pancreatic cancer is a common malignant tumor of digestive system, with poor prognosis. About 80% of patients have lost the opportunity of surgical resection when diagnosed. In different treatment schemes, radioactive seed 125I implantation can improve the quality of life of patients with unresectable pancreatic cancer and is expected to improve their survival rate. This article reviews the clinical applications of 125I particle implantation therapy combined with chemotherapy, cryotherapy, intracavitary irradiation, stent placement, radiofrequency ablation, nanoknife, and bypass surgery, in order to better promote its clinical application. However, it is necessary to establish unified dosage standards and regulatory guidelines to make them safer and more widely serve clinical practice.

Objective:To investigate the value of the virtual monoenergetic image (VMI) obtained by a new dual-layer detector spectral CT combined with metal artifact reduction algorithms(O-MAR) in reduction of different types of artifacts caused by 125I seeds implantation and in improvement of the post-operative CT image quality. Methods:This was a cross-sectional study. Thirty-five patients who underwent dual-layer detector spectral CT scanning of the chest and abdomen after 125I seeds implantation were retrospectively included at the First Affiliated Hospital of Zhengzhou University from March to September 2022. The spectral data were collected and reconstructed into conventional CT image (CI), VMI image (50-150 keV, 20 keV/level), CI+O-MAR image, and VMI+O-MAR image (50-150 keV, 20 keV/level). The artifacts′ removal effects and image quality improvement in each group were evaluated. Two slices with the strongest artifacts were selected for analysis for each patient, resulting in a total of 70 slices. Objective indicators including artifact index (AI), signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of soft tissue regions affected by artifacts were measured and calculated. Subjective indicators including the overcorrected artifacts and new artifacts, the different forms of artifacts, the diagnosis of artifacts, and the image quality were assessed. One-way analysis of variance was used for comparisons among multiple groups. Paired t test was used to compare the quantitative indicators between the combined O-MAR group and the non-O-MAR group. Kappa statistics was used to evaluate the consistency between observers. Results:In high/low-density artifacts (ROI H/L), the AI values in all groups showed decrease with increasing VMI keV. In artifact-affected tissue (ROI T), SNR of the CI/VMI (70-150 keV)+O-MAR group were significantly higher than those of the CI/VMI group ( P<0.05), CNR of the CI/VMI(50-150 keV)+O-MAR group were significantly higher than those of the CI/VMI group ( P<0.05). Both overcorrection and new artifacts mainly presented in VMI 50 keV and VMI 70 keV groups; Compared with VMI (50-70 keV) group, significantly less numbers of overcorrection and new artifacts were found in VMI (50-70 keV)+O-MAR group ( P<0.05); regarding the comparison of artifact types, with the VMI keV increasing, the number of a-type banded artifacts gradually decreased on images with high-density artifacts, reaching a minimum of 3 in the VMI 150 keV+O-MAR group; while the number of e-type artifacts with little or no artifacts increased, with the highest number of 23 in the VMI 150 keV+O-MAR group. The total number of high-density artifacts in each type decreased with increasing VMI keV. As VMI keV increased, the diagnostic and image quality scores of high-density artifacts in each group were significantly higher than those of low-density artifacts in the VMI+O-MAR group ( P<0.05). Conclusions:VMI combined with O-MAR can significantly improve the objective and subjective image quality of follow-up CT imaging after 125I seed implantation, enhancing lesion visibility and diagnostic confidence. Additionally, VMI+O-MAR showed more pronounced correction effect on high-density artifacts.

Follicular lymphoma (FL) is the most common inert B-cell lymphoproliferative disease characterized by extensive lymph node involvement, splenomegaly, and bone marrow infiltration. In recent years, with the development of molecular imaging technology and precision medicine, the imaging research of FL has been moving towards a more refined direction. 18F-FDG PET/CT plays an increasingly important role in the diagnosis, staging, efficacy evaluation, and prognosis judgment of FL patients, promoting more precise personalized treatment and improving the efficacy and survival of FL patients. This article reviews the research progress of 18F-FDG PET/CT in the diagnosis and prognosis of FL based on domestic and foreign research progress, summarizing existing literature, in order to provide reference for personalized diagnosis and treatment of FL.

Imaging omics can predict disease evolution, progression, and treatment response by extracting high-dimensional quantitative features from medical imaging. Positron emission tomography (PET) related imaging omics has been a research hotspot in recent years, and its application in urogenital system tumors is rapidly increasing. This article provides a review of the research progress on the application of PET related imaging omics in urogenital system tumors, and discusses the existing challenges and future prospects, in order to provide reference for further clinical application research.

Objective To construct a 3D ResNet deep learning model based on multi-parametric prostate MRI(mpMRI),and to observe its value for automatically identifying the main MR sequences.Methods Totally 1 153 sets pre-biopsy prostate mpMRI data of 1 086 patients who underwent ultrasound-guided prostate biopsy in 3 hospitals were collected and divided into different image datasets,i.e.T2WI,diffusion-weighted imaging(DWI)and apparent diffusion coefficient(ADC)maps with a total of 5 151 images.Then the images were categorized into non-fat-suppressed T2WI(T2WI_nan,n=1 000),fat-suppressed T2WI(T2WI_fs,n=1 188),high b-value DWI(DWI_High,b-value≥500 s/mm2,n=1 045),low b-value DWI(DWI_Low,b-value＜500 s/mm2,n=1 012)or ADC map(n=906),also divided into training set(n=4 122),verification set(n=513)and test set(n=516)at the ratio of 8∶1∶1.After preprocessing and augmentation,a 3D ResNet model for automatically identifying image categories was trained and optimized in the training and verification sets,and its classification efficiency was evaluated in the test set.Results The identifying accuracy,sensitivity,specificity,positive predictive value,negative predictive value,F1 score and Kappa value of the obtained model for automatically identifying categories of images in the test set was 0.995-1.000,0.990-1.000,0.998-1.000,0.990-1.000,0.998-1.000,0.995-1.000 and 0.994-1.000,respectively.Conclusion The obtained 3D ResNet deep learning model could effectively and automatically identify the main sequences of prostate mpMRI.

Objective To develop a 3D V-Net deep learning segmentation model based on multi-center data,and to evaluate its value for automatic segmentation of prostate on T2WI and apparent diffusion coefficient(ADC)maps.Methods Totally 2 894 sets of multi-parametric MRI data of 2 673 patients with clinically suspected prostate cancer from 3 medical centers within 1 month before biopsy were retrospectively collected.Finally 5 974 sets axial images were enrolled,including 3 654 sets of T2WI and 2 320 sets of ADC maps.Prostate contours were manually annotated layer by layer on axial T2WI and ADC maps,and the left-to-right,anterior-to-posterior,superior-to-inferior diameters and volume of prostate were measured and taken as reference standards.The images were divided into training set(n=4 780,including 2 907 sets of T2WI and 1 873 sets of ADC map),verification set(n=601,including 384 sets of T2WI and 217 sets of ADC map)and test set(n=593,including 363 sets of T2WI and 230 sets of ADC map)at the ratio of 8:1:1.After preprocessing and augmentation,3D V-Net was used to construct and train the segmentation model based on training and verification sets,and the segmentation performance of the model was evaluated in test set using Dice similarity coefficient(DSC),Jaccard coefficient(JACARD)and volume similarity(VS),respectively.The parameters measured with the model were compared with the reference standards,and the correlations were explored.Results Compared with the corresponding ADC maps,DSC,JACARD and VS of the model for automatic segmentation of prostate on T2WI in test set were all higher(all P＜0.001).The left-to-right,anterior-to-posterior and superior-to-inferior diameters of prostate measured with the model on both T2WI and ADC maps were all larger than the reference standards(all P＜0.001),while no significant difference of the volume was found(both P＞0.05).All parameters measured with the model on T2WI and ADC maps were positively correlated with reference standards(rs=0.794-0.985).Conclusion 3D V-Net deep learning model could automatically segment prostate on T2WI and ADC maps with high accuracy,and its efficiency based on T2WI was better than that based on ADC maps.

Objective: To compare the clinical outcomes and biomechanical characteristics of 1-, 2-, and 3-level pedicle subtraction osteotomy (PSO), and establish selection criteria based on preoperative radiographic parameters. Methods: Patients undergone PSO to treat ankylosing spondylitis from February 2009 to May 2019 in Sun Yat-sen Memorial Hospital of Sun Yat-sen University were enrolled. According to the quantity of osteotomy performed, the participants were divided into group A (1-level PSO, n = 24), group B (2-level PSO, n = 19), and group C (3-level PSO, n = 11). Clinical outcomes were assessed before surgery and at the final follow-up. Comparisons of the radiographic parameters and quality-of-life indicators were performed among and within these groups, and the selection criteria were established by regression. Finite element analysis was conducted to compare the biomechanical characteristics of the spine treated with different quantity of osteotomies under different working conditions. Results: Three-level PSO improved the sagittal parameters more significantly, but resulted in longer operative time and greater blood loss (p < 0.05). Greater stress was found in the proximal screws and proximal junction area of the vertebra in the model simulating 1-level PSO. Larger stress of screws and vertebra was observed at the distal end in the model simulating 3-level PSO. Conclusion Multilevel PSO works better for larger deformity correction than single-level PSO by allowing greater sagittal parameter correction and obtaining a better distribution of stress in the hardware construct, although with longer operation time and greater blood loss. Three-level osteotomy is recommended for the patients with preoperative of global kyphosis > 85.95°, T1 pelvic angle > 62.3°, sagittal vertical alignment > 299.55 mm, and pelvic tilt+ chin-brow vertical angle > 109.6°.

Objective: To compare the clinical outcomes and biomechanical characteristics of 1-, 2-, and 3-level pedicle subtraction osteotomy (PSO), and establish selection criteria based on preoperative radiographic parameters. Methods: Patients undergone PSO to treat ankylosing spondylitis from February 2009 to May 2019 in Sun Yat-sen Memorial Hospital of Sun Yat-sen University were enrolled. According to the quantity of osteotomy performed, the participants were divided into group A (1-level PSO, n = 24), group B (2-level PSO, n = 19), and group C (3-level PSO, n = 11). Clinical outcomes were assessed before surgery and at the final follow-up. Comparisons of the radiographic parameters and quality-of-life indicators were performed among and within these groups, and the selection criteria were established by regression. Finite element analysis was conducted to compare the biomechanical characteristics of the spine treated with different quantity of osteotomies under different working conditions. Results: Three-level PSO improved the sagittal parameters more significantly, but resulted in longer operative time and greater blood loss (p < 0.05). Greater stress was found in the proximal screws and proximal junction area of the vertebra in the model simulating 1-level PSO. Larger stress of screws and vertebra was observed at the distal end in the model simulating 3-level PSO. Conclusion Multilevel PSO works better for larger deformity correction than single-level PSO by allowing greater sagittal parameter correction and obtaining a better distribution of stress in the hardware construct, although with longer operation time and greater blood loss. Three-level osteotomy is recommended for the patients with preoperative of global kyphosis > 85.95°, T1 pelvic angle > 62.3°, sagittal vertical alignment > 299.55 mm, and pelvic tilt+ chin-brow vertical angle > 109.6°.

Objective: To compare the clinical outcomes and biomechanical characteristics of 1-, 2-, and 3-level pedicle subtraction osteotomy (PSO), and establish selection criteria based on preoperative radiographic parameters. Methods: Patients undergone PSO to treat ankylosing spondylitis from February 2009 to May 2019 in Sun Yat-sen Memorial Hospital of Sun Yat-sen University were enrolled. According to the quantity of osteotomy performed, the participants were divided into group A (1-level PSO, n = 24), group B (2-level PSO, n = 19), and group C (3-level PSO, n = 11). Clinical outcomes were assessed before surgery and at the final follow-up. Comparisons of the radiographic parameters and quality-of-life indicators were performed among and within these groups, and the selection criteria were established by regression. Finite element analysis was conducted to compare the biomechanical characteristics of the spine treated with different quantity of osteotomies under different working conditions. Results: Three-level PSO improved the sagittal parameters more significantly, but resulted in longer operative time and greater blood loss (p < 0.05). Greater stress was found in the proximal screws and proximal junction area of the vertebra in the model simulating 1-level PSO. Larger stress of screws and vertebra was observed at the distal end in the model simulating 3-level PSO. Conclusion Multilevel PSO works better for larger deformity correction than single-level PSO by allowing greater sagittal parameter correction and obtaining a better distribution of stress in the hardware construct, although with longer operation time and greater blood loss. Three-level osteotomy is recommended for the patients with preoperative of global kyphosis > 85.95°, T1 pelvic angle > 62.3°, sagittal vertical alignment > 299.55 mm, and pelvic tilt+ chin-brow vertical angle > 109.6°.

Objective: To compare the clinical outcomes and biomechanical characteristics of 1-, 2-, and 3-level pedicle subtraction osteotomy (PSO), and establish selection criteria based on preoperative radiographic parameters. Methods: Patients undergone PSO to treat ankylosing spondylitis from February 2009 to May 2019 in Sun Yat-sen Memorial Hospital of Sun Yat-sen University were enrolled. According to the quantity of osteotomy performed, the participants were divided into group A (1-level PSO, n = 24), group B (2-level PSO, n = 19), and group C (3-level PSO, n = 11). Clinical outcomes were assessed before surgery and at the final follow-up. Comparisons of the radiographic parameters and quality-of-life indicators were performed among and within these groups, and the selection criteria were established by regression. Finite element analysis was conducted to compare the biomechanical characteristics of the spine treated with different quantity of osteotomies under different working conditions. Results: Three-level PSO improved the sagittal parameters more significantly, but resulted in longer operative time and greater blood loss (p < 0.05). Greater stress was found in the proximal screws and proximal junction area of the vertebra in the model simulating 1-level PSO. Larger stress of screws and vertebra was observed at the distal end in the model simulating 3-level PSO. Conclusion Multilevel PSO works better for larger deformity correction than single-level PSO by allowing greater sagittal parameter correction and obtaining a better distribution of stress in the hardware construct, although with longer operation time and greater blood loss. Three-level osteotomy is recommended for the patients with preoperative of global kyphosis > 85.95°, T1 pelvic angle > 62.3°, sagittal vertical alignment > 299.55 mm, and pelvic tilt+ chin-brow vertical angle > 109.6°.