Jianbo Teng","doi":"10.21037/qims-2025-638","DOIUrl":"10.21037/qims-2025-638","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Sarcopenia, an age-related condition marked by progressive muscle loss and dysfunction, is a growing clinical and public health challenge. While current diagnostic methods involve limitations in cost, accessibility, and assessment of muscle quality, ultrasound offers a practical alternative. This study examined grayscale histogram analysis of gastrocnemius muscle ultrasound images as a novel quantitative method for diagnosing sarcopenia by evaluating its ability to detect textural changes associated with intramuscular fat infiltration and fibrosis, with the ultimate aim of establishing an accurate, accessible diagnostic approach.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A retrospective case-control study was conducted on 101 patients diagnosed with sarcopenia who were admitted to the Department of Endocrinology at Shandong Provincial Hospital between March and December 2024. Additionally, 101 healthy volunteers who underwent health examinations in our hospital during the same period were recruited as the control group. Grayscale histogram parameters, including the minimum gray value, maximum gray value, median gray value, mean gray value, standard deviation of gray values, skewness, kurtosis, and the gray values corresponding to seven percentile points (quantile 5, quantile 10, quantile 25, quantile 50, quantile 75, quantile 90, quantile 95) were extracted from the ultrasound images of the participants' gastrocnemius muscles. Statistical methods were used to analyze the differences between the sarcopenia and control groups. Receiver operating characteristic (ROC) curves were used to compare the differential diagnostic efficacy of each parameter and their combinations. Linear regression and least absolute shrinkage and selection operator (LASSO) were used to predict the probability of sarcopenia, with model performance evaluated with R&lt;sup&gt;2&lt;/sup&gt; values and the mean square error.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The grayscale histogram parameters of the gastrocnemius ultrasound images in the sarcopenia group, including the minimum gray value, maximum gray value, median gray value, mean gray value, standard deviation of gray values, and the gray values corresponding to seven percentile points, were significantly higher than those in the control group (P&lt;0.001), while both the skewness and kurtosis were smaller than those in the control group (P&lt;0.001). The gray value corresponding to quantile 75 demonstrated the best diagnostic efficacy [area under the curve (AUC) =0.988, sensitivity =96%, specificity =95%] at a cutoff of 132.5. The LASSO regression model outperformed linear regression (test set: R&lt;sup&gt;2&lt;/sup&gt; =0.769 &lt;i&gt;vs.&lt;/i&gt; 0.727; mean square error =0.057 &lt;i&gt;vs.&lt;/i&gt; 0.068).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The grayscale histogram parameters extracted from ultrasound images may be able to quantitatively reflect the differences between patients with sarcopenia and healthy individuals to some extent. Grayscale histogram a","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"7885-7895"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397623/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978660","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":"Development of a prediction model for HER2 low breast cancer using quantitative intra- and peri-tumoral heterogeneity and MRI features on high-spatial resolution ultrafast DCE-MRI.","authors":"Hongbing Luo, Shixuan Zhao, Zhe Chen, Juan Ji, Jing Ren, Yongjie Li, Peng Zhou","doi":"10.21037/qims-24-976","DOIUrl":"10.21037/qims-24-976","url":null,"abstract":"<p><strong>Background: </strong>Accurate preoperative human epidermal growth factor receptor 2 (HER2) status assessment is crucial for guiding treatment selection, particularly with the emergence of anti-HER2 antibody-drug conjugates (ADCs) for HER2-low breast cancer. However, current immunohistochemistry (IHC)-based classification is limited by spatial heterogeneity and sampling bias. Quantitative analysis of intra- and peri-tumoral heterogeneity (ITH) on imaging may offer a non-invasive, objective, and reproducible approach to distinguish HER2-low breast cancer from other subtypes. This study aimed to investigate quantitative ITH from high-spatial resolution ultrafast dynamic contrast-enhanced magnetic resonance imaging (UF DCE-MRI) based kinetic curves in distinguishing HER2 low from HER2 zero or positive breast cancer.</p><p><strong>Methods: </strong>Consecutive breast cancer patients who underwent preoperative high-spatial-resolution UF DCE-MRI were retrospectively enrolled. They were stratified into HER2 zero, HER2 low, or HER2 positive groups based on IHC and in situ hybridization results. Traditional MRI findings and clinicopathological characteristics were evaluated, and personalized ITH scores were constructed using semi-quantitative parameters derived from kinetic curves. Models incorporating ITH, MRI, and clinicopathological distinctions were developed for dichotomized HER2 statuses prediction using multivariable logistic regression. The added value of ITH in the Final Combined Model was evaluated.</p><p><strong>Results: </strong>This study enrolled 368 patients, with 45.9% (169/368) having HER2-low breast cancer. The ITH score was higher in HER2 low than that in HER2 zero (P<0.001), but lower than that in HER2 positive (P<0.001). The ITH score was higher in HER2 positive compared to HER2 zero (P<0.001). The Final Combined Model integrating ITH, MRI, and clinicopathological variables achieved good predictive performance, achieving area under the curve (AUC) values of 0.80 [95% confidence interval (CI): 0.75-0.86] for HER2 low <i>vs.</i> zero, 0.85 (95% CI: 0.80-0.89) for HER2 low <i>vs.</i> positive, and 0.83 (95% CI: 0.77-0.88) for HER2 zero <i>vs.</i> positive. The corresponding sensitivity/specificity values were 77%/72%, 77%/81%, and 94%/58%, respectively. The ITH score significantly enhanced HER2 status prediction, supported by AUC improvement (DeLong test, P<0.05), along with statistical significance in net reclassification improvement (NRI) (P<0.001) and integrated discrimination improvement (IDI) (P<0.001) across all tasks.</p><p><strong>Conclusions: </strong>Integrating ITH from high-spatial resolution UF DCE-MRI-based kinetic curves improved the non-invasive differentiation of HER2-low breast cancer. This approach may guide targeted biopsy strategies and aid in selecting candidates for anti-HER2 ADC therapy, optimizing HER2-targeted precision medicine.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"7788-7802"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397656/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978656","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":"Early-stage diagnosis of HIV-associated neurocognitive disorders via multiple learning models based on resting-state functional magnetic resonance imaging.","authors":"Chuanke Hou, Meng Zhang, Xingyuan Jiang, Hongjun Li","doi":"10.21037/qims-2025-290","DOIUrl":"10.21037/qims-2025-290","url":null,"abstract":"<p><strong>Background: </strong>People living with human immunodeficiency virus (PLWH) are at risk of human immunodeficiency virus (HIV)-associated neurocognitive disorders (HAND). The mildest disease stage of HAND is asymptomatic neurocognitive impairment (ANI), and the accurate diagnosis of this stage can facilitate timely clinical interventions. The aim of this study was to mine features related to the diagnosis of ANI based on resting-state functional magnetic resonance imaging (rs-fMRI) and to establish classification models.</p><p><strong>Methods: </strong>A total of 74 patients with 74 ANI and 78 with PLWH but no neurocognitive disorders (PWND) were enrolled. Basic clinical, T1-weighted imaging, and rs-fMRI data were obtained. The rs-fMRI signal values and radiomics features of 116 brain regions designated by the Anatomical Automatic Labeling template were collected, and the features were selected via the least absolute shrinkage and selection operator. rs-fMRI, radiomics, and combined models were constructed with five machine learning classifiers, respectively. Model performance was evaluated via the mean area under the curve (AUC), accuracy, sensitivity, and specificity.</p><p><strong>Results: </strong>Twenty-one rs-fMRI signal values and 28 radiomics features were selected to construct models. The performance of the combined models was exceptional, with the standout random forest (RF) model delivering an AUC value of 0.902 [95% confidence interval (CI): 0.813-0.990] in the validation set and 1.000 (95% CI: 1.000-1.000) in the training set. Further analysis of the 49 features revealed significantly overlapping brain regions for both feature types. Three key features demonstrating significant differences between ANI and PWND were identified (all P values <0.001). These features correlated with cognitive test performance (r>0.3).</p><p><strong>Conclusions: </strong>The RF combined model exhibited high classification performance in ANI, enabling objective and reliable individual diagnosis in clinical practice. It thus represents a novel method for characterizing the brain functional impairment and pathophysiology of patients with ANI. Greater attention should be paid to the frontoparietal and striatum in the research and clinical work related to ANI.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"7989-8007"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397634/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978628","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":"Risk prediction models for biochemical recurrence of Chinese prostate cancer patients after radical prostatectomy based on magnetic resonance imaging examination: a systematic review.","authors":"Yu Wang, Yao Shi, Li Wang, Wenli Rong, Yunhong Du, Yuliang Duan, Lili Peng","doi":"10.21037/qims-2024-2843","DOIUrl":"10.21037/qims-2024-2843","url":null,"abstract":"<p><strong>Background: </strong>Biochemical recurrence (BCR) after radical prostatectomy (RP) affects the prognosis of patients and early accurate prediction is crucial. Magnetic resonance imaging (MRI) is of great value in the assessment of prostate cancer (PCa). However, there is a lack of a systematic summary of the current research status for the construction of a postoperative BCR prediction model applicable to Chinese PCa patients based on MRI features. This study aimed to systematically evaluate the predictive performance and clinical applicability of the available models.</p><p><strong>Methods: </strong>A standardized search of relevant literature in the PubMed, Cochrane Library, Embase, Web of Science, CINAHL, CNKI, VIP, Wanfang Data, and CBM databases was performed, with the search time restricted to the establishment of the database to 11 September 2024. Studies that developed and/or validated prediction models based on MRI examination to identify and/or predict BCR in patients after RP in China were included. Two researchers independently screened the literature and used the prediction model risk of bias assessment tool to assess the quality of research on the prediction models and performed descriptive analyses of predictor variables for modeling.</p><p><strong>Results: </strong>A total of 17 studies were included, and 41 prediction models for BCR risk in Chinese patients after RP based on MRI examination were constructed, with the area under the receiver operating characteristic curve (AUC) or concordance index (C-index) of the cases ranging from 0.610 to 0.982. A total of 36 prediction models had good predictive performance, eight studies performed model calibration, two studies performed internal validation, two studies performed external validation, and seven studies conducted both internal and external validation. The results of the quality assessment revealed that all 17 studies were at high risk of bias. The most frequent predictors were prostate-specific antigen (PSA) level, MRI image features, and Gleason score.</p><p><strong>Conclusions: </strong>At present, a prediction model based on MRI examination for the risk of BCR in Chinese patients after RP is still in the development stage, and the overall quality of research needs to be further improved. In the future, the study design and reporting process should be improved, and the existing model should be validated to provide a basis for the development of effective prevention strategies.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"8648-8662"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397703/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978686","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 association between the Charlson Comorbidity Index and prognosis in patients with supratentorial spontaneous intracerebral hemorrhage following hematoma evacuation.","authors":"Qiangjun Wu, Huirong Xie, Hao Chen, Jingping Sun, Bailong Xin","doi":"10.21037/qims-2024-2789","DOIUrl":"10.21037/qims-2024-2789","url":null,"abstract":"<p><strong>Background: </strong>Spontaneous intracerebral hemorrhage (ICH) carries high mortality and morbidity. Compared to deep ICH, acute lobar ICH has distinct profiles and poorer early prognosis, frequently associated with non-hypertensive etiologies. The Charlson Comorbidity Index (CCI) is linked to critical ICH outcomes. This study assessed the relationship between CCI and prognosis following hematoma evacuation in supratentorial spontaneous ICH patients.</p><p><strong>Methods: </strong>Three hundred and eighty-one patients with spontaneous supratentorial ICH underwent hematoma evacuation, with their CCI scores categorized into low and high comorbidity groups. Following an analysis of demographic data, medical history, clinical and imaging characteristics, and poor outcomes [modified Rankin Scale (mRS) 4-6], the study examined the differences in CCI between the two groups. Logistic regression analysis was conducted to assess the correlation between CCI and the poor outcomes in patients with supratentorial ICH after hematoma evacuation.</p><p><strong>Results: </strong>Of the 381 patients with ICH who underwent hematoma evacuation, the high comorbidity group had a higher proportion of medical histories including diabetes, stroke, hemorrhage, heart disease, and anticoagulant use compared to the low comorbidity group. Additionally, the high comorbidity group exhibited significantly higher preoperative hematoma volume and postoperative hematoma volume than the low comorbidity group. The incidence of postoperative rehemorrhage [23 (6.8%) <i>vs.</i> 7 (17.1%), P=0.045] and 6-month poor outcomes (mRS 4-6) [209 (61.5%) <i>vs.</i> 37 (90.2%), P<0.001] was also higher in the High comorbidity group. According to logistic regression analysis, a high CCI score was independently associated with poor outcomes in Model 1 [Model 1, odds ratio (OR) 5.80; 95% confidence interval (CI): 2.02-16.64; P=0.001]. After adjusting for clinical preset variables in Model 2, the difference remained statistically significant (Model 2, OR 7.48; 95% CI: 2.15-25.96; P=0.002). After adjusting for baseline differences and clinical preset variables, the results remained consistent (Model 3, OR 10.68; 95% CI: 2.76-41.30; P<0.001; Model 4, OR 10.89; 95% CI: 2.75-43.05; P<0.001).</p><p><strong>Conclusions: </strong>In patients with supratentorial ICH post-evacuation, a higher CCI score correlates with poorer prognosis. The high CCI group has a ninefold increased risk of unfavorable outcomes, which guides clinical treatment and prognostic assessment.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"8055-8063"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397637/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978701","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":"Habitat analysis based on magnetic resonance imaging for the prediction of prostate cancer: a dual-center study.","authors":"Zijian Gong, Zhixuan Liu, Kaiyao Huang, Jie Zou, Zijing Wu, Yun Peng, Hongxing Ying, Lianggeng Gong, Xiaochang Xiang, Yinquan Ye","doi":"10.21037/qims-2025-223","DOIUrl":"10.21037/qims-2025-223","url":null,"abstract":"<p><strong>Background: </strong>The application of habitat analysis is anticipated to enhance the diagnostic efficacy of magnetic resonance imaging (MRI) in prostate cancer (PCa) by providing a more accurate reflection of the microenvironmental characteristics within the lesion. The objective of this study was to investigate the feasibility of multisequence and multiregional MRI-based habitat analysis in the differentiation of PCa and benign prostatic hyperplasia (BPH).</p><p><strong>Methods: </strong>We retrospectively evaluated the data of 673 cases from The Second Affiliated Hospital of Nanchang University and The First Hospital of Xiushui who received MRI examination of the prostate and pathologically confirmed diagnosis of PCa or BPH. Habitat features and classical radiomic features from the regions of lesions and prostate gland (PG) were extracted for model construction. Receiver operating characteristic analysis was used to assess the performance of the models. An integrated nomogram combining dominant models and clinical variables was ultimately constructed. In addition, we further assessed the performance of the nomogram in a subgroup of early-stage lesions without capsular invasion (CIV). The Delong test was used to compare the differences in the area under receiver operating characteristic curve (AUC) between models.</p><p><strong>Results: </strong>The AUCs of the habitat radiomics score (rad-score) based on the lesion (LHrad-score) in both the internal (0.898) and external validation (0.878) sets were higher than those of the rad-score based on the lesion (0.860 and 0.854, respectively). The AUCs of the classical rad-score based on PG (PCrad-score; 0.883 and 0.865 in the internal and external sets, respectively) were higher than those of the habitat rad-score based on PG (0.871 and 0.773, respectively). By combining the PCrad-score and LHrad-score with clinically independent predictors, the nomogram yielded AUCs of 0.899 and 0.963 in the internal and external sets, respectively. Discrimination between early-stage PCa and BPH in the overall validation set yielded an AUC of 0.802.</p><p><strong>Conclusions: </strong>The habitat analysis may serve as a means to noninvasively and preoperatively identifying PCa from BPH, even in the early stages of PCa.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"8395-8408"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397675/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978710","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":"Quantitative assessment of hypertrophic obstructive cardiomyopathy with intraoperative three-dimensional epicardial and transesophageal echocardiography.","authors":"Mireia Pozo Albiol, Azad Mashari, Ricard Navarro-Ripoll, Anthony Ralph-Edwards, Ella Huszti, Qixuan Li, Jacobo Moreno Garijo","doi":"10.21037/qims-2024-2822","DOIUrl":"10.21037/qims-2024-2822","url":null,"abstract":"<p><strong>Background: </strong>Hypertrophic obstructive cardiomyopathy (HOCM), a subset of hypertrophic cardiomyopathy (HCM), is characterized by dynamic left ventricular outflow tract (LVOT) obstruction, often caused by systolic anterior motion (SAM) of the mitral valve and septal hypertrophy. Accurate intraoperative assessment of septal morphology, SAM distance, and LVOT area (LVOTa) is critical for surgical planning during septal myectomy. While transesophageal echocardiography (TEE), particularly with three-dimensional (3D) imaging, is the standard modality for evaluating these parameters, it may be contraindicated or suboptimal in select cases. Real-time 3D epicardial echocardiography (EE) offers an alternative imaging approach that allows direct visualization of the heart intraoperatively without esophageal instrumentation. This study investigates the utility of 3D EE compared to 3D TEE for quantitative assessment of septal left ventricular wall thickness (LVWT), SAM distance, and LVOTa in HOCM patients undergoing myectomy. The primary aim is to assess whether 3D EE and TEE measurements correlate and can be used interchangeably. A secondary aim is to compare 2D and 3D measurements by both modalities.</p><p><strong>Methods: </strong>Perioperative data of 59 patients with HOCM were obtained by retrospective review in a tertiary care setting. 2D and 3D intraoperative transesophageal and EE studies were assessed performing multiple measurements relevant for myectomy. Demographic and clinical data were summarized with descriptive statistics, while the Altman-Bland method assessed the interchangeability of three-dimensional transesophageal and EE measurements. Inter- and intraobserver variabilities were evaluated using the Bland-Altman method and intraclass correlation coefficient.</p><p><strong>Results: </strong>Off-line analysis of 3D data sets with Qlab Phillips was feasible in 79.7% of the patients. No significant differences were found between epicardial and transesophageal echocardiographic intraoperative measurements by 2D: septal LVWT (P=0.59), SAM distance (P=0.40) or LVOTa (P=0.22), or by 3D: septal LVWT (P=0.42), SAM distance (P=0.23) or LVOTa (P=0.38).</p><p><strong>Conclusions: </strong>Intraoperative EE demonstrates equal potential utility in guiding HOCM patients when TEE is not an option or is contraindicated. These findings underscore the clinical significance of EE as a reliable alternative for image guidance during myectomy in HOCM patients, contributing to improved surgical outcomes.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 8","pages":"7195-7209"},"PeriodicalIF":2.3,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12332657/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144818308","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 atrial myxoma complicated by a coronary artery fistula due to rupture of the feeding artery: a case description.","authors":"Wanyan Li, Lin Li, Chunying Yu, Junjie Sun, Ting Gao, Lihong Wang","doi":"10.21037/qims-2025-185","DOIUrl":"10.21037/qims-2025-185","url":null,"abstract":"","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 8","pages":"7589-7594"},"PeriodicalIF":2.3,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12332604/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144818283","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":"Obstructive sleep apnea as a possible mediator for the association between glymphatic function and body mass index in Parkinson's disease.","authors":"Jiri Nepozitek, Karel Sonka","doi":"10.21037/qims-2025-1124","DOIUrl":"10.21037/qims-2025-1124","url":null,"abstract":"","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 8","pages":"7674-7675"},"PeriodicalIF":2.3,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12332613/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144818288","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}