Quantitative Imaging in Medicine and Surgery最新文献

Background: 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.

Methods: 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.

Results: 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%.

Conclusions: 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.

Background: 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).

Methods: 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 U 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.

Results: 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).

Conclusions: 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.

When treating femoral fractures with closed reduction intramedullary nail fixation, excessive residual displacement of the fracture end can affect the fixation effect and prolong the healing time, which is difficult to manage intraoperatively. This article introduces a simple steel wire cerclage fixation technique, which is percutaneous and can control the incision within 1 cm without excessive reliance on specially designed surgical instruments. It is suitable for the reduction and fixation of oblique femoral metaphysis fractures and butterfly-shaped femoral shaft fracture blocks.

Background: The effectiveness of coronary computed tomography (CT) angiography in assessing stent restenosis is hindered by heavy metal artifacts. This study aimed to evaluate the image quality of monoenergetic reconstructions and iodine density map for coronary stent imaging using an 8-cm dual-layer detector spectral CT.

Methods: In this study, 8 stents with a diameter <3 mm (group A) and 10 with a diameter ≥3 mm (group B) were placed in plastic tubes filled with iodinated contrast media and scanned. The internal diameter of the prepared stents was then measured by intravascular ultrasound. The reconstructed images included iodine density maps, conventional images, and different energy levels. The visualization of the stent lumen and stent structure was subjectively assessed using a 4-point Likert scale. The objective evaluation was performed using the in-stent lumen signal-to-noise ratio (SNRis), non-stent lumen SNR (SNRns), internal diameter difference (IDD), and blooming artifact index (BAI). The Friedman test and analysis of variance were used for multiple comparisons.

Results: For lumen visualization, the optimal monoenergetic images received the highest score for both group A (2.56±0.51) and group B (3.1±0.55). Multiple comparisons showed that there were significant differences between the optimal monoenergetic images and iodine density maps. However, for stent structure, iodine density maps received the highest score for group A (3.0±0.52) and group B (3.8±0.41). For quantitative assessment, the optimal monoenergetic images had the highest SNRis and SNRns, while the iodine density maps had the lowest SNRis and SNRns. For IDD and BAI, the iodine density maps yielded the smallest value.

Conclusions: The monoenergetic images on the second-generation dual-layer detector CT provide better visualization of the lumen and higher SNR. However, iodine density maps are superior for evaluating stent structure and IDD and BAI compared to monoenergetic and conventional reconstructions.

Background: Photorefractive intrastromal corneal cross-linking (PiXL) treatment corrects myopia by enhancing localized central corneal biomechanics. However, the dose-effect relationship between the changes in corneal biomechanics and alterations in corneal curvature resulting from this treatment remain unclear. We therefore developed an acoustic radiation force optical coherence elastography (ARF-OCE) technique to investigate the dose-effect relationship in PiXL.

Methods: ARF-OCE measurements and corneal topography were performed 3 days before and 1 week after PiXL treatment. Depth-resolved Young's modulus images of the in vivo corneas were obtained based on the phase velocity of the Lamb wave. PiXL treatments with five ultraviolet-A (UVA) energy doses (5.4, 15, 25, 35, and 45 J/cm²) were administered to rabbit corneas in vivo (n=15).

Results: The percentage change in Young's modulus (ΔE%) of the cornea increased from 0.26 to 1.71 as the UVA energy dose increased from group I (5.4 J/cm²) to group V (45 J/cm²). Meanwhile, the change in the mean keratometry (ΔK_m ) of the cornea increased from 0.40 to 2.10 diopters (D) as the UVA energy dose increased from group I to group IV (35 J/cm²). Furthermore, a statistically significant positive correlation was observed between ΔE% and ΔK_m in groups I to IV.

Conclusions: With increasing UVA energy dose, the corneal Young's modulus significantly increased. Given the observed correlation, ΔE% holds promise as a new quantitative biomechanical parameter for determining the dose-effect relationship in PiXL treatment. It should be emphasized that there may be an inflection point of ΔE%, at which corneal keratometry ceases to flatten and begins to increase. The ARF-OCE system has demonstrated its efficacy in quantitatively assessing changes in corneal biomechanics in vivo following PiXL treatment. This technique has great potential in facilitating the quantitative determination of the dose-effect relationship in PiXL treatment.

Background: The precise identification of the position and form of a tumor mass can improve early diagnosis and treatment. However, due to the complicated tumor categories and varying sizes and forms, the segregation of brain gliomas and their internal sub-regions is still very challenging. This study sought to design a new deep-learning network based on three-dimensional (3D) U-Net to address its shortcomings in brain tumor segmentation (BraTS) tasks.

Methods: We developed a 3D dilated multi-scale residual attention U-Net (DMRA-U-Net) model for magnetic resonance imaging (MRI) BraTS. It used dilated convolution residual (DCR) modules to better process shallow features, multi-scale convolution residual (MCR) modules in the bottom encoding path to create richer and more comprehensive feature expression while reducing overall information loss or blurring, and a channel attention (CA) module between the encoding and decoding paths to address the problem of retrieving and preserving important features during the processing of deep feature maps.

Results: The BraTS 2018-2021 datasets served as the training and evaluation datasets for this study. Further, the proposed architecture was assessed using metrics such as the dice similarity coefficient (DSC), Hausdorff distance (HD), and sensitivity (Sens). The DMRA U-Net model segments the whole tumor (WT), and the tumor core (TC), and the enhancing tumor (ET) regions of brain tumors. Using the suggested architecture, the DSCs were 0.9012, 0.8867, and 0.8813, the HDs were 28.86, 13.34, and 10.88 mm, and the Sens was 0.9429, 0.9452, and 0.9303 for the WT, TC, and ET regions, respectively. Compared to the traditional 3D U-Net, the DSC of the DMRA U-Net increased by 4.5%, 2.5%, and 0.8%, the HD of the DMRA U-Net decreased by 21.83, 16.42, and 10.00, the Sens of the DMRA U-Net increased by 0.4%, 0.7%, and 1.4% for the WT, TC, and ET regions, respectively. Further, the results of the statistical comparison of the performance indicators revealed that our model performed well generally in the segmentation of the WT, TC, and ET regions.

Conclusions: We developed a promising tumor segmentation model. Our solution is open sourced and is available at: https://github.com/Gold3nk/dmra-unet.