Quantitative MR imaging biomarkers for distinguishing inflammatory pancreatic mass and pancreatic cancer-a systematic review and meta-analysis.

OBJECTIVES: To evaluate the diagnostic performance of quantitative magnetic resonance (MR) imaging biomarkers in distinguishing between inflammatory pancreatic masses (IPM) and pancreatic cancer (PC). METHODS: A literature search was conducted using PubMed, Embase, the Cochrane Library, and Web of Science through August 2023. Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) was used to evaluate the risk of bias and applicability of the studies. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were calculated using the DerSimonian-Laird method. Univariate meta-regression analysis was used to identify the potential factors of heterogeneity. RESULTS: Twenty-four studies were included in this meta-analysis. The two main types of IPM, mass-forming pancreatitis (MFP) and autoimmune pancreatitis (AIP), differ in their apparent diffusion coefficient (ADC) values. Compared with PC, the ADC value was higher in MFP but lower in AIP. The pooled sensitivity/specificity of ADC were 0.80/0.85 for distinguishing MFP from PC and 0.82/0.84 for distinguishing AIP from PC. The pooled sensitivity/specificity for the maximal diameter of the upstream main pancreatic duct (dMPD) was 0.86/0.74, with a cutoff of dMPD ≤ 4 mm, and 0.97/0.52, with a cutoff of dMPD ≤ 5 mm. The pooled sensitivity/specificity for perfusion fraction (f) was 0.82/0.68, and 0.82/0.77 for mass stiffness values. CONCLUSIONS: Quantitative MR imaging biomarkers are useful in distinguishing between IPM and PC. ADC values differ between MFP and AIP, and they should be separated for consideration in future studies. CLINICAL RELEVANCE STATEMENT: Quantitative MR parameters could serve as non-invasive imaging biomarkers for differentiating malignant pancreatic neoplasms from inflammatory masses of the pancreas, and hence help to avoid unnecessary surgery. KEY POINTS: • Several quantitative MR imaging biomarkers performed well in differential diagnosis between inflammatory pancreatic mass and pancreatic cancer. • The ADC value could discern pancreatic cancer from mass-forming pancreatitis or autoimmune pancreatitis, if the two inflammatory mass types are not combined. • The diameter of main pancreatic duct had the highest specificity for differentiating autoimmune pancreatitis from pancreatic cancer.

Application of magnetic resonance imaging radiomics in endometrial cancer: a systematic review and meta-analysis.

PURPOSE: We aimed to systematically assess the methodological quality and clinical potential application of published magnetic resonance imaging (MRI)-based radiomics studies about endometrial cancer (EC). METHODS: Studies of EC radiomics analyses published between 1 January 2000 and 19 March 2023 were extracted, and their methodological quality was evaluated using the radiomics quality score (RQS) and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Pairwise correlation analyses and separate meta-analyses of studies exploring differential diagnoses and risk prediction were also performed. RESULTS: Forty-five studies involving 3 aims were included. The mean RQS was 13.77 (range: 9-22.5); publication bias was observed in the areas of 'index test' and 'flow and timing'. A high RQS was significantly associated with therapy selection-aimed studies, low QUADAS-2 risk, recent publication year, and high-performance metrics. Raw data from 6 differential diagnosis and 34 risk prediction models were subjected to meta-analysis, revealing diagnostic odds ratios of 23.81 (95% confidence interval [CI] 8.48-66.83) and 18.23 (95% CI 13.68-24.29), respectively. CONCLUSION: The methodological quality of radiomics studies involving patients with EC is unsatisfactory. However, MRI-based radiomics analyses showed promising utility in terms of differential diagnosis and risk prediction.

[Applications of Artificial Intelligence in Pancreatic Cystic Lesion Imaging].

As the detection rate of pancreatic cystic lesions(PCL)increases,artificial intelligence(AI)has made breakthroughs in the imaging workflow of PCL,including image post-processing,lesion detection,segmentation,diagnosis and differential diagnosis.AI-based image post-processing can optimize the quality of medical images and AI-assisted models for lesion detection,segmentation,diagnosis and differential diagnosis significantly enhance the work efficiency of radiologists.This article reviews the application progress of AI in PCL imaging and provides prospects for future research directions.

Seeing beyond the tumor: computed tomography image-based radiomic analysis helps identify ovarian clear cell carcinoma subtype in epithelial ovarian cancer.

OBJECTIVE: To develop and validate a model that can preoperatively identify the ovarian clear cell carcinoma (OCCC) subtype in epithelial ovarian cancer (EOC) using CT imaging radiomics and clinical data. MATERIAL AND METHODS: We retrospectively analyzed data from 282 patients with EOC (training set = 225, testing set = 57) who underwent pre-surgery CT examinations. Patients were categorized into OCCC or other EOC subtypes based on postoperative pathology. Seven clinical characteristics (age, cancer antigen [CA]-125, CA-199, endometriosis, venous thromboembolism, hypercalcemia, stage) were collected. Primary tumors were manually delineated on portal venous-phase images, and 1218 radiomic features were extracted. The F-test-based feature selection method and logistic regression algorithm were used to build the radiomic signature, clinical model, and integrated model. To explore the effects of integrated model-assisted diagnosis, five radiologists independently interpreted images in the testing set and reevaluated cases two weeks later with knowledge of the integrated model's output. The diagnostic performances of the predictive models, radiologists, and radiologists aided by the integrated model were evaluated. RESULTS: The integrated model containing the radiomic signature (constructed by four wavelet radiomic features) and three clinical characteristics (CA-125, endometriosis, and hypercalcinemia), showed better diagnostic performance (AUC = 0.863 [0.762-0.964]) than the clinical model (AUC = 0.792 [0.630-0.953], p = 0.295) and the radiomic signature alone (AUC = 0.781 [0.636-0.926], p = 0.185). The diagnostic sensitivities of the radiologists were significantly improved when using the integrated model (p = 0.023-0.041), while the specificities and accuracies were maintained (p = 0.074-1.000). CONCLUSION: Our integrated model shows great potential to facilitate the early identification of the OCCC subtype in EOC, which may enhance subtype-specific therapy and clinical management.

[Quality Evaluation of Temporomandibular Joint Images from 3 High-resolution Dynamic Sequences].

Objective To compare the image quality of three high-resolution dynamic MRI methods for evaluating the motion of temporomandibular joint disc and condyle. Methods Twenty-five patients with suspected temporomandibular joint disorders were examined by single-shot fast spin-echo (SSFSE),fast imaging employing steady-state acquisition (FIESTA),and spoiled gradient echo (SPGR) on the oblique sagittal position.Two radiologists performed subjective and objective evaluation on the images with double-blind method.The subjective evaluation included the signal intensity of mandibular condyle,articular disc,soft tissue around articular disc,and lateral pterygoid muscle,the contrast between articular disc and condyle,the contrast between articular disc and surrounding soft tissue,condylar motion,and disc movement.The objective evaluation indexes included image signal intensity,signal-to-noise ratio (SNR),and contrast-to-noise ratio (CNR).The subjective and objective indexes of the image quality were compared between the three sequences. Results The SSFSE sequence had lower signal intensity of articular disc and higher signal intensity of condyle and surrounding soft tissue than FIESTA and SPGR sequences (all P<0.001).The SPGR sequence showed higher signal intensity of lateral pterygoid muscle than the SSFSE and FIESTA sequences (P=0.017,P<0.001).Among the three sequences,SSFSE sequence showed the clearest articular disc structure (χ2=41.952,P<0.001),the strongest contrast between articular disc and condyle (χ2=35.379,P<0.001),the strongest contrast between articular disc and surrounding soft tissue (χ2=27.324,P<0.001),and the clearest movement of articular disc (χ2=44.655,P<0.001).SSFSE and FIESTA sequences showed higher proportion of disc displacement and reduction than SPGR sequence (all P<0.001).The CNR (χ2=21.400,P<0.001),SNR (χ2=34.880,P<0.001),and condyle signal intensity (F=337.151,P<0.001) demonstrated differences among SSFSE,FIESTA,and SPGR sequences.The CNR of SSFSE sequence was higher than that of FIESTA sequence (P<0.001),while it had no significant difference between SSFSE and SPGR sequences (P=0.472).In addition,the SSFSE sequence had higher SNR and signal intensity than FIESTA and SPGR sequences (all P<0.001). Conclusion The best image quality can be observed from SSFSE sequence where both the structure and movement of temporomandibular joint are well displayed.Therefore,SSFSE is preferred for the examination of temporomandibular joint movement.

MRI-derived radiomics analysis improves the noninvasive pretreatment identification of multimodality therapy candidates with early-stage cervical cancer.

OBJECTIVES: To develop and validate a clinical-radiomics model that incorporates radiomics signatures and pretreatment clinicopathological parameters to identify multimodality therapy candidates among patients with early-stage cervical cancer. METHODS: Between January 2017 and February 2021, 235 patients with IB1-IIA1 cervical cancer who underwent radical hysterectomy were enrolled and divided into training (n = 194, training:validation = 8:2) and testing (n = 41) sets according to surgical time. The radiomics features of each patient were extracted from preoperative sagittal T2-weighted images. Significance testing, Pearson correlation analysis, and Least Absolute Shrinkage and Selection Operator were used to select radiomic features associated with multimodality therapy administration. A clinical-radiomics model incorporating radiomics signature, age, 2018 Federation International of Gynecology and Obstetrics (FIGO) stage, menopausal status, and preoperative biopsy histological type was developed to identify multimodality therapy candidates. A clinical model and a clinical-conventional radiological model were also constructed. A nomogram and decision curve analysis were developed to facilitate clinical application. RESULTS: The clinical-radiomics model showed good predictive performance, with an area under the curve, sensitivity, and specificity in the testing set of 0.885 (95% confidence interval: 0.781-0.989), 78.9%, and 81.8%, respectively. The AUC, sensitivity, and specificity of the clinical model and clinical-conventional radiological model were 0.751 (0.603-0.900), 63.2%, and 63.6%, 0.801 (0.661-0.942), 73.7%, and 68.2%, respectively. A decision curve analysis demonstrated that when the threshold probability was > 20%, the clinical-radiomics model or nomogram may be more advantageous than the treat all or treat-none strategy. CONCLUSIONS: The clinical-radiomics model and nomogram can potentially identify multimodality therapy candidates in patients with early-stage cervical cancer. KEY POINTS: • Pretreatment identification of multimodality therapy candidates among patients with early-stage cervical cancer helped to select the optimal primary treatment and reduce severe complication risk and costs. • The clinical-radiomics model achieved a better prediction performance compared with the clinical model and the clinical-conventional radiological model. • An easy-to-use nomogram exhibited good performance for individual preoperative prediction.

Assessment of Changes in the Cesarean Scar and Uterus Between One and Two Years after Cesarean Section Using 3D T2w SPACE MRI.

Objective To evaluate changes in morphology of the cesarean scar and uterus between one and two years after cesarean section using high-resolution, three dimensional T2-weighted sampling perfection with application optimized contrast using different flip angle evolutions Magnetic Resonance Imaging (3D T2w SPACE MRI). Methods This prospective study was performed to investigate morphological changes in the cesarean scars and uterus from one to two years after cesarean section using high-resolution, 3D T2w SPACE MRI. The healthy volunteers having no childbearing history were recruited as the controls. All data were measured by two experienced radiologists. All data with normal distribution between the one-year and two-year groups were compared using a paired-sample t test or independent t test. Results Finally, 46 women took a pelvic MR examination one year after cesarean section, and a subset of 15 completed the same examination again after two years of cesarean section. Both the uterine length and the anterior wall thickness after two years of cesarean section (5.75 ± 0.46 and 1.45 ± 0.35 cm) were significantly greater than those measured at one year (5.33 ± 0.59 and 1.25 ± 0.27 cm) (t = -2.363 and -2.175, P= 0.033 and 0.048). No significant difference was shown in myometrial thickness two years after cesarean section (1.45 ±0.35 cm) with respect to the control group (1.58 ± 0.21 cm, P= 0.170). Nine women who underwent MRI twice were considered to have scar diverticula one year after cesarean section, and still had diverticula two years after cesarean section. The thickness, height, and width of the uterine scar showed no significant change from one to two years (all P > 0.05). Conclusions 3D T2w SPACE MRI provides overall morphologic details and shows dynamic changes in the scar and the uterus between one and two years after cesarean section. Scar morphology after cesarean section reached relatively stable one year after cesarean section, and uterine morphology was closer to normal two years after cesarean section.

[Guidelines for Diagnosis and Treatment of Pancreatic Cystic Neoplasms Based on Radiology].

As the detection rate of pancreatic cystic neoplasms (PCN) increases,recommendations or guidelines for the diagnosis and treatment of PCN have been released from professional organizations.From the perspective of radiology,we compared seven guidelines in terms of general introduction,preoperative monitoring methods and strategies,stratification of risk factors,surgical indications,and postoperative follow-ups,aiming to provide references for the evaluation of images and the formulation of individualized approach for the treatment of PCN.

[Cervical Primary Ewing's Sarcoma:Report of One Case].

Ewing's sarcoma in the cervix is characterized by extremely rare occurrence,high degree of malignancy,and rapid progression.The diagnosis of this disease is based on pathology and immunohistochemistry. The main image of the case reported in this paper showed the cervical cyst with solid mass,large volume,and uneven density and signal,and the solid part can be strengthened in enhanced scanning.Because of the rapid growth,the lesion is prone to liquefaction necrosis and bleeding.Since the metastasis occurs early,timely diagnosis is essential.

[Effect of Deep Learning-based Contrast-enhanced CT Image Reconstruction on the Image Quality of the Biliary System].

Objective To evaluate the effect of a deep learning reconstruction (DLR) method on the visibility of contrast-enhanced CT images of the biliary system by comparing it with different iterative reconstruction algorithms including the adaptive iterative dose reduction 3D (AIDR 3D) algorithm,forward projected model based iterative reconstruction solution (FIRST),and filtered back projection (FBP) algorithm. Methods A total of 30 patients subjected to abdominal contrast-enhanced CT and diagnosed with dilatation of common bile duct or extrahepatic bile duct were retrospectively included in this study.The images of the portal phase were reconstructed via four different algorithms (FBP,AIDR 3D,FIRST,and DLR).Signal to noise ratio (SNR) and contrast to noise ratio (CNR) of the dilated bile duct,liver parenchyma,measurable bile duct lesions,and image noise were compared between the four datasets.In subjective analyses,two radiologists independently scored the image quality (best:4 points,second:3 points;third:2 points;fourth:1 point) of the four datasets based on the noise and image visual quality of the biliary system.The Friedman and the Bonferroni-Dunn post-hoc tests were performed for comparison. Results The DLR images (bile duct:4.42±0.87;liver parenchyma:3.78±1.47) yielded higher CNR than the FBP (bile duct:2.21±1.02,P<0.001;liver parenchyma:1.43±1.29,P<0.001),AIDR 3D (bile duct:2.81±0.91,P=0.024;liver parenchyma:2.39±1.94,P=0.278),and FIRST (bile duct:2.51±1.24,P<0.001;liver parenchyma:2.45±1.81,P=0.003) images.Furthermore,the DLR images had higher SNR (bile duct:1.39±0.85,liver parenchyma:9.75±1.90) than the FBP (bile duct:0.86±0.63,P<0.001;liver parenchyma:3.31±1.12,P<0.001) and FIRST (bile duct:1.01±0.61,P=0.013;liver parenchyma:5.73±1.37,P<0.001) images,and showed lower noise (10.51±3.53) than the FBP(4.10±3.92,P<0.001),AIDR 3D (15.72±2.41,P=0.032),and FIRST (17.20±3.82,P<0.001) images.SNR and CNR showed no significant differences between FIRST and AIDR 3D images (all P>0.05).DLR images [4(4,4)] obtained higher score than FPB [1(1,1),P<0.001],AIDR3D[3 (2,3),P=0.029],and FIRST[2 (2,3),P<0.001] images. Conclusion DLR algorithm improved the subjective and objective quality of the contrast-enhanced CT image of the biliary system.

Assessing Liver Function by T1 Maps on Gd-EOB-DTPA-Enhanced MRI for up to 50 Min in Rat Models of Liver Fibrosis: A Longer Hepatobiliary Time Period may Help.

Objectives To investigate whether a longer time period of gadolinium ethoxybenzyl diethylenetriaminepen-taacetic acid (Gd-EOB-DTPA)-enhanced T1 mapping scanning, as well as dynamic contrast-enhanced (DCE) and multiple hepatobiliary phase magnetic resonance imaging (MRI) have the potential to provide information about liver function in rats with liver fibrosis. Methods Forty rats were divided into the carbon tetrachloride-induced hepatic injury groups [carbon tetrachloride for four (n=14), eight (n=8), or twelve (n=8) weeks] and the control group (n=10). Gd-EOB-DTPA-enhanced MRI was performed including T1-mapping (delayed to 50 min), DCE, and multiple hepatobiliary phases. Indocyanine green retention rate at 15 min (ICG-R15) was determined. Parameters such as T1 reduction rate (ΔT1), elimination half-life of ΔT1 (TΔT1 1/2), relative enhancement (RE), time to maximum RE (Tmax), and perfusion parameters were calculated. Pearson correlation analysis was used for correlation analysis between ICG-R15 and each MRI indices. Results ΔT1 at 30, 40, and 50 min showed significant positive correlations with ICG-R15 ( r=0.784, 0.653, 0.757, P=0.007, 0.041, 0.030). TΔT1 1/2 showed a significant positive correlation with ICG-R15 (r=0.685, P=0.029). Tmaxshowed a significant positive correlation with ICG-R15 (r=0.532, P=0.019). Conclusions ΔT1 in the late hepatobiliary phase and T ΔT1 1/2 exhibited moderate correlations with liver function. The longer time period of Gd-EOB-DTPA-enhanced T1 mapping scanning, as well as DCE and multiple hepatobiliary phases, may be of some value for estimating liver function in rats with liver fibrosis.

[Role of Imaging in Early Therapeutic Response Assessment for Neuroendocrine Neoplasm with Liver Metastasis:from Anatomical to Functional View].

Liver metastasis is not rare during the course of neuroendocrine neoplasms.The methods for treating neuroendocrine neoplasm with liver metastasis(NENLM)are diversifying,which exposes the limitations of the early therapeutic response assessment based on only morphological changes.The emerging imaging biomarkers can sensitively describe changes in response to treatment from the functional level,providing new ideas for the therapeutic response evaluation of NENLM.In this paper,we reviewed the status quo and the latest research progress of imaging assessment for early therapeutic response of NENLM,aiming to provide reference for assessing the response and further exploring the treatment-related biomarkers.

[Averaging Strategy to Form the Imaging for Routine Reading of Insulinoma from Pancreatic Perfusion Dataset].

Objective To determine the appropriate averaging strategy for pancreatic perfusion datasets to create images for routine reading of insulinoma.Methods Thirty-nine patients undergoing pancreatic perfusion CT in Peking Union Medical College Hospital and diagnosed as insulinoma by pathology were enrolled in this retrospective study.The time-density curve of abdominal aorta calculated by software dynamic angio was used to decide the timings for averaging.Five strategies,by averaging 3,5,7,9 and 11 dynamic scans in perfusion,all including peak enhancement of the abdominal aorta,were investigated in the study.The image noise,pancreas signal-to-noise ratio(SNR),lesion contrast and lesion contrast-to-noise ratio(CNR)were recorded and compared.Besides,overall image quality and insulinoma depiction were also compared.ANOVA and Friedman's test were performed.Results The image noise decreased and the SNR of pancreas increased with the increase in averaging time points(all P<0.001).The lesion contrast(69.81±41.35)averaged from 5 scans showed no significant difference compared with that(72.77±45.25)averaged from 3 scans(P=0.103),both of which were higher than that in other groups(all P≤0.001).The lesion CNRs of the last four groups showed no significant difference(all P>0.99)and were higher than that of the first group(all P<0.05).There was no significant difference in overall image quality among the 5 groups(P=0.977).Conclusions Image averaged from 5 scans showed moderate image noise,pancreas SNR and relatively high lesion contrast and lesion CNR.Therefore,it is advised to be used in image averaging to detect insulinoma.

Radiomics Based on MRI as a Biomarker to Guide Therapy by Predicting Upgrading of Prostate Cancer From Biopsy to Radical Prostatectomy.

BACKGROUND: Biopsy Gleason score (GS) is crucial for prostate cancer (PCa) treatment decision-making. Upgrading in GS from biopsy to radical prostatectomy (RP) puts a proportion of patients at risk of undertreatment. PURPOSE: To develop and validate a radiomics model based on multiparametric magnetic resonance imaging (mp-MRI) to predict PCa upgrading. STUDY TYPE: Retrospective, radiomics. POPULATION: A total of 166 RP-confirmed PCa patients (training cohort, n = 116; validation cohort, n = 50) were included. FIELD STRENGTH/SEQUENCE: 3.0T/T2 -weighted (T2 W), apparent diffusion coefficient (ADC), and dynamic contrast enhancement (DCE) sequences. ASSESSMENT: PI-RADSv2 score for each tumor was recorded. Radiomic features were extracted from T2 W, ADC, and DCE sequences and Mutual Information Maximization criterion was used to identify the optimal features on each sequence. Multivariate logistic regression analysis was used to develop predictive models and a radiomics nomogram and their performance was evaluated. STATISTICAL TESTS: Student's t or chi-square were used to assess the differences in clinicopathologic data between the training and validation cohorts. Receiver operating characteristic (ROC) curve analysis was performed and the area under the curve (AUC) was calculated. RESULTS: In PI-RADSv2 assessment, 67 lesions scored 5, 70 lesions scored 4, and 29 lesions scored 3. For each sequence, 4404 features were extracted and the top 20 best features were selected. The radiomics model incorporating signatures from the three sequences achieved better performance than any single sequence (AUC: radiomics model 0.868, T2 W 0.700, ADC 0.759, DCE 0.726). The combined mode incorporating radiomics signature, clinical stage, and time from biopsy to RP outperformed the clinical model and radiomics model (AUC: combined model 0.910, clinical model 0.646, radiomics model 0.868). The nomogram showed good performance (AUC 0.910) and calibration (P-values: training cohort 0.624, validation cohort 0.294). DATA CONCLUSION: Radiomics based on mp-MRI has potential to predict upgrading of PCa from biopsy to RP. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 5 J. Magn. Reson. Imaging 2020;52:1239-1248.

Typical and atypical pelvic MRI characteristics of Mayer-Rokitansky-Küster-Hauser syndrome: a comprehensive analysis of 201 patients.

OBJECTIVES: To comprehensively evaluate the pelvic magnetic resonance imaging (MRI) findings of Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome and summarize the typical and atypical characteristics. METHODS: A retrospective analysis of 201 consecutive MRKH patients was carried out. Pelvic MRI was reviewed by two experienced gynecological radiologists in consensus. Characteristics including the morphology, signal pattern and volumes of the uterine rudiments, location and volume of the ovaries, and the degree of vaginal dysgenesis were evaluated. Other noted abnormalities were also recorded. RESULTS: Morphologically, the majority (95%) of patients displayed bilateral uterine rudiments combined with a fibrous band. The minority of patients showed no (3.5%) or unilateral (1.5%) uterine rudiments. A total of 385 uterine rudiments were detected which showed four types of signal patterns: one-layer differentiation (325, 84.4%), two-layer differentiation (27, 7%), three-layer differentiation without subsequent alteration (23, 6.0%), and three-layer differentiation with hematometra and/or ipsilateral hematosalpinx (10, 2.6%). The median volumes of these four types of uterine rudiments were 2.6 ml (1.69-3.81 ml), 3.19 ml (2.67-4.51 ml), 6.05 ml (3.37-12.44 ml), and 31.97 ml (19.2-38.7 ml), respectively. The mean ovarian volume was 6.49 ± 3.91 ml. Abnormally located ovaries were detected in 63 (31.3%) patients. The distal vagina was discernable in 25.1% of patients. CONCLUSION: MRKH patients typically display bilateral uterine rudiments combined with a fibrous band and normally located ovaries. The uterine rudiments are generally small with only one-layer differentiation, a subset of which might be large and exhibited other atypical presentations, including two- or three-layer differentiation or even hematometra. Abnormally located ovaries are not rare. KEY POINTS: • Morphologically, MRKH patients typically displayed bilateral uterine rudiments combined with a fibrous band. • Typically, the uterine rudiments (84.4%) were small and displayed only one-layer differentiation. • About 15.6% of rudiments showed atypical characteristics including two- or three-layer differentiation, even complicated with hematometra or hematosalpinx.

Potential value of CT radiomics in the distinction of intestinal-type gastric adenocarcinomas.

OBJECTIVE: The purpose of the study was to investigate the role of CT radiomics for the preoperative distinction of intestinal-type gastric adenocarcinomas. MATERIALS AND METHODS: A total of 187 consecutive patients with preoperative contrast CT examination and pathologically proven gastric adenocarcinoma were retrospectively collected. Patients were divided into a training set (n = 150) and a test set (n = 37). Arterial phase (AP), portal phase (PP), and delay phase (DP) images were retrieved for analysis. A dedicated postprocessing software was used to segment the lesions and extract radiomics features. Random forest (RF) algorithm was applied to construct the classifier models. A nomogram was developed by incorporating multiphase radiomics scores. Receiver operating characteristic (ROC) curves were used to evaluate the performance of the radiomics model and nomogram in both sets. RESULTS: The radiomics model showed a favorable capability in the distinction of intestinal-type gastric adenocarcinomas. The areas under curves (AUCs) of the AP, PP, and DP radiomics models were 0.754 (95% CI: 0.676, 0.820), 0.815 (95% CI: 0.744, 0.874), and 0.764 (95% CI: 0.688, 0.829) in the training set, respectively, which were confirmed in the test set with AUCs of 0.742 (95% CI: 0.572, 0.872), 0.775 (95% CI: 0.608, 0.895), and 0.857 (95% CI: 0.703, 0.950), respectively. The nomogram yielded excellent performance for distinguishing intestinal-type adenocarcinomas in both sets, with AUCs of 0.928 (95%: 0.875, 0.964) and 0.904 (95% CI: 0.761, 0.976). CONCLUSIONS: The multiphase CT radiomics nomogram holds promise for the individual preoperative discrimination of intestinal-type gastric adenocarcinoma. KEY POINTS: • CT radiomics has a potential role in the distinction of intestinal-type gastric adenocarcinomas. • Single-phase enhanced CT-based radiomics showed favorable capability in distinguishing intestinal-type tumors. • The nomogram which incorporates the multiphase radiomics scores could facilitate the individual prediction of intestinal-type lesions.

Detection of insulinoma: one-stop pancreatic perfusion CT with calculated mean temporal images can replace the combination of bi-phasic plus perfusion scan.

OBJECTIVE: To evaluate the feasibility of one-stop pancreatic perfusion CT with mean temporal (MT) imaging replacing the combination of a bi-phasic scan plus a perfusion scan to detect insulinoma. MATERIAL AND METHODS: Forty-five patients with suspected insulinoma, who underwent both biphasic and perfusion CT, were enrolled in this retrospective study. MT datasets including images for different delineation purposes were generated by averaging 3 dynamic datasets from perfusion CT, which are MTA for arterial, MTPV for portal vein and MTO for lesions. Two readers assessed the image quality and diagnostic performance separately for biphasic and MT datasets. Radiation doses were also assessed. Paired t tests, Wilcoxon signed-rank tests and McNemar's tests were applied for comparison. RESULTS: Compared with bi-phasic CT images, image noise, SNR and CNR of the MTA and MTPV datasets were all non-inferior (noise and CNR of the portal vein, p = 0.565 and p = 0.227, respectively) or superior (p ≤ 0.001). The subjective image quality was better in the MTA and MTPV images (p < 0.001 to p = 0.004). The sensitivity and NPV of MT images were also better (95% vs 75% and 75% vs 37.5% for reader 1; 97.5% vs 72.5% and 85.7% vs 35.3% for reader 2). Omitting the bi-phasic scan resulted in a dose reduction of 25% ± 4%. CONCLUSION: MT imaging can allow pancreatic perfusion CT to be used alone without the need for an additional bi-phasic CT in the detection of insulinoma. KEY POINTS: • Mean temporal images reconstructed from perfusion CT with an averaging technique reproduce usual bi-phasic images (arterial and portal phases). • The image quality of mean temporal images is non-inferior or superior to native bi-phasic CT. The sensitivity and NPV for the diagnosis of insulinoma are better for mean temporal images than for traditional bi-phasic CT. • Mean temporal imaging can allow pancreatic perfusion CT to be used alone without the need for an additional bi-phasic CT in the detection of insulinoma. Radiation dose saving is important.

CT radiomics nomogram for the preoperative prediction of lymph node metastasis in gastric cancer.

PURPOSE: To investigate the role of computed tomography (CT) radiomics for the preoperative prediction of lymph node (LN) metastasis in gastric cancer. MATERIALS AND METHODS: This retrospective study included 247 consecutive patients (training cohort, 197 patients; test cohort, 50 patients) with surgically proven gastric cancer. Dedicated radiomics prototype software was used to segment lesions on preoperative arterial phase (AP) CT images and extract features. A radiomics model was constructed to predict the LN metastasis by using a random forest (RF) algorithm. Finally, a nomogram was built incorporating the radiomics scores and selected clinical predictors. Receiver operating characteristic (ROC) curves were used to validate the capability of the radiomics model and nomogram on both the training and test cohorts. RESULTS: The radiomics model showed a favorable discriminatory ability in the training cohort with an area under the curve (AUC) of 0.844 (95% CI, 0.759 to 0.909), which was confirmed in the test cohort with an AUC of 0.837 (95% CI, 0.705 to 0.926). The nomogram consisted of radiomics scores and the CT-reported LN status showed excellent discrimination in the training and test cohorts with AUCs of 0.886 (95% CI, 0.808 to 0.941) and 0.881 (95% CI, 0.759 to 0.956), respectively. CONCLUSIONS: The CT-based radiomics nomogram holds promise for use as a noninvasive tool in the individual prediction of LN metastasis in gastric cancer. KEY POINTS: • CT radiomics showed a favorable performance for the prediction of LN metastasis in gastric cancer. • Radiomics model outperformed the routine CT in predicting LN metastasis in gastric cancer. • The radiomics nomogram holds potential in the individualized prediction of LN metastasis in gastric cancer.

[Relationship between Aneurysm Volumetric Changes and Endoleaks after Endovascular Abdominal Aortic Aneurysm Repair].

Objective To evaluate the relationship of volumetric changes and endoleaks after endovascular aneurysm repair(EVAR)for abdominal aortic aneurysms(AAAs). Methods We retrospectively evaluated the clinical and imaging data of 54 patients who had underwent EVAR within 1 month after their aneurysms were detected.All patients received abdominal and pelvic enhanced computed tomography(CTA)for two follow-up visits in Peking Union Medical College Hospital from July 2014 to February 2019.Three-dimensional volumes and maximum diameters on axial CT of the aortic aneurysms were calculated by dedicated semi-automated 3D segmentation software before surgery(V0 and D0),in the 4 th postoperative month(V1and D1),and in the 12 th postoperative month(V2and D2),respectively.The presence or absence of endoleak for each patient with the V1/V0,V2/V0,and V2/V1 were calculated to assess the significance of volume changes with respect to endoleaks and the correlation between volume changes and maximum diameter changes on axial CT images. Results Of the 54 patients,endoleaks were found in 11 patients at the first follow-up visit(4 months after surgery),among whom 8 patients were arranged a second follow-up visit(12 months after surgery),during which endoleaks were found in 5 patients.Fifteen of 43 non-leaked patients underwent a second CTA examination,which revealed endoleak in one case.Patients who did exhibit endoleaks[n =11,V1/V0=1.086(1.033,1.116)]showed significant increases in aneurysm volume when compared with those who did not exhbit endoleaks[n =43,V1/V0=1.019(0.970,1.065)]at the first follow-up visit(Z=-2.695,P=0.007),although no significant difference was found with regard to volume changes between endoleaks(n=6,V2/V0=1.1±0.2,V2/V1=1.0±0.1)and non-endoleaks(n=17,V2/V0=1.0±0.1,V2/V1=1.0±0.1)at the second follow-up visit(t=0.725,P=0.476)as well as between these two follow-up visits(t=-0.021,P=0.984).V0 and D0 were moderately correlated with V1 and D1,respectively(r=0.5,P<0.001)and strongly correlated with V2 and D2,respectively(r=0.8,P<0.001).V1 and D1 were strongly correlated with V2 and D2,respectively(r=0.8,P<0.001). Conclusions The changes of aneurysm volume cannot reliably reflect the occurrence of endoleaks.The change of maximum axial diameter of aneurysm has certain correlation with the changes of aneurysm volume.

[Correlation of Intravoxel Incoherent Motion-derived Parameters with Computer Tomography Perfusion Parameters in Insulinoma].

Objective To prospectively evaluate the correlation between intravoxel incoherent motion (IVIM)-derived parameters and CT perfusion parameters as well as the pathological grade in insulinoma. Methods A total of 55 patients with suspected insulinoma undergoing IVIM and CT perfusion scans were prospectively enrolled. The images were post-processed to obtain IVIM parameters including apparent diffusion coefficient (ADC),diffusion (D),perfusion correlated diffusion (D*),and f,and CT perfusion parameters including blood flow (BF),blood volume (BV),and permeability (PM). The pathological specimens were stained to obtain pathological parameters including the grading,ki-67 index,and the mitotic count. The IVIM derived parameters of normal pancreas including head,body,and tail as well as that of the pancreatic insulinoma were compared. The correlation between IVIM parameters and CT perfusion parameters as well as the pathological parameters was analyzed. Results ADC and D values of pancreatic tail were significantly lower than those of the pancreatic head and neck (all P<0.001). There were significant differences in all IVIM parameters between insulinoma and normal pancreas (all P<0.001). The ADC and f value of the normal pancreas was positively correlated with BF (r=0.437,P=0.003;r=0.357,P=0.010). There is no correlation between the remaining IVIM parameters and the CT perfusion parameters as well as between IVIM parameters and pathological parameters (all P>0.05). Conclusions IVIM parameters differ at different anatomical parts of normal pancreas. IVIM parameters can distinguish normal pancreatic parenchyma from insulinoma. The ADC value is weakly correlated with BF.