Quantitative Imaging in Medicine and Surgery最新文献

{"title":"Uncommon presentation of Castleman disease in the duodenum: a case description and computed tomography imaging analysis.","authors":"Shuang Lai, Chunhong Hu, Qian Zheng","doi":"10.21037/qims-24-704","DOIUrl":"10.21037/qims-24-704","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/PMC11485329/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480717","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":"Support vector machine classification of irritable bowel syndrome patients based on whole-brain resting-state functional connectivity features.","authors":"Lei Xie, Zelin Zhuang, Xiaona Lin, Xiaoyan Shi, Yanmin Zheng, Kailuan Wu, Shuhua Ma","doi":"10.21037/qims-24-892","DOIUrl":"10.21037/qims-24-892","url":null,"abstract":"<p><strong>Background: </strong>Irritable bowel syndrome (IBS) is a disorder characterized by signaling dysregulation between the brain and gut, leading to gastrointestinal dysfunction. Symptoms such as abdominal pain and constipation can manifest periodically or persistently, and negative emotions may exacerbate the symptoms. Previous studies have shown that the pathogenesis of IBS is closely related to the brain-gut axis and brain function, but there are still difficulties in disease diagnosis. Therefore, this study applied a machine-learning approach based on resting-state functional magnetic resonance imaging (rs-fMRI) whole-brain functional connectivity (FC) to distinguish IBS patients from healthy controls (HCs).</p><p><strong>Methods: </strong>A total of 176 subjects, comprising 88 consecutive patients with IBS and 88 age-, sex- and education-matched HCs, were enrolled in this study between January 2020 and January 2024 at the First Affiliated Hospital of Shantou University Medical College. All the subjects underwent rs-fMRI and high-resolution anatomical T1-weighted imaging (T1WI) examinations. Following the preprocessing of the rs-fMRI image data, FC matrices between all regions of interest (ROIs) were extracted using automated anatomical labeling (AAL). Subsequently, supervised machine learning was performed using whole-brain FC for classification features to identify the best-performing model. Finally, weights of the optimal model's features were exported to confirm the neuroanatomical regions significantly influencing model establishment.</p><p><strong>Results: </strong>Compared with other supervised learning models, the support vector machine (SVM) model had significantly higher classification accuracy and performed significantly better than the other models (P<0.05) with a classification accuracy of 75% and an area under the curve (AUC) of 0.7788 (95% confidence interval [CI]: 0.6861-0.8715) (P<0.01). In addition, the FC features from the Rolandic operculum (ROL) to the anterior cingulate gyrus (ACG), the calcarine sulcus (CAL) to the triangular part of the inferior frontal gyrus (IFG), the gyrus rectus (REC) to the inferior occipital gyrus (IOG), the lingual gyrus (LING) to the putamen (PUT), and the IOG to the angular gyrus (ANG) were relatively important in the construction of the machine-learning models.</p><p><strong>Conclusions: </strong>The SVM was the optimal machine-learning model for effectively classifying IBS patients and HCs based on whole-brain resting-state FC matrices. The FC features between the emotion-related brain regions significantly affected the construction of the machine-learning models. As a classification feature in machine learning, whole-brain resting-state FC holds the potential to achieve precision medicine in IBS and enhance disease diagnostic efficacy.</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/PMC11485364/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480663","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 transition from hypertension to hypertensive heart disease and heart failure with preserved ejection fraction: a retrospective cross-sectional study of myocardial magnetic resonance strain and tissue characteristics.","authors":"Rui Li, Feng Lei, Feng Liu, Liang Cao, Xu Cao, Meng Niu, Shunlin Guo","doi":"10.21037/qims-24-803","DOIUrl":"10.21037/qims-24-803","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Due to the variability of symptoms and signs associated with heart failure, along with the lack of specific tests for definitive diagnosis, the noninvasive diagnosis of heart failure with preserved ejection fraction (HFpEF) continues to pose significant clinical challenges. This investigation was designed to elucidate the clinical manifestations of HFpEF and to analyze cardiac magnetic resonance (CMR)-derived myocardial strain metrics and tissue characteristics in a cohort exhibiting HFpEF with hypertension (HFpEF-HTN).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This retrospective analysis consisted of 128 patients diagnosed HFpEF-HTN, 78 individuals with hypertensive heart disease (HHD), 89 individuals with hypertension (HTN), and 60 normotensive healthy controls and was conducted from August 2021 to February 2024. All participants were recruited from The First Hospital of Lanzhou University and underwent laboratory examinations and 3.0 T CMR. The study compared clinical features and CMR-derived structural and functional parameters across different groups. Logistic regression was employed to determine the association between CMR parameters and HFpEF-HTN. Spearman correlation coefficient analysis was used to clarify the relationship between myocardial strain parameters and left ventricular (LV) ejection fraction and right ventricular (RV) ejection fraction. Additionally, the area under the curve (AUC) from receiver operating characteristic (ROC) analysis was used to compare the diagnostic performance of different CMR parameters for HFpEF-HTN.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Patients diagnosed with (HFpEF-HTN) were characterized by an older demographic profile, a higher prevalence of smoking history, elevated systolic and diastolic blood pressure, increased levels of N-terminal pro-brain natriuretic peptide, and more advanced New York Heart Association functional class as compared to other studied groups. In terms of myocardial deformation, individuals with HFpEF-HTN exhibited pronounced impairments in both LV and RV function, as evidenced by significantly reduced longitudinal strain (LS), circumferential strain (CS), and radial strain (RS), relative to HTN, HHD, the control cohorts (all P values &lt;0.001). Patients with HFpEF-HTN showed significantly elevated levels of late gadolinium enhancement, native T1, and extracellular volume fraction (ECV) indicative of myocardial interstitial fibrosis as compared to patients with HHD. Additionally, as compared to ECV, LV GCS emerged as a superior diagnostic indicator, demonstrating greater diagnostic accuracy in differentiating HFpEF-HTN patients from those with HHD (AUC =0.85; P&lt;0.001). Moreover, LVEF showed a mild correlation with CMR-derived LV GLS (R=-0.43; P&lt;0.001), LV GCS (R=-0.42; P&lt;0.001), and LV GRS, (R=0.56; P&lt;0.001) in all patients.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Myocardial strain, T1 mapping, and ECV can be used for the quantitative evaluation of LV and RV ventricular ","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/PMC11485389/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480709","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":"Discriminating bronchiolar adenoma from peripheral lung cancer by thin-section computed tomography (CT): a 2-center study.","authors":"Yang Tao, Ting-Wei Xiong, Qing-Shu Li, Shi-Hai Yang, Fa-Jin Lv, Zhi-Gang Chu","doi":"10.21037/qims-24-687","DOIUrl":"10.21037/qims-24-687","url":null,"abstract":"<p><strong>Background: </strong>Bronchiolar adenoma (BA) is frequently misdiagnosed as peripheral lung cancer (PLC) because it resembles PLC. Computed tomography (CT) examination is an effective tool for detecting and diagnosing lung diseases. To date, there has been no comprehensive study on the differential diagnosis of BAs and PLCs using thin-section computed tomography (TSCT) based on a large sample, and the efficiency of CT in diagnosing BAs has not been verified. The goal of this study was to distinguish BA from PLC by summarizing their clinical and TSCT characteristics.</p><p><strong>Methods: </strong>A retrospective cross-sectional study on 71 cases with BAs and 218 matched controls with PLCs (from March 2020 to May 2023) within 2 centers (The First Affiliated Hospital of Chongqing Medical University and the Second Affiliated Hospital of Army Medical University) was conducted to investigate their clinical and radiological differences. The clinical characteristics and TSCT features of BAs and PLCs were summarized and compared. A multivariate logistic regression analysis was performed to reveal the key predictors of BAs.</p><p><strong>Results: </strong>The BAs and PLCs exhibited significant differences in TSCT features. Multivariate analysis revealed that the lesion being located in basal segments [odds ratio (OR), 17.835; 95% confidence interval (CI): 6.977-45.588; P<0.001], irregular shape (OR, 4.765; 95% CI: 1.877-12.099; P=0.001), negative of spiculation sign (OR, 7.436; 95% CI: 2.063-26.809; P=0.002), central vessel sign with pulmonary artery (OR, 3.576; 95% CI: 1.557-8.211; P=0.003), peripheral vessel sign with pulmonary vein (OR, 12.444; 95% CI: 4.934-31.383; P<0.001), and distance from lesion edge to pleura (D-ETP) ≤5 mm (OR, 5.535; 95% CI: 2.346-13.057; P<0.001) were independent predictors of BAs, and the area under the curve (AUC) of this model was 0.935; 95% CI: 0.901-0.960 (sensitivity: 88.0%, specificity: 86.03%, P<0.001).</p><p><strong>Conclusions: </strong>Peripheral pulmonary nodules locating in the basal segment of lower lobe with irregular shape, central vessel sign with pulmonary artery, peripheral vessel sign with pulmonary vein and D-ETP ≤5 mm, but without spiculation sign, should be highly suspected of BAs.</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/PMC11485361/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480613","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":"Evaluation of the presence and severity of spontaneous splenorenal or gastrorenal shunts via four-dimensional flow magnetic resonance imaging: a preliminary study.","authors":"You Zheng, Qiong Hu, Jun Zhou, Xiang Li, Xiaojing He, Tianwu Chen, Xi Liu, Weijuan Chen, Xin Li, Dajing Guo","doi":"10.21037/qims-24-826","DOIUrl":"10.21037/qims-24-826","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Four-dimensional phase-contrast magnetic resonance imaging (4D flow MRI) is a relatively new type of MRI acquisition technique that provides a unique and comprehensive set of information within a single acquisition, including hemodynamic and anatomical information. This study was designed to noninvasively evaluate the correlation between the presence and severity of spontaneous splenorenal shunt (SRS) or gastrorenal shunt (GRS) and 4D flow MRI-derived parameters.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This retrospective case-control study enrolled 70 patients who were diagnosed with hepatocirrhosis portal hypertension and admitted to the Second Affiliated Hospital of Chongqing Medical University. Patients were divided into three groups according to the diameter of the SRS and GRS. 4D flow MRI-derived parameters, including the turbulent kinetic energy, total volume (TV), flow velocity, blood flow volume (BFV), maximum flow (MF), wall shear stress, and relative pressure, were obtained for eight cut planes: proximal to the splenomesenteric confluence and liver hilum of the portal vein (PV&lt;sub&gt;1&lt;/sub&gt;/PV&lt;sub&gt;2&lt;/sub&gt;); the left/right branch of the bifurcation of the PV (LPV/RPV), at the mesosplenic confluence of the splenic vein (SV&lt;sub&gt;1&lt;/sub&gt;), at the splenic hilum of the SV (SV&lt;sub&gt;2&lt;/sub&gt;); at the proximal to the splenomesenteric confluence of the superior mesenteric vein (SMV&lt;sub&gt;1&lt;/sub&gt;), and 5 cm from the splenomesenteric confluence of the SMV (SMV&lt;sub&gt;2&lt;/sub&gt;). Comparisons among the three groups were based on one-way analysis of variance (ANOVA). Logistic regression was used to identify the risk factors for small SRS/GRS (S-SRS/GRS) and for large SRS/GRS (L-SRS/GRS). Receiver operating characteristic curves were used to evaluate the diagnostic performance of the independent risk factors for SRS and GRS. The associations between the clinical data and the 4D flow MRI-derived parameters of GRS and SRS were assessed via Spearman correlation coefficient analysis.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The presence of SRS or GRS was correlated with TV&lt;sub&gt;LPV&lt;/sub&gt; (r=-0.302; P=0.035), TV&lt;sub&gt;PV1&lt;/sub&gt; (r=-0.385; P=0.001), TV&lt;sub&gt;PV2&lt;/sub&gt; (r=-0.301; P=0.013), BFV&lt;sub&gt;PV1&lt;/sub&gt; (r=-0.360; P=0.010), BFV&lt;sub&gt;SMV2&lt;/sub&gt; (r=0.371; P=0.008), MF&lt;sub&gt;PV1&lt;/sub&gt; (r=-0.341; P=0.004), and MF&lt;sub&gt;PV2&lt;/sub&gt; (r=-0.291; P=0.017). Meanwhile, the severity of the SRS or GRS was correlated with alanine aminotransferase level (r=-0.535; P&lt;0.001), BFV&lt;sub&gt;LPV&lt;/sub&gt; (r=-0.560; P=0.008), aspartate aminotransferase level (r=-0.321; P=0.038), and model for end-stage liver disease score (r=0.323; P=0.039). TV&lt;sub&gt;PV1&lt;/sub&gt;, TV&lt;sub&gt;PV2&lt;/sub&gt;, BFV&lt;sub&gt;PV1,&lt;/sub&gt; BFV&lt;sub&gt;PV2&lt;/sub&gt;, and MF&lt;sub&gt;SMV2&lt;/sub&gt; were found to be independent risk factors for L-SRS/GRS, with intermediate diagnostic efficacy, with the area under the curve (AUC)&lt;sub&gt;TV PV1&lt;/sub&gt;=0.706 [95% confidence interval (CI): 0.519-0.853; sensitivity, 61.54%; specificity, 80.77%; P=0.018], AUC&lt;sub&gt;BF","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/PMC11485384/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480616","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":"Multiple myeloma segmentation net (MMNet): an encoder-decoder-based deep multiscale feature fusion model for multiple myeloma segmentation in magnetic resonance imaging.","authors":"Xin Zhao, Lili Chen, Nannan Zhang, Yuchan Lv, Xue Hu","doi":"10.21037/qims-24-683","DOIUrl":"10.21037/qims-24-683","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Patients with multiple myeloma (MM), a malignant disease involving bone marrow plasma cells, shows significant susceptibility to bone degradation, impairing normal hematopoietic function. The accurate and effective segmentation of MM lesion areas is crucial for the early detection and diagnosis of myeloma. However, the presence of complex shape variations, boundary ambiguities, and multiscale lesion areas, ranging from punctate lesions to extensive bone damage, presents a formidable challenge in achieving precise segmentation. This study thus aimed to develop a more accurate and robust segmentation method for MM lesions by extracting rich multiscale features.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;In this paper, we propose a novel, multiscale feature fusion encoding-decoding model architecture specifically designed for MM segmentation. In the encoding stage, our proposed multiscale feature extraction module, dilated dense connected net (DCNet), is employed to systematically extract multiscale features, thereby augmenting the model's sensing field. In the decoding stage, we propose the CBAM-atrous spatial pyramid pooling (CASPP) module to enhance the extraction of multiscale features, enabling the model to dynamically prioritize both channel and spatial information. Subsequently, these features are concatenated with the final output feature map to optimize segmentation outcomes. At the feature fusion bottleneck layer, we incorporate the dynamic feature fusion (DyCat) module into the skip connection to dynamically adjust feature extraction parameters and fusion processes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;We assessed the efficacy of our approach using a proprietary dataset of MM, yielding notable advancements. Our dataset comprised 753 magnetic resonance imaging (MRI) two-dimensional (2D) slice images of the spinal regions from 45 patients with MM, along with their corresponding ground truth labels. These images were primarily obtained from three sequences: T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and short tau inversion recovery (STIR). Using image augmentation techniques, we expanded the dataset to 3,000 images, which were employed for both model training and prediction. Among these, 2,400 images were allocated for training purposes, while 600 images were reserved for validation and testing. Our method showed increase in the intersection over union (IoU) and Dice coefficients by 7.9 and 6.7 percentage points, respectively, as compared to the baseline model. Furthermore, we performed comparisons with alternative image segmentation methodologies, which confirmed the sophistication and efficacy of our proposed model.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Our proposed multiple myeloma segmentation net (MMNet), can effectively extract multiscale features from images and enhance the correlation between channel and spatial information. Furthermore, a systematic evaluation of the proposed network architecture was condu","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/PMC11485342/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480640","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":"Predicting the Ki-67 proliferation index in cervical cancer: a preliminary comparative study of four non-Gaussian diffusion-weighted imaging models combined with histogram analysis.","authors":"Yun Su, Kunjie Zeng, Zhuoheng Yan, Xiaojun Yang, Lingjie Yang, Lu Yang, Riyu Han, Fengqiong Huang, Hong Deng, Xiaohui Duan","doi":"10.21037/qims-24-576","DOIUrl":"10.21037/qims-24-576","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;The prognosis for patients with cervical cancer (CC) is strongly correlated with the Ki-67 proliferation index (PI). However, the Ki-67 PI obtained through biopsy has certain limitations. The non-Gaussian distribution diffusion model of magnetic resonance imaging (MRI) may play an important role in characterizing tissue heterogeneity. At present, there are limited data available concerning the prediction of Ki-67 PI using models based on histogram features of non-Gaussian diffusion distribution. This study aimed to determine whether preoperative histogram features from multiple non-Gaussian models of diffusion-weighted imaging can predict the Ki-67 PI in patients with CC.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Our cross-sectional prospective study recruited a total of 53 patients suspected of having CC who underwent 3.0-T MRI at Sun Yat-sen Memorial Hospital of Sun Yat-sen University between January 2022 and January 2023. Fifteen b values (0-4,000 s/mm&lt;sup&gt;2&lt;/sup&gt;) were used for diffusion-weighted imaging. A total of nine parameters from four non-Gaussian diffusion-weighted imaging models, including continuous-time random walk (CTRW), diffusion kurtosis imaging (DKI), fractional order calculus (FROC), and intravoxel incoherent motion (IVIM), were used. Whole-tumor volumetric histogram analysis of these parameters was then obtained. In logistic regression, significant histogram characteristics were statistically examined across two groups to build the final prediction model. To assess diagnostic parameters of the proposed model in the diagnosis of the Ki-67 PI, along with the sensitivity, specificity, and diagnostic accuracy of these various parameters from the four models, receiver operating feature analysis was applied.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Among the 53 patients (55.3±9.6 years, ranging from 23 to 79 years) included in the study, 15 had a Ki-67 PI ≤50% and 38 had a Ki-67 PI &gt;50%. Univariable analysis determined that 12 histogram features were statistically different between the two groups. In multivariable logistic regression, we ultimately selected 6 histogram features to construct the final prediction model, with CTRW_α_10&lt;sup&gt;th&lt;/sup&gt; percentile [odds ratio (OR) =0.955; 95% confidence interval (CI): 0.92-0.99; P=0.019], CTRW_α_robust mean absolute deviation (OR =0.893; 95% CI: 0.81-0.99; P=0.028), and CTRW_α_uniformity (OR =0.000, 95% CI: 0.00-0.90, P=0.047) being the independent predictive variables. The area under the curve of the combined prediction model was 0.845 (95% CI: 0.74-0.95), with a sensitivity of 78.9% (95% CI: 0.63-0.90), a specificity of 86.7% (95% CI: 0.60-0.98), an accuracy of 81.1% (95% CI: 0.68-0.91), a positive predictive value of 93.8% (95% CI: 0.79-0.99), and a negative predictive value of 61.9% (95% CI: 0.38-0.82).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The histogram features of multiple non-Gaussian diffusion-weighted imaging can help to predict the Ki-67 PI of CC, providing a new meth","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/PMC11485368/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480643","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":"Predictors of nasolacrimal duct intubation failure for primary acquired nasolacrimal duct obstruction: a computed tomography-dacryocystography (CT-DCG) study.","authors":"Wushuang Wang, Tong Lin, Lan Gong, Yan Wang","doi":"10.21037/qims-24-519","DOIUrl":"10.21037/qims-24-519","url":null,"abstract":"<p><strong>Background: </strong>Making a choice between nasolacrimal duct intubation and dacryocystorhinostomy (DCR) for primary acquired nasolacrimal duct obstruction (PANDO) is an important issue in clinical practice. This study aimed to determine the potential lacrimal sac characteristics that could be used as predictors of unsuccessful intubation for PANDO based on computed tomography-dacryocystography (CT-DCG).</p><p><strong>Methods: </strong>In this retrospective comparative observational study, we included PANDO patients with a history of failed intubation for nasolacrimal duct obstruction as the intubation failure group and PANDO patients without a history of intubation as the control group. We analyzed the lacrimal sac height, lacrimal sac width, and obstruction site based on CT-DCG, all measured based on several reference levels on axial sections (upper, intermediate, lower level, common canaliculus level, and lowermost contrast level), which were defined according to the contrast and the bony structure.</p><p><strong>Results: </strong>A total of 114 sides of the PANDO were studied, including 36 in the intubation failure group and 78 in the control group. The intubation failure group showed a smaller lacrimal sac height (11.69±4.59 mm) and width (2.28±1.97 mm, intermediate level) than the control group (14.13±2.92, 3.32±2.02 mm, P=0.005 and 0.012, respectively). The intubation failure group had a higher obstruction site than the control group (P=0.009).</p><p><strong>Conclusions: </strong>A small lacrimal sac and high obstruction site are predictors of nasolacrimal duct intubation failure in PANDO. For PANDO patients with a small lacrimal sac or a high obstruction position, DCR is recommended as opposed to intubation.</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/PMC11485350/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480655","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":"Testicular arterial blood flow volume in predicting semen improvement following microscopic subinguinal varicocelectomy.","authors":"Wei Fu, Jun Cui, Shaoshan Tang","doi":"10.21037/qims-24-105","DOIUrl":"10.21037/qims-24-105","url":null,"abstract":"<p><strong>Background: </strong>Varicocele is a significant but treatable contributor to male infertility. The efficacy of varicocelectomy in improving sperm quality is not consistent, with only 60-80% of patients experiencing improved semen quality. This prospective cohort study aimed to evaluate the effect of microscopic subinguinal varicocelectomy (MSV) on testicular arterial blood flow volume (TABFV) and to determine the value of preoperative TABFV in predicting the outcome of MSV.</p><p><strong>Methods: </strong>Patients with varicocele who underwent MSV at the same clinical center between July 2020 and April 2023 were enrolled. All patients underwent ultrasound assessment and at least one semen analysis before and after MSV. Both univariate and multivariate logistic regression analyses were performed to assess the association between pre-MSV variables and semen improvement after MSV. Subsequently, a diagnostic model was developed.</p><p><strong>Results: </strong>This study enrolled 96 patients with varicocele, including 31 who showed semen improvement after MSV and 65 who did not. The postoperative semen-improved group demonstrated a significant increase in TABFV of the right testis (TABFV-R) and left testis (TABFV-L) (P<0.001). Notably, the postoperative TABFV-L was more than twice the preoperative TABFV-L. Preoperative TABFV-R and a combination of subclinical right-sided varicocele were found to be associated with semen improvement after MSV, and a diagnostic model was developed using these two variables. The diagnostic model exhibited satisfactory performance, with an area under the curve (AUC) of 0.824 [95% confidence interval (CI): 0.735-0.913], which was further validated internally yielding an AUC of 0.824 (95% CI: 0.726-0.900). Additionally, calibration analysis confirmed that the diagnostic model was well calibrated, and the Hosmer-Lemeshow test resulted in a P value of 0.794. The decision curve demonstrated that using this proposed nomogram would yield a net benefit if the threshold probability for semen improvement after MSV exceeded 10%.</p><p><strong>Conclusions: </strong>TABFV-L demonstrated potential utility in clinical practice for assessing outcomes of MSV, and the diagnostic model incorporating TABFV-R and a combination of right-side varicocele performed well in predicting improvements in semen parameters following MSV.</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/PMC11485348/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480689","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 relationship between sarcopenia and metabolic parameters of ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) and the prognostic value of sarcopenia in early-stage non-small cell lung cancer.","authors":"Xin Xu, Jin Zhou, Xiaodong Yao, Shibiao Sang, Jihui Li, Bo Wang, Yi Yang, Bin Zhang, Shengming Deng","doi":"10.21037/qims-24-852","DOIUrl":"10.21037/qims-24-852","url":null,"abstract":"<p><strong>Background: </strong>Patients with lung cancer face a heightened risk of developing sarcopenia. Despite this known risk, the impact of sarcopenia on the long-term prognosis of lung cancer patients, specifically concerning progression-free survival (PFS) and overall survival (OS), remains unclear. The primary objective of our study was to examine the correlation between metabolic parameters derived from ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) and sarcopenia, as well as the prognostic value of sarcopenia in patients with surgically resected early-stage non-small cell lung cancer (NSCLC).</p><p><strong>Methods: </strong>In this retrospective cross-sectional study, we analyzed 187 NSCLC patients who underwent ¹⁸F-FDG PET/CT at the First Affiliated Hospital of Soochow University between March 2019 and October 2023. Patients were divided into two groups based on the presence (n=46) or absence (n=141) of sarcopenia. The correlation between sarcopenia, metabolic parameters, and patient characteristics was evaluated using chi-square and Mann-Whitney <i>U</i> tests. Survival analyses, including PFS and OS, were conducted using Kaplan-Meier analysis and Cox proportional hazards regression. Based on sarcopenia, metabolic parameters and patient characteristics, patients were classified into high-risk (n=28), intermediate-risk (n=121), and low-risk (n=38) groups.</p><p><strong>Results: </strong>Our analysis identified gender, body mass index (BMI), psoas Hounsfield unit (HU), and maximum standardized uptake value of the psoas major muscle (SUV_max-Muscle) as independent predictors of sarcopenia (P<0.05 for all). A nomogram model, utilizing these parameters, was constructed to predict sarcopenia. Survival analysis further demonstrated that total lesion glycolysis [hazard ratio (HR) =2.499; 95% confidence interval (CI): 2.014-3.267; P=0.016], sarcopenia (HR =3.323; 95% CI: 1.748-6.316; P<0.001), and programmed death ligand-1 (PD-L1) expression (HR =0.093; 95% CI: 0.012-0.698; P=0.021) emerged as independent predictors of OS in early-stage NSCLC. Notably, patients categorized as high-risk, characterized by elevated total lesion glycolysis, presence of sarcopenia, and PD-L1 positivity, exhibited a significantly poorer prognosis compared to the intermediate-risk (P<0.05) and low-risk groups (P<0.05).</p><p><strong>Conclusions: </strong>Our findings indicated an inverse relationship between SUV_max-Muscle or psoas HU with the incidence of sarcopenia in NSCLC patients. Additionally, total lesion glycolysis, sarcopenia, and PD-L1 expression were identified as independent prognostic factors for OS in early-stage NSCLC. The risk stratification model, incorporating total lesion glycolysis, sarcopenia, and PD-L1 expression, assumed a pivotal role in guiding personalized therapy decisions and post-treatment monitoring.</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/PMC11485386/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480708","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}