Quantitative Imaging in Medicine and Surgery最新文献

{"title":"Effects of plantar static pressure distribution in subject with bilateral hallux limitus: a detailed case-control study.","authors":"Natalia Tovaruela-Carrión, Ricardo Becerro-de-Bengoa-Vallejo, Marta Elena Losa-Iglesias, Daniel López-López, Juan Gómez-Salgado, Javier Bayod López","doi":"10.21037/qims-2025-907","DOIUrl":"10.21037/qims-2025-907","url":null,"abstract":"<p><strong>Background: </strong>Hallux limitus (HL) is defined as the restriction of dorsiflexion (DF) in the first metatarsophalangeal joint (IMTFJ) under closed kinetic chain conditions, where the distal segment is fixed and the foot is in contact with the ground. This biomechanical condition compromises the Windlass mechanism during the propulsive phase of gait, generating pain and functional disability. Therefore, the aim of this research was to examine the aspect of foot shape linked to distribution of static plantar pressure in individuals with bilateral HL compared to subjects with normal foot.</p><p><strong>Methods: </strong>A total of 90 subjects participated in this case-control study, divided into two groups: 45 individuals with bilateral HL and 45 healthy individuals without any known foot pathology. A portable pressure platform was used to measure each subject's static plantar pressure.</p><p><strong>Results: </strong>Individuals with HL showed significantly increased contact surface in the forefoot (left: 36.67±8.30 <i>vs.</i> 28.91±7.94 cm²) and heel (left: 30.85±7.70 <i>vs.</i> 24.55±7.17 cm²; right: 31.01±7.98 <i>vs.</i> 25.71±7.64 cm²), and higher medium peak pressure in the left foot (HL: 27.90±5.41 kPa <i>vs.</i> control: 22.58±6.57 kPa) (P<0.001).</p><p><strong>Conclusions: </strong>Individuals with bilateral HL showed altered static plantar pressure distribution and increased contact surface in the forefoot and heel compared to healthy controls. Limitations include sex imbalance between groups and lack of dynamic data. These findings may reflect compensatory adaptations and support the need for tailored interventions to improve foot function in this population.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"8153-8162"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397620/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978551","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":"Comprehensive assessment of patients with Kawasaki disease without coronary artery aneurysm.","authors":"Lei Hu, Chuan Wang, Zhongqin Zhou, Shiganmo Azhe, Shengkun Peng, Nanjun Zhang, Kaiyu Zhou, Yingkun Guo, Li Yu, Lingyi Wen","doi":"10.21037/qims-2024-2772","DOIUrl":"10.21037/qims-2024-2772","url":null,"abstract":"<p><strong>Background: </strong>In the current guidelines, the management algorithm for patients with Kawasaki disease (KD) without coronary artery (CA) aneurysms primarily depends on the clinical experience of pediatricians. It is necessary to conduct a comprehensive evaluation of these patients to provide a higher level of evidence for their management. Therefore, our study aimed to assess patients with KD using multidimensional data and investigate their prognosis.</p><p><strong>Methods: </strong>A total of 455 patients with KD were retrospectively recruited and divided into a non-CA involvement group (n=313) and a CA dilation-only group (n=142), with 16.1% (50/311) and 15.5% (22/142), respectively, undergoing cardiac magnetic resonance (CMR) examinations during recovery. Data regarding inflammatory markers, electrocardiography, and echocardiography were compared between the two groups both in the acute phase and during the recovery period. Kaplan-Meier analysis was performed to estimate the cumulative probability of the endpoints including coronary events, cardiac death, heart failure, and new-onset malignant arrhythmias.</p><p><strong>Results: </strong>Baseline inflammatory markers, including white blood cell count (WBC) and C-reactive protein (CRP), were not significantly different between patients with KD and non-CA involvement and those with dilation only (median WBC: 14.1×10⁹/L <i>vs.</i> 13.9×10⁹/L, P=0.57; median CRP: 87.4 <i>vs.</i> 85.6 mg/L, P=0.73). In terms of echocardiography assessment at baseline, there were no significant differences between the non-CA involvement group and the dilation-only group in terms of left ventricular ejection fraction (67.8%±13.6% <i>vs.</i> 68.1%±10.3%; P=0.13) or fractional shortening (37.6%±5.3% <i>vs.</i> 35.4%±6.6%; P=0.25). For CMR assessment at recovery, the myocardial systolic function of patients with KD but non-CA involvement was not significantly different from that of patients with CA dilation only in terms of global radial strain (38.3%±18.7% <i>vs.</i> 39.9%±20.5%; P=0.20), global circumferential strain (-18.7%±6.8% <i>vs.</i> -18.3%±7.2%; P=0.38), and global longitudinal strain (-13.2%±3.7% <i>vs.</i> -13.4%±4.1%; P=0.17). The global native T1 value of patients with non-CA involvement was 1,296.5±74.1 msec, while that of patients with CA dilation only was 1,313.3±80.5 msec (P=0.21); there was also no significant difference in global T2 values between the two groups of patients (38.2±4.1 <i>vs.</i> 38.1±3.5 msec; P=0.53). Finally, at a median follow-up of 4.2 years, there was a favorable prognosis in both two groups of patients, with no patients reaching the endpoints.</p><p><strong>Conclusions: </strong>Comprehensive assessment revealed no significant differences between patients with KD and CA dilation only and those with non-CA involvement, and thus these patients should be treated according to the same medium-long-term management algorithm.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"8348-8358"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397668/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978703","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":"Added prognostic value of histogram features from preoperative multi-modal diffusion MRI in predicting Ki-67 proliferation for adult-type diffuse gliomas.","authors":"Yingqian Huang, Siyuan He, Hangtong Hu, Hui Ma, Zihuan Huang, Shanmei Zeng, Liwei Mazu, Wenwen Zhou, Chen Zhao, Nengjin Zhu, Jiajing Wu, Qiuchan Liu, Zhiyun Yang, Wei Wang, Guoping Shen, Nu Zhang, Jianping Chu","doi":"10.21037/qims-2025-242","DOIUrl":"10.21037/qims-2025-242","url":null,"abstract":"<p><strong>Background: </strong>Ki-67 labelling index (LI), a critical marker of tumor proliferation, is vital for grading adult-type diffuse gliomas and predicting patient survival. However, its accurate assessment currently relies on invasive biopsy or surgical resection. This makes it challenging to non-invasively predict Ki-67 LI and subsequent prognosis. Therefore, this study aimed to investigate whether histogram analysis of multi-parametric diffusion model metrics-specifically diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), and neurite orientation dispersion and density imaging (NODDI)-could help predict Ki-67 LI in adult-type diffuse gliomas and further predict patient survival.</p><p><strong>Methods: </strong>A total of 123 patients with diffuse gliomas who underwent preoperative bipolar spin-echo diffusion magnetic resonance imaging (MRI) were included. Diffusion metrics (DTI, DKI and NODDI) and their histogram features were extracted and used to develop a nomogram model in the training set (n=86), and the performance was verified in the test set (n=37). Area under the receiver operating characteristics curve of the nomogram model was calculated. The outcome cohort, including 123 patients, was used to evaluate the predictive value of the diffusion nomogram model for overall survival (OS). Cox proportion regression was performed to predict OS.</p><p><strong>Results: </strong>Among 123 patients, 87 exhibited high Ki-67 LI (Ki-67 LI >5%). The patients had a mean age of 46.08±13.24 years, with 39 being female. Tumor grading showed 46 cases of grade 2, 21 cases of grade 3, and 56 cases of grade 4. The nomogram model included eight histogram features from diffusion MRI and showed good performance for prediction Ki-67 LI, with area under the receiver operating characteristic curves (AUCs) of 0.92 [95% confidence interval (CI): 0.85-0.98, sensitivity =0.85, specificity =0.84] and 0.84 (95% CI: 0.64-0.98, sensitivity =0.77, specificity =0.73) in the training set and test set, respectively. Further nomogram incorporating these variables showed good discrimination in Ki-67 LI predicting and glioma grading. A low nomogram model score relative to the median value in the outcomes cohort was independently associated with OS (P<0.01).</p><p><strong>Conclusions: </strong>Accurate prediction of the Ki-67 LI in adult-type diffuse glioma patients was achieved by using multi-modal diffusion MRI histogram radiomics model, which also reliably and accurately determined survival.</p><p><strong>Trial registration: </strong>ClinicalTrials.gov Identifier: NCT06572592.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"8423-8439"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397644/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978433","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":"Enhancing diagnostic precision for thyroid C-TIRADS category 4 nodules: a hybrid deep learning and machine learning model integrating grayscale and elastographic ultrasound features.","authors":"Daoyuan Zou, Fei Lyu, Yiqi Pan, Xinyu Fan, Jing Du, Xiaoli Mai","doi":"10.21037/qims-2025-594","DOIUrl":"10.21037/qims-2025-594","url":null,"abstract":"<p><strong>Background: </strong>Accurate and timely diagnosis of thyroid cancer is critical for clinical care, and artificial intelligence can enhance this process. This study aims to develop and validate an intelligent assessment model called C-TNet, based on the Chinese Guidelines for Ultrasound Malignancy Risk Stratification of Thyroid Nodules (C-TIRADS) and real-time elasticity imaging. The goal is to differentiate between benign and malignant characteristics of thyroid nodules classified as C-TIRADS category 4. We evaluated the performance of C-TNet against ultrasonographers and BMNet, a model trained exclusively on histopathological findings indicating benign or malignant nature.</p><p><strong>Methods: </strong>The study included 3,545 patients with pathologically confirmed C-TIRADS category 4 thyroid nodules from two tertiary hospitals in China: Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine (n=3,463 patients) and Jiangyin People's Hospital (n=82 patients). The cohort from Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine was randomly divided into a training set and validation set (7:3 ratio), while the cohort from Jiangyin People's Hospital served as the external validation set. The C-TNet model was developed by extracting image features from the training set and integrating them with six commonly used classifier algorithms: logistic regression (LR), linear discriminant analysis (LDA), random forest (RF), kernel support vector machine (K-SVM), adaptive boosting (AdaBoost), and Naive Bayes (NB). Its performance was evaluated using both internal and external validation sets, with statistical differences analyzed through the Chi-squared test.</p><p><strong>Results: </strong>C-TNet model effectively integrates feature extraction from deep neural networks with a RF classifier, utilizing grayscale and elastography ultrasound data. It successfully differentiates benign from malignant thyroid nodules, achieving an area under the curve (AUC) of 0.873, comparable to the performance of senior physicians (AUC: 0.868).</p><p><strong>Conclusions: </strong>The model demonstrates generalizability across diverse clinical settings, positioning itself as a transformative decision-support tool for enhancing the risk stratification of thyroid nodules.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"7951-7963"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397621/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978561","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":"Iodine-131 (¹³¹I) uptake in bilateral ovarian teratomas of a papillary thyroid carcinoma patient.","authors":"Xiaojing Ren, Ding Nan, Zairong Gao, Xiao Zhang","doi":"10.21037/qims-2025-797","DOIUrl":"10.21037/qims-2025-797","url":null,"abstract":"","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"8668-8673"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397757/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978675","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":"Impact of a deep learning image reconstruction algorithm on the robustness of abdominal computed tomography radiomics features using standard and low radiation doses.","authors":"Shuo Yang, Yifan Bie, Lei Zhao, Kun Luan, Xingchao Li, Yanheng Chi, Zhen Bian, Deqing Zhang, Guodong Pang, Hai Zhong","doi":"10.21037/qims-2025-238","DOIUrl":"10.21037/qims-2025-238","url":null,"abstract":"<p><strong>Background: </strong>Deep learning image reconstruction (DLIR) can enhance image quality and lower image dose, yet its impact on radiomics features (RFs) remains unclear. This study aimed to compare the effects of DLIR and conventional adaptive statistical iterative reconstruction-Veo (ASIR-V) algorithms on the robustness of RFs using standard and low-dose abdominal clinical computed tomography (CT) scans.</p><p><strong>Methods: </strong>A total of 54 patients with hepatic masses who underwent abdominal contrast-enhanced CT scans were retrospectively analyzed. The raw data of standard dose in the venous phase and low dose in the delayed phase were reconstructed using five reconstruction settings, including ASIR-V at 30% (ASIR-V30%) and 70% (ASIR-V70%) levels, and DLIR at low (DLIR-L), medium (DLIR-M), and high (DLIR-H) levels. The PyRadiomics platform was used for the extraction of RFs in 18 regions of interest (ROIs) in different organs or tissues. The consistency of RFs among different algorithms and different strength levels was tested by coefficient of variation (CV) and quartile coefficient of dispersion (QCD). The consistency of RFs among different strength levels of the same algorithm and clinically comparable levels across algorithms was evaluated by intraclass correlation coefficient (ICC). Robust features were identified by Kruskal-Wallis and Mann-Whitney <i>U</i> test.</p><p><strong>Results: </strong>Among the five reconstruction methods, the mean CV and QCD in the standard-dose group were 0.364 and 0.213, respectively, and the corresponding values were 0.444 and 0.245 in the low-dose group. The mean ICC values between ASIR-V 30% and 70%, DLIR-L and M, DLIR-M and H, DLIR-L and H, ASIR-V30% and DLIR-M, and ASIR-V70% and DLIR-H were 0.672, 0.734, 0.756, 0.629, 0.724, and 0.651, respectively, in the standard-dose group, and the corresponding values were 0.500, 0.567, 0.700, 0.474, 0.499, and 0.650 in the low-dose group. The ICC values between DLIR-M and H under low-dose conditions were even higher than those of ASIR-V30% and -V70% under standard dose conditions. Among the five reconstruction settings, averages of 14.0% (117/837) and 10.3% (86/837) of RFs across 18 ROIs exhibited robustness under standard-dose and low-dose conditions, respectively. Some 23.1% (193/837) of RFs demonstrated robustness between the low-dose DLIR-M and H groups, which was higher than the 21.0% (176/837) observed in the standard-dose ASIR-V30% and -V70% groups.</p><p><strong>Conclusions: </strong>Most of the RFs lacked reproducibility across algorithms and energy levels. However, DLIR at medium (M) and high (H) levels significantly improved RFs consistency and robustness, even at reduced doses.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"7922-7934"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397659/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978690","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 high-density lipoprotein cholesterol, myocardial perfusion index, and global longitudinal strain derived from cardiac magnetic resonance imaging in predicting coronary slow flow in patients with nonobstructive coronary artery disease.","authors":"Yunbo Zhang, Lin Sun, Xin-Xiang Zhao","doi":"10.21037/qims-24-1668","DOIUrl":"10.21037/qims-24-1668","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Coronary slow flow (CSF) is associated with dyslipidemias, smoking, and increased body mass index (BMI), yet its diagnosis through noninvasive methods remains challenging. Cardiac magnetic resonance (CMR) is a multimodal imaging technique that enables the simultaneous assessment of impaired myocardial perfusion and deteriorated ventricular function in patients with cardiac disease. This study aimed to demonstrate altered perfusion and deformation parameters on CMR and to evaluate the value of CMR parameters for predicting CSF.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Participants without obstructive epicardial arterial disease who underwent CMR imaging and coronary angiography (CAG) for typical angina symptoms were enrolled in this retrospective study. CSF was defined by the presence of at least one CAG showing corrected thrombolysis in myocardial infarction frame count (CTFC) &gt;27 frames. The myocardial perfusion index (PI) was analyzed via semiquantitative resting first-pass perfusion. Left ventricular (LV) performance was assessed via CMR feature tracking (CMR-FT) cine imaging, including global longitudinal strain (GLS), global circumferential strain (GCS), and global radial strain (GRS). Baseline clinical factors were collected, including sex, age, and traditional cardiovascular risk factors, along with levels of low-density lipoprotein cholesterol, high-density lipoprotein cholesterol (HDL-C), triglyceride (TG), and serum creatinine. Multivariate logistic regression analysis was performed to identify independent predictors of CSF, and a combined prediction model for CSF was developed. The predictive accuracy of the parameters was evaluated via receiver operating characteristic (ROC) curves.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 146 participants who underwent CAG and CMR were included and divided into CSF (n=73; 78.1% male; age 49.44±9.59 years) and control (n=73; 57.5% male; age 47.32±13.57 years) groups based on CTFC. Patients with CSF were more likely to have a higher BMI, hyperuricemia, peripheral arterial disease, and a smoking habit, as well as lower HDL-C levels and elevated TGs as compared to controls. Compared with controls, patients with CSF had impaired GLS (-12.09%±2.69% &lt;i&gt;vs&lt;/i&gt;. -14.38%±2.36%) and GCS (-18.70%±3.24% &lt;i&gt;vs&lt;/i&gt;. -19.80%±2.21%) (all P values &lt;0.05). Global LV PI was significantly decreased in patients with CSF as compared with controls (11.34%±4.24% &lt;i&gt;vs&lt;/i&gt;. 15.25%±8.50%; P&lt;0.001). After adjustments were made for clinical factors and imaging indices, multivariate analysis indicated that the independent predictors of CSF were HDL-C [odds ratio (OR) 0.119; 95% confidence interval (CI): 0.016-0.897; P=0.039], GLS (OR 1.339; 95% CI: 1.112-1.613; P=0.002), and global LV PI (OR 0.456; 95% CI: 0.209-0.994; P=0.048). Moreover, in predicting CSF, the combination of PI, GLS, and HDL-C yielded the best area under the curve (with an 84.9% sensitivity and a 60.3% specificity) as compared to PI (0.7","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"8491-8504"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397633/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978693","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":"Imaging indicators and fusion analysis of percutaneous endoscopic posterior lumbar interbody fusion and modified posterior lumbar interbody fusion for the treatment of lumbar degenerative diseases.","authors":"Jin Tang, Jianing Wang, Tao Li, Siyu Wang, Zhengping Liu, Xue Du, Xiaokun Wang, Wei Xie, Jinfeng Hu, Xugui Li","doi":"10.21037/qims-24-2268","DOIUrl":"10.21037/qims-24-2268","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Although numerous studies have confirmed percutaneous endoscopic posterior lumbar interbody fusion (PE-PLIF) as a safe and effective minimally invasive technique for lumbar degenerative diseases (LDDs), existing research primarily focuses on clinical outcomes and involves limited imaging analysis. This study aimed to quantitatively compare PE-PLIF and modified posterior lumbar interbody fusion (MPLIF) through comprehensive radiographic evaluation and clinical outcomes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We conducted a retrospective analysis of 75 consecutive LDD patients who underwent surgical treatment at our institution between January 2018 and October 2023. The patients were divided into an observation group (PE-PLIF; 36 cases) and a control group (MPLIF; 39 cases) according to their surgical approach. The intervertebral space height (mm), segmental Cobb angle (°), bone graft area (mm&lt;sup&gt;2&lt;/sup&gt;), and bone graft range were recorded and compared for each patient during the preoperative period, the first postoperative review, and the final follow-up. Additionally, the fusion rates, operative time, intraoperative blood loss (IBL), time to ambulation post-surgery, length of postoperative hospital stay, and complications were compared between the two groups at 3 and 6 months postoperatively.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Complete follow-up data showed significant postoperative improvement in both groups (all P&lt;0.001). The PE-PLIF group showed better results, with the intervertebral height increasing from 11.59±2.04 to 14.67±1.62 mm (an improvement of 26.6%), whereas the MPLIF group increased from 10.67±1.25 to 12.64±2.58 mm (an improvement of 18.5%). At the final follow-up, a high recovery rate of 16.1% was maintained (13.53±1.26 &lt;i&gt;vs&lt;/i&gt;. 10.74±4.53 mm, P&lt;0.001). Cobb angle correction also demonstrated similar advantages. The PE-PLIF improved from 17.01°±10.84° to 20.65°±6.42° (21.4% correction), whereas the MPLIF improved from 16.05°±7.43° to 18.54°±5.13° (15.5% correction). The final alignment of PE-PLIF remained better (18.73°±8.95° to 17.52°±7.33°, P&lt;0.001). The surgical results showed that the required bone graft volume for PE-PLIF decreased by 12.4% (478.70±97.50 and 546.67±101.39 mm&lt;sup&gt;2&lt;/sup&gt;, P=0.004), and the average operation time was significantly longer than that of the MPLIF group (P&lt;0.001). However, the IBL was significantly less than that in the MPLIF group (P&lt;0.001). The postoperative bed rest time in the PE-PLIF group was significantly shorter than that in the MPLIF group (P&lt;0.001). The postoperative hospital stay in the PE-PLIF group was significantly shorter than that in the MPLIF group (P&lt;0.001). Both procedures were completed successfully with no major complications.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;PE-PLIF demonstrates superior efficacy over MPLIF in restoring intervertebral height and stability, with advantages including reduced blood loss, better endplate preservation, reliable fusion r","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"8079-8095"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397665/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978708","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":"Deep learning-based super-resolution method for projection image compression in radiotherapy.","authors":"Zhixing Chang, Jiawen Shang, Yuhan Fan, Peng Huang, Zhihui Hu, Ke Zhang, Jianrong Dai, Hui Yan","doi":"10.21037/qims-2024-2962","DOIUrl":"10.21037/qims-2024-2962","url":null,"abstract":"<p><strong>Background: </strong>Cone-beam computed tomography (CBCT) is a three-dimensional (3D) imaging method designed for routine target verification of cancer patients during radiotherapy. The images are reconstructed from a sequence of projection images obtained by the on-board imager attached to a radiotherapy machine. CBCT images are usually stored in a health information system, but the projection images are mostly abandoned due to their massive volume. To store them economically, in this study, a deep learning (DL)-based super-resolution (SR) method for compressing the projection images was investigated.</p><p><strong>Methods: </strong>In image compression, low-resolution (LR) images were down-sampled by a factor from the high-resolution (HR) projection images and then encoded to the video file. In image restoration, LR images were decoded from the video file and then up-sampled to HR projection images via the DL network. Three SR DL networks, convolutional neural network (CNN), residual network (ResNet), and generative adversarial network (GAN), were tested along with three video coding-decoding (CODEC) algorithms: Advanced Video Coding (AVC), High Efficiency Video Coding (HEVC), and AOMedia Video 1 (AV1). Based on the two databases of the natural and projection images, the performance of the SR networks and video codecs was evaluated with the compression ratio (CR), peak signal-to-noise ratio (PSNR), video quality metric (VQM), and structural similarity index measure (SSIM).</p><p><strong>Results: </strong>The codec AV1 achieved the highest CR among the three codecs. The CRs of AV1 were 13.91, 42.08, 144.32, and 289.80 for the down-sampling factor (DSF) 0 (non-SR) 2, 4, and 6, respectively. The SR network, ResNet, achieved the best restoration accuracy among the three SR networks. Its PSNRs were 69.08, 41.60, 37.08, and 32.44 dB for the four DSFs, respectively; its VQMs were 0.06%, 3.65%, 6.95%, and 13.03% for the four DSFs, respectively; and its SSIMs were 0.9984, 0.9878, 0.9798, and 0.9518 for the four DSFs, respectively. As the DSF increased, the CR increased proportionally with the modest degradation of the restored images.</p><p><strong>Conclusions: </strong>The application of the SR model can further improve the CR based on the current result achieved by the video encoders. This compression method is not only effective for the two-dimensional (2D) projection images, but also applicable to the 3D images used in radiotherapy.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"8611-8626"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397698/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978720","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":"Prediction of weaning outcomes from mechanical ventilation in critically ill patients based on the combination of ultrasound parameters of the heart, lung, and diaphragm: a prospective observational cohort study.","authors":"Qian Zhou, Ying Xu, Jun Chen, Qin Gu, Wentao Kong","doi":"10.21037/qims-2025-167","DOIUrl":"10.21037/qims-2025-167","url":null,"abstract":"<p><strong>Background: </strong>Postextubation distress in critically ill patients with successful spontaneous breathing trials (SBTs) is unfavorable for prognosis. This study aimed to determine whether the combined application of multimodal ultrasound parameters of the heart, lung, and diaphragm can predict the mechanical ventilation weaning outcome among critically ill patients.</p><p><strong>Methods: </strong>From December 2022 to December 2023, a total of 74 patients (aged over 18 years old) mechanically ventilated for more than 48 hours and prepared for an SBT were selected from the Department of Critical Care Unit, Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School. Patients who met the criteria for weaning were prepared to undergo a 30-minute SBT, during which the heart, lungs, and diaphragm of the patients were examined via ultrasound. According to the weaning outcomes, patients were divided into a success group and a failure group. Ultrasound parameters with statistical significance in univariate analysis were incorporated into a binary logistic regression model to identify the independent influencing factors of weaning outcomes. The receiver operating characteristic (ROC) curve was plotted, and the area under the curve (AUC) was calculated for statistical analysis.</p><p><strong>Results: </strong>Out of the 74 included patients, 23 failed weaning. There were significant differences in diaphragm excursion (DE), diaphragm thickening fraction (DTF), bilateral lung ultrasound score (LUS), total LUS, and left ventricular ejection fraction (LVEF) between the success and failure groups (P<0.05). The predictive performance of individual ultrasound parameters was as follows: LVEF achieved an AUC of 0.742 [95% confidence interval (CI): 0.642-0.842; P<0.001], with optimal thresholds of 58.05% (sensitivity: 76.5%; specificity: 69.6%); LUS achieved an AUC of 0.837 (95% CI: 0.738-0.936; P<0.001), with an 80.4% sensitivity and 82.6% specificity at a cutoff value of 17.50. DE yielded an AUC of 0.895 (95% CI: 0.821-0.969; P<0.001), with an 82.4% sensitivity and a 95.7% specificity at a cutoff value of 1.205 cm; DTF reached an AUC of 0.896 (95% CI: 0.827-0.965; P<0.001), with a 68.6% sensitivity and a 100% specificity at a cutoff value of 22.75%. A composite model integrating LVEF, LUS, DE, and DTF achieved an AUC of 0.951 (95% CI: 0.907-0.996; P<0.001), with an 88.2% sensitivity and a 95.7% specificity.</p><p><strong>Conclusions: </strong>Ultrasound parameters of the heart, lungs, and diaphragm provide critical information on cardiopulmonary and diaphragmatic function during SBT. Weaning failure is more common when LUS is increased and LVEF, DE, and DTF are decreased. The combination of these three aspects can improve the accuracy of predicting weaning outcomes.</p>","PeriodicalId":54267,"journal":{"name":"Quantitative Imaging in Medicine and Surgery","volume":"15 9","pages":"7697-7710"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12397658/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978402","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}