Objective To evaluate the image quality of abdominal dual-energy CT virtual monoenergetic imaging (VMI) in patients with early gastric cancer using titanium alloy clips and assess its effectiveness on reducing metal artifacts. Methods A retrospective study was conducted, including 31 patients with gastric cancer who underwent abdominal dual-energy CT scans with titanium clips inserted in the gastric cavity. Each scan was reconstructed into mixed images (simulated 120 kVp CT) and VMIs with energy levels ranging from 40 keV to 140 keV. Metal artifacts were quantitatively evaluated by measuring the noise values in the lesion and perigastric regions. The contrast-noise ratio (CNR) of the lesion and the corresponding liver tissue was calculated to assess the image quality. Two radiologists independently evaluated the images, considering overall quality, artifact severity, lesion conspicuity, perigastric clarity, and vascular contrast. Results Quantitative analysis revealed that metal artifacts in both the lesion and perigastric regions decreased as the energy level increased. VMIs at 80-140 keV (lesion site) and 90-140 keV (perigastric space) showed significantly fewer artifacts compared to mixed images (P＜0.05). The CNR of lesions remained stable across VMIs at 50-140 keV, while the CNR of normal liver tissue decreased significantly with increasing energy (P＜0.05). In the subjective assessment, VMIs at 80-140 keV had higher artifact scores than mixed images (P＜0.05). VMIs at 70-90 keV provided better lesion conspicuity and perigastric clarity, although vascular contrast decreased significantly with increasing energy (P＜0.05). VMIs at 70-90 keV showed better overall quality (P＜0.05), though not significantly different from mixed images. Conclusions VMIs at 80 keV and 90 keV improve the visibility of lesions and perigastric regions affected by metallic clips, which combined with mixed images can enhance radiologists’ diagnostic accuracy.

This review systematically summarized the development of breast imaging.Focused on the development,breakthroughs and limitations of breast imaging techniques,such as mammography,breast ultrasound and MRI,emphasizing the innovative applications of multimodal imaging fusion and artificial intelligence(AI)in screening,diagnosis and treatment of breast cancer,as well as the evolution of technologies and clinical achievements,the significant value of multimodal imaging fusion and AI for improving screening sensitivity,enhancing diagnostic accuracy and optimizing the medical process of breast cancer,as well as the future development of breast imaging were revealed.

Background and purpose:Accurate preoperative differentiation between vagal nerve cervical schwannomas(SCCS)and sympathetic chain cervical schwannomas(SCCS)in the neck is crucial because of their different postoperative complication.This study aimed to construct and validate a Diagnosis Score and vascular displacement nomogram for the preoperative differentiation of VNCS from SCCS in the neck.Methods:This cross-sectional study retrospectively analyzed patients with pathologically confirmed VNCS and SCCS at Fudan University Shanghai Cancer Center from January 2017 to April 2022.This study was approved by the medical ethics committee of Fudan University Shanghai Cancer Center(approval number:1612167-18).Inclusion criteria:① histopathological diagnosis of VNCS or SCCS through biopsy or surgical resection;② patients with complete clinic data;③availability of preoperative contrast-enhanced computed tomography(CT)or magnetic resonance imaging(MRI)examinations.Patients were excluded for:① contrast agent contraindications;② poor image quality;③ severe artifacts;④ non-standard scanning protocols.The cohort was randomly divided into training and validation sets in a 7∶3 ratio.Two radiologists(one resident and one attending physician)independently evaluated tumor characteristics(location,size and vascular displacement patterns)on preoperative imaging.Independent predictors were selected using LASSO regression analysis to construct a diagnostic scoring system and nomogram,with model performance evaluated by the receiver operating characteristic(ROC)curve.Results:A total of 110 patients were enrolled,with 77 cases allocated to the training set and 33 cases to the validation set.The age range was 24-78 years,and the mean age was(51.22±12.36)years.There were no statistically significant differences in baseline characteristics including age,gender,tumor location and size between the two patient groups(P＞0.05).ICA/ECA splaying was significantly associated with SCCS(P＜0.001),while the ICA/IJV splaying was significantly associated with VNCS(P＜0.001).Lateral and posterior ICA displacement were significantly associated with SCCS(P＜0.001),and medial and anterior ICA displacement were significantly associated with VNCS(P＜0.001).Five features including tumor size,ICA displacement direction,IJV displacement direction,ICA/ECA splaying and ICA/IJV splaying were used to establish the Diagnosis Score and nomogram.The nomogram combined imaging features showed favorable preference value for differentiating VNCS from SCCS,with area under curve(AUC)values of 0.953(95%CI:0.912-0.994)and 0.939(95%CI:0.885-0.993)for the training and validation cohorts,respectively.Conclusion:The Diagnosis Score and vascular displacement nomogram showed favorable predictive efficacy for differentiating VNCS from SCCS in the neck,and might be useful for clinical decision-making.

Background and purpose:In the quality control of mammography,the signal-to-noise ratio(SNR)refers to the ratio of the useful signal intensity to the background noise in the image,which is one of the important indicators for measuring the quality of the image.The coefficient of variation(CoV)is a commonly used indicator to describe the consistency and repeatability of SNR.This study aimed to assess the stability and repeatability of mammographic device performance by analyzing the changes in SNR CoV in two-dimensional(2D)images and tomosynthesis images(referred to as Tomo images)under different exposure modes using three mammographic devices from different manufacturers.Methods:A polymethylmethacrylate(PMMA)phantom designed for mammography quality control was used to perform automatic exposure detection at PMMA thicknesses ranging from 20-80 mm,with actual compression thickness equivalent to the average density of the breast compressed to 21-103 mm under full-field digital mammography(FFDM),low-dose mammography and digital breast tomosynthesis(DBT)exposure modes.The CoV of SNR in 2D images and tomosynthesis images was calculated for different mammographic devices under different exposure modes and compression thicknesses.Results:Between the compression thicknesses equivalent to the average density of the breast from 21 mm to 103 mm under FFDM,low-dose mammography,and DBT exposure modes,the differences in SNR CoV of 2D images under different exposure modes among mammographic devices 1,2,and 3 were statistically significant only in the DBT exposure mode(P=0.003),with SNR CoV ranging from 0.188%to 0.720%,0.368%to 1.073%and 0.402%to 1.662%,respectively.There were no statistically significant differences in SNR CoV of 2D images among devices 1,2,and 3 under FFDM and low-dose exposure modes(P=0.060).Under the DBT exposure mode,there were no statistically significant differences in the SNR CoV of the first projection image and the 0° projection image of tomosynthesis among devices 1(2 angles),2,and 3(P=0.373,P=0.742,P=0.225,P=0.693,respectively).Conclusion:The SNR CoV in 2D images and tomosynthesis images varies under different mammographic devices and exposure modes,with no fixed or standard values,but all within the required range for mammographic device quality control.The stability and repeatability of 2D images of mammographic devices are better under FFDM and low-dose exposure modes;the SNR CoV values of the first projection image and the 0° projection image of tomosynthesis under the DBT exposure mode show no statistical differences,indicating good stability of the devices.

Background and purpose:With the increasing use of medical imaging examinations,Computed tomography(CT)scans have become one of the primary sources of effective dose.This study analyzed the correlation between radiation dose,image quality and body composition in thyroid CT to provide a data foundation for better control of radiation dose and image quality in the future.Methods:A retrospective analysis was conducted on patients who underwent thyroid CT scans at Fudan University Shanghai Cancer Center from January 2015 to December 2019.CT values and standard deviations(SD)of the homogeneous parenchyma of the thyroid were collected,and CT values and SD values of adjacent subcutaneous fat tissue were measured with the same region of interest(ROI)size.All data were measured three times to obtain the average value,and the volume CT dose index(CTDIvol)and dose-length product(DLP)were recorded.Effective dose values and signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)for various parts were calculated.All patients underwent bone density examinations,and patient height,weight,body mass index(BMI),body surface area(BSA),and the percentage of muscle and fat in the spine and thighs were recorded.Results:A total of 104 patients were enrolled in this study.The SNR of thyroid CT images and the percentage of spinal muscle(r=0.284,P=0.004),CNR of thyroid CT images and the percentage of spinal fat(r=0.197,P=0.045),and the effective dose of thyroid CT images and age,weight,BMI,thigh fat percentage,and body surface area(r=0.221,0.247,0.260,0.262,and 0.222;P=0.024,0.011,0.008,0.007 and 0.024)were positively correlated.While,SNR and age,weight,BMI,and the percentage of spinal fat(r=-0.292,-0.198,-0.207,and-0.284;P=0.003,0.044,0.035,0.004),CNR and the percentage of spinal muscle(r=-0.197,P=0.045),and the effective dose and the percentage of thigh muscle(r=-0.262,P=0.007)were negatively correlated.Conclusion:The radiation dose in thyroid CT is correlated with female body composition.The image quality is related to female body composition,providing a data foundation for better control of radiation dose and image quality in the future.

Background and purpose:Accurate preoperative differentiation between vagal nerve cervical schwannomas(SCCS)and sympathetic chain cervical schwannomas(SCCS)in the neck is crucial because of their different postoperative complication.This study aimed to construct and validate a Diagnosis Score and vascular displacement nomogram for the preoperative differentiation of VNCS from SCCS in the neck.Methods:This cross-sectional study retrospectively analyzed patients with pathologically confirmed VNCS and SCCS at Fudan University Shanghai Cancer Center from January 2017 to April 2022.This study was approved by the medical ethics committee of Fudan University Shanghai Cancer Center(approval number:1612167-18).Inclusion criteria:① histopathological diagnosis of VNCS or SCCS through biopsy or surgical resection;② patients with complete clinic data;③availability of preoperative contrast-enhanced computed tomography(CT)or magnetic resonance imaging(MRI)examinations.Patients were excluded for:① contrast agent contraindications;② poor image quality;③ severe artifacts;④ non-standard scanning protocols.The cohort was randomly divided into training and validation sets in a 7∶3 ratio.Two radiologists(one resident and one attending physician)independently evaluated tumor characteristics(location,size and vascular displacement patterns)on preoperative imaging.Independent predictors were selected using LASSO regression analysis to construct a diagnostic scoring system and nomogram,with model performance evaluated by the receiver operating characteristic(ROC)curve.Results:A total of 110 patients were enrolled,with 77 cases allocated to the training set and 33 cases to the validation set.The age range was 24-78 years,and the mean age was(51.22±12.36)years.There were no statistically significant differences in baseline characteristics including age,gender,tumor location and size between the two patient groups(P＞0.05).ICA/ECA splaying was significantly associated with SCCS(P＜0.001),while the ICA/IJV splaying was significantly associated with VNCS(P＜0.001).Lateral and posterior ICA displacement were significantly associated with SCCS(P＜0.001),and medial and anterior ICA displacement were significantly associated with VNCS(P＜0.001).Five features including tumor size,ICA displacement direction,IJV displacement direction,ICA/ECA splaying and ICA/IJV splaying were used to establish the Diagnosis Score and nomogram.The nomogram combined imaging features showed favorable preference value for differentiating VNCS from SCCS,with area under curve(AUC)values of 0.953(95%CI:0.912-0.994)and 0.939(95%CI:0.885-0.993)for the training and validation cohorts,respectively.Conclusion:The Diagnosis Score and vascular displacement nomogram showed favorable predictive efficacy for differentiating VNCS from SCCS in the neck,and might be useful for clinical decision-making.

Background and purpose:With the increasing use of medical imaging examinations,Computed tomography(CT)scans have become one of the primary sources of effective dose.This study analyzed the correlation between radiation dose,image quality and body composition in thyroid CT to provide a data foundation for better control of radiation dose and image quality in the future.Methods:A retrospective analysis was conducted on patients who underwent thyroid CT scans at Fudan University Shanghai Cancer Center from January 2015 to December 2019.CT values and standard deviations(SD)of the homogeneous parenchyma of the thyroid were collected,and CT values and SD values of adjacent subcutaneous fat tissue were measured with the same region of interest(ROI)size.All data were measured three times to obtain the average value,and the volume CT dose index(CTDIvol)and dose-length product(DLP)were recorded.Effective dose values and signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)for various parts were calculated.All patients underwent bone density examinations,and patient height,weight,body mass index(BMI),body surface area(BSA),and the percentage of muscle and fat in the spine and thighs were recorded.Results:A total of 104 patients were enrolled in this study.The SNR of thyroid CT images and the percentage of spinal muscle(r=0.284,P=0.004),CNR of thyroid CT images and the percentage of spinal fat(r=0.197,P=0.045),and the effective dose of thyroid CT images and age,weight,BMI,thigh fat percentage,and body surface area(r=0.221,0.247,0.260,0.262,and 0.222;P=0.024,0.011,0.008,0.007 and 0.024)were positively correlated.While,SNR and age,weight,BMI,and the percentage of spinal fat(r=-0.292,-0.198,-0.207,and-0.284;P=0.003,0.044,0.035,0.004),CNR and the percentage of spinal muscle(r=-0.197,P=0.045),and the effective dose and the percentage of thigh muscle(r=-0.262,P=0.007)were negatively correlated.Conclusion:The radiation dose in thyroid CT is correlated with female body composition.The image quality is related to female body composition,providing a data foundation for better control of radiation dose and image quality in the future.

Background and purpose:In the quality control of mammography,the signal-to-noise ratio(SNR)refers to the ratio of the useful signal intensity to the background noise in the image,which is one of the important indicators for measuring the quality of the image.The coefficient of variation(CoV)is a commonly used indicator to describe the consistency and repeatability of SNR.This study aimed to assess the stability and repeatability of mammographic device performance by analyzing the changes in SNR CoV in two-dimensional(2D)images and tomosynthesis images(referred to as Tomo images)under different exposure modes using three mammographic devices from different manufacturers.Methods:A polymethylmethacrylate(PMMA)phantom designed for mammography quality control was used to perform automatic exposure detection at PMMA thicknesses ranging from 20-80 mm,with actual compression thickness equivalent to the average density of the breast compressed to 21-103 mm under full-field digital mammography(FFDM),low-dose mammography and digital breast tomosynthesis(DBT)exposure modes.The CoV of SNR in 2D images and tomosynthesis images was calculated for different mammographic devices under different exposure modes and compression thicknesses.Results:Between the compression thicknesses equivalent to the average density of the breast from 21 mm to 103 mm under FFDM,low-dose mammography,and DBT exposure modes,the differences in SNR CoV of 2D images under different exposure modes among mammographic devices 1,2,and 3 were statistically significant only in the DBT exposure mode(P=0.003),with SNR CoV ranging from 0.188%to 0.720%,0.368%to 1.073%and 0.402%to 1.662%,respectively.There were no statistically significant differences in SNR CoV of 2D images among devices 1,2,and 3 under FFDM and low-dose exposure modes(P=0.060).Under the DBT exposure mode,there were no statistically significant differences in the SNR CoV of the first projection image and the 0° projection image of tomosynthesis among devices 1(2 angles),2,and 3(P=0.373,P=0.742,P=0.225,P=0.693,respectively).Conclusion:The SNR CoV in 2D images and tomosynthesis images varies under different mammographic devices and exposure modes,with no fixed or standard values,but all within the required range for mammographic device quality control.The stability and repeatability of 2D images of mammographic devices are better under FFDM and low-dose exposure modes;the SNR CoV values of the first projection image and the 0° projection image of tomosynthesis under the DBT exposure mode show no statistical differences,indicating good stability of the devices.

This review systematically summarized the development of breast imaging.Focused on the development,breakthroughs and limitations of breast imaging techniques,such as mammography,breast ultrasound and MRI,emphasizing the innovative applications of multimodal imaging fusion and artificial intelligence(AI)in screening,diagnosis and treatment of breast cancer,as well as the evolution of technologies and clinical achievements,the significant value of multimodal imaging fusion and AI for improving screening sensitivity,enhancing diagnostic accuracy and optimizing the medical process of breast cancer,as well as the future development of breast imaging were revealed.

Objective:To evaluate the value of radiomics based on contrast-enhanced spectral mammography (CESM) of internal and peripheral regions combined with clinical factors in predicting benign and malignant breast lesions of breast imaging reporting and data system category 4 (BI-RADS 4).Methods:A retrospective analysis was performed on the clinical and imaging data of patients with breast lesions who were treated in Yantai Yuhuangding Hospital (Center 1) Affiliated to Qingdao University from July 2017 to July 2020 and in Fudan University Cancer Hospital (Center 2) from June 2019 to July 2020. Center 1 included 835 patients, all female, aged 17-80 (49±12) years, divided into training set (667 cases) and test set (168 cases) according to the "train-test-split" function in Python software at a ratio of 8∶2; and 49 patients were included from Center 2 as external validation set, all female, aged 34-70 (51±8) years. The radiomics features were extracted from the intralesional region (ITR), the perilesional regions of 5, 10 mm (PTR 5 mm, PTR10 mm) and the intra-and perilesional regions of 5, 10 mm (IPTR 5 mm, IPTR 10 mm) and were selected by variance filtering, SelectKBest algorithm, and least absolute shrinkage and selection operator. Then five radiomics signatures were constructed including ITR signature, PTR 5 mm signature, PTR 10 mm signature, IPTR 5 mm signature, IPTR 10 mm signature. In the training set, univariable and multivariable logistic regressions were used to construct nomograms by selecting radiomics signatures and clinical factors with significant difference between benign and malignant BI-RADS type 4 breast lesions. The efficacy of nomogram in predicting benign and malignant BI-RADS 4 breast lesions was evaluated by the receiver operating characteristic curve and area under the curve (AUC). Decision curve and calibration curve were used to evaluate the net benefit and calibration capability of the nomogram.Results:The nomogram included ITR signature, PTR 5 mm signature, PTR 10 mm signature, IPTR 5 mm signature, age, and BI-RADS category 4 subclassification for differentiating malignant and benign BI-RADS category 4 breast lesions and obtained AUCs of 0.94, 0.92, and 0.95 in the training set, test set, and external validation set, respectively. The calibration curve showed good agreement between the predicted probabilities and actual results and the decision curve indicated a good net benefit of the nomogram for predicting malignant BI-RADS 4 lesions in the training set, test set, and external validation set.Conclusion:The nomogram constructed from the radiomics features of the internal and surrounding regions of CESM breast lesions combined with clinical factors is attributed to differentiate benign from malignant BI-RADS category 4 breast lesions.