Quantitative Imaging in Medicine and Surgery最新文献

Background: Breast cancer screening and diagnosis remain to be improved. This study aimed to explore the diagnostic value of contrast-enhanced spectral mammography (CESM) for breast lesions through qualitative and quantitative analyses, and to evaluate the consistency of enhancement curves between CESM and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

Methods: This retrospective study included patients in whom CESM was performed because of suspected (clinical or ultrasound) breast lesions between January 2023 and February 2024 at the Shanxi Bethune Hospital. CESM images were analyzed to obtain mass shape, margin, enhancement, and enlarged lymph nodes. The lesion grey value (LGV) of the region of interest, contrast-to-noise ratio (CNR), and contrast ratio were calculated. The diagnostic value of the qualitative and quantitative metrics for benign and malignant breast lesions was evaluated using receiver operating characteristic (ROC) curves. DCE-MRI images were post-processed, and the enhancement curves were evaluated. A κ consistency analysis was performed to evaluate the enhancement curves between the CESM and DCE-MRI.

Results: This study included 202 female patients: 51 with benign lesions (46.55±11.84 years) and 151 with malignant lesions (51.32±11.21 years). Qualitative analysis showed differences between benign and malignant breast lesions in shape, margin, enhancement, and enlarged lymph nodes in CESM (all P<0.05). The LGV, CNR, and contrast ratio of malignant lesions were higher than in benign lesions (all P<0.001). Regarding the enhancement curves between CESM and DCE-MRI, the concordance rate was 85.42%. Specifically, the concordance rates for enhancement types I, II, and III were 76.19%, 81.67%, and 92.06%, respectively (κ=0.764). The areas under the curves for the qualitative, quantitative, and combined analyses of benign and malignant breast lesions were 0.857, 0.895, and 0.957, respectively.

Conclusions: There were significant differences in the qualitative and quantitative metrics of CESM between benign and malignant lesions, and the combined CESM qualitative and quantitative analysis achieved a high diagnostic value. Moreover, the enhancement curve of CESM demonstrated concordance with those of DCE-MRI. These suggest that CESM may have a promising application in the early diagnosis of breast cancer.

Background: Chronic obstructive pulmonary disease (COPD) is characterized by progressive airflow limitation and heterogeneous parenchymal destruction. Spirometry, the clinical standard, assesses global function but cannot evaluate regional lung mechanics. Four-dimensional dynamic-ventilation computer tomography (4D-CT)-based strain analysis can quantify local parenchymal deformation, yet its behavior across the full spectrum of COPD severity-particularly during the entire expiration phase in advanced disease-remains poorly characterized. This study aimed to quantitatively evaluate lung deformation patterns across COPD severities, and investigate the potential value in characterizing of strain-related parameters in cases of severe airflow limitation.

Methods: Sixty-one COPD patients who underwent spirometry and 4D-CT (three spatial dimensions plus time) were included in this study. Lung strain quantification utilized an adapted computational fluid dynamics (CFD) algorithm (MicroVec V3.6.2). Strain parameters derived from the expiration phase were adjusted for lung volume changes. Parameters from the whole expiration phase and the initial 2-s phase were compared among the Global Initiative for Chronic Obstructive Lung Disease (GOLD) I (mild), II (moderate), and III-IV (severe) airflow limitation groups using the Kruskal-Wallis nonparametric test. Correlations with the degree of airflow limitation were evaluated using Spearman analysis.

Results: Strain parameters showed significant progressive declines with worsening GOLD stage (all P<0.05). Parameters from the whole expiration phase correlated more strongly with disease severity than those from the initial 2-s phase. Specifically, the maximum principal strain in the whole expiratory phase (P_Smax-all) exhibited the strongest inverse correlation with GOLD classification (ρ=-0.732, P<0.001), and its median value decreased over 70% in severe (GOLD III-IV) patients compared to the mild (GOLD I) group.

Conclusions: Decreased lung deformation during expiration was associated with loss of lung function. Strain-related parameters, especially those derived from the whole expiration phase, showed promising values in reflecting the severity of airflow limitation in patients with COPD.

Background: The outcomes for perivascular hepatocellular carcinoma (HCC) and nonperivascular HCC after hepatectomy have not been well illustrated. This study aimed to compare long-term outcomes between perivascular and nonperivascular HCC.

Methods: A total of 714 HCC patients were retrospectively collected and categorized into perivascular and nonperivascular groups according to whether the tumors had contact with branches of the portal or hepatic vein. A 1:1 propensity score matching (PSM) with a caliper of 0.02 was used to eliminate bias. Disease-free survival (DFS) and overall survival (OS) were assessed using the Kaplan-Meier method, and long-term survival analyses were conducted.

Results: After PSM, 249 pairs of patients were enrolled in a nonadjacent portal vein (nPV) group and an adjacent portal vein (aPV) group. Additionally, 268 pairs of patients were enrolled in a nonadjacent hepatic vein (nHV) group and an adjacent hepatic vein (aHV) group. The aPV group had significantly worse DFS than the nPV group (5-year recurrence rates: 69.3% vs. 58.5%; P=0.008) and OS (5-year mortality: 48.6% vs. 39.0%; P=0.023). In contrast, no significant survival differences were observed between the aHV and nHV groups (DFS: P=0.980; OS: P=0.810). Multivariate analysis indicated that the tumor being adjacent to the portal vein was an independent risk factor for tumor recurrence [hazard ratio (HR) =1.374; 95% confidence interval (CI): 1.091-1.730] and overall mortality (HR =1.434; 95% CI: 1.086-1.893).

Conclusions: HCC adjacent to the portal vein negatively impacted the prognosis, whereas the hepatic vein did not appear to have such an influence.

Background: Accurate preoperative assessment of axillary lymph node (ALN) status is crucial for breast cancer staging and subsequent clinical decision-making. Consequently, identifying a reliable noninvasive method for evaluating ALN status before surgery remains a key clinical priority. This study aimed to evaluate the value of the new proposed qualitative shear wave elastography (SWE) patterns in the differentiation of suspicious ALNs observed on B-mode ultrasound (BMUS).

Methods: A retrospective multicenter study was performed on patients with breast cancer with suspicious axillary nodes on BMUS from May 2022 to June 2025. BMUS characteristics [cortical thickness, absence of fatty hilum, and longitudinal-to-transverse ratio (L/T) <2], vascularity distribution, quantitative SWE parameters [maximum value (Emax), mean value (Emean), minimal value (Emin), standard deviation (SD), and elasticity ratio (Eratio)], and the proposed qualitative SWE patterns of ALN status were evaluated. The diagnostic performance of BMUS characteristics, vascular distribution, quantitative SWE parameters, and the newly qualitative SWE patterns were compared with that of ALN pathological status, with either ALN dissection (ALND) or sentinel lymph node biopsy (SLNB) serving as the reference standard.

Results: A total of 144 ALNs in 144 patients with breast cancer were examined in this study. ALND was performed in 52 (36.1%) of patients, while 92 (63.9%) underwent SLNB. The optimal cutoff value of Emin, Emean, Emax, SD, and Eratio were 4.35 KPa, 17.30 KPa, 41.55 KPa, 1.95 KPa, and 2.25, respectively. Compared with the BMUS characteristics, vascularity distribution, and quantitative SWE parameters, the newly qualitative SWE patterns obtained the highest diagnostic performance, with an area under the curve of 0.972, a sensitivity of 96.72%, a specificity of 97.59%, and an accuracy of 97.22%.

Conclusions: The novel qualitative SWE patterns could achieve reliable diagnostic discrimination for benign and metastatic BMUS-suspicious ALNs. They may thus be able to optimize surgical planning and reduce overtreatment, improving the quality of life of patients treated with breast cancer.

Background: Accurate auto-segmentation of gross tumor volume in nasopharyngeal carcinoma (GTVnx) remains a significant challenge. This study introduces a novel two-stage deep learning cascade framework designed to address the precision limitations of single-stage models by strategically decoupling coarse localization from boundary refinement, thereby enhancing accuracy while maintaining computational efficiency.

Methods: This study developed an end-to-end model comprising a localization prompt generation unit (PGU) and a fine segmentation unit (FSU), integrated via an attention-guided mechanism. Using a dataset of 276 nasopharyngeal carcinoma (NPC) patients, we quantitatively evaluated three prompting strategies within the PGU: prompt-mask, prompt-box, and a dual-prompt combination. Performance was assessed against expert manual contours using the Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), and mean distance to agreement (MDA). Statistical significance was determined via paired t-tests.

Results: The proposed framework achieved state-of-the-art performance. The dual-prompt strategy yielded the most significant improvements over a baseline single-stage model: DSC increased by 9.7% (0.8219 vs. 0.7489, P<0.001), HD95 decreased by 28.2% (9.22 vs. 12.84 mm, P<0.001), and MDA improved by 31.4% (1.53 vs. 2.23 mm, P<0.001). Both single-prompt variants were statistically outperformed by the dual-prompt approach (P<0.01 for all metrics). Qualitative analysis confirmed superior anatomical fidelity for the dual-prompt model.

Conclusions: This work presents a computationally efficient, two-stage deep learning-based auto-segmentation (DLAS) framework that significantly improves the accuracy and reliability of GTVnx segmentation. It improves the accuracy and reliability of GTVnx segmentation, features a lightweight architecture and high scalability, and highlights a promising pathway for clinical integration.

Background: Appropriate staging of esophageal cancer is crucial for optimizing treatment planning and enhancing patient outcomes. ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) has emerged as a key imaging technique for assessing lymph node and distant metastases in esophageal cancer. In this systematic review, we aimed to assess the diagnostic performance of ¹⁸F-FDG PET/CT in staging esophageal cancer, including its sensitivity, specificity, and clinical utility in tumor detection, lymph node status, treatment response, and prognostication.

Methods: A systematic literature search was conducted between 2017 and 2024 using MEDLINE, Embase, LILACS, and ClinicalTrials.gov databases. Studies assessing the diagnostic accuracy of ¹⁸F-FDG PET/CT for esophageal cancer staging were included. The Quality Assessment of Diagnostic Accuracy Studies version 2 (QUADAS-2) tool was used to assess risk of bias. Data extraction focused on the sensitivity, specificity, predictive value, and relative accuracy compared with other imaging methods.

Results: A total of 22 studies were included in this review out of 182 initially selected studies. The sensitivity of ¹⁸F-FDG PET/CT for tumor staging ranges from 70% to 94%, and the specificity ranges from 60% to 78%. PET/CT sensitivity for lymph node metastases ranged from 60% to 85%, and the specificity ranged from 70% to 95%. PET/CT was also effective in detecting distant metastases (sensitivity: 85-95%) and in identifying responses to treatment by measuring the reduction in maximum standardized uptake value (SUVmax). However, false-positive findings have been observed due to inflammatory changes and limitations in detecting tiny metastases.

Conclusions: ¹⁸F-FDG PET/CT is an important adjunct for esophageal cancer staging with excellent sensitivity for tumor and nodal staging. However, it has certain limitations in detecting tiny lesions and post-treatment inflammatory changes. Future research should aim to standardize imaging protocols, combine PET/CT with techniques like endoscopic ultrasound (EUS) and magnetic resonance imaging (MRI), and optimize SUVmax cutoff points to improve diagnostic accuracy.