AUNP-12 Near-Infrared Fluorescence Probes across NIR-I to NIR-II Enable In Vivo Detection of PD-1/PD-L1 Axis in the Tumor Microenvironment.

The innovative PD-1/PD-L1 pathway strategy is gaining significant traction in cancer therapeutics. However, fluctuating response rates of 20-40% to PD-1/PD-L1 inhibitors, coupled with the risk of hyperprogression after immunotherapy, underscore the need for accurate patient selection and the identification of more beneficiaries. Molecular imaging, specifically near-infrared (NIR) fluorescence imaging, is a valuable alternative for real-time, noninvasive visualization of dynamic PD-L1 expression in vivo. This research introduces AUNP-12, a novel PD-L1-targeting peptide antagonist conjugated with Cy5.5 and CH1055 for first (NIR-I) and second near-infrared (NIR-II) imaging. These probes have proven to be effective in mapping PD-L1 expression across various mouse tumor models, offering insights into tumor-immune interactions. This study highlights the potential of AUNP-12-Cy5.5 and AUNP-12-CH1055 for guiding clinical immunotherapy through precise patient stratification and dynamic monitoring, supporting the shift toward molecular imaging for personalized cancer care.

Intravoxel incoherent motion imaging to assess the acute effects of moderate-intensity continuous training and high-intensity interval training on thigh muscles.

This study investigated the use of intravoxel incoherent motion imaging (IVIM) to compare skeletal muscle perfusion during and after high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) to determine the impact on fat oxidation outcomes. Twenty overweight volunteers were recruited for the study. Each participant received one HIIT intervention and one MICT intervention using a cycling ergometer. Participants underwent a magnetic resonance imaging scan before, immediately after, and 1 and 2 h after each intervention. The IVIM parameters (D, fD*) of the rectus femoris, vastus lateralis, and biceps femoris long head were obtained. Changes in IVIM parameters of these muscles after both exercise interventions were compared using a two-factor repeated measures analysis of variance. In the rectus femoris, the fD* increased immediately after exercise intervention (d = 0.69 × 10-3  mm2 /s, p < 0.0083) and 2 h after exercise intervention (d = 0.64 × 10-3  mm2 /s, p < 0.0083) compared with before exercise. The increase in the fD* in the HIIT group was greater than that in the MICT group (d = 0.32, p = 0.023). In the vastus lateralis, the fD* increased immediately after the exercise intervention (d = 0.53 × 10-3  mm2 /s, p < 0.001) and returned to the pre-exercise level 1 h after exercising. The increase in the fD* in the HIIT group was lower than that in the MICT group (d = -0.21, p = 0.015). For the biceps femoris long head, the fD* was not significantly different between the two exercise interventions before and after exercise. Furthermore, the fD* 60 min after the HIIT intervention correlated with maximal oxygen consumption (VO2max), whereas fD* immediately after the MICT intervention correlated with VO2max. In summary, IVIM parameters can be used to evaluate differences in muscle perfusion between HIIT and MICT, and show a correlation with VO2max.

Magnetic-optical dual-modality imaging monitoring chemotherapy efficacy of pancreatic ductal adenocarcinoma with a low-dose fibronectin-targeting Gd-based contrast agent.

PURPOSE: Pancreatic ductal adenocarcinoma (PDAC) is a lethal hypovascular tumor surrounded by dense fibrosis. Albumin-bound paclitaxel and gemcitabine (AG) chemotherapy is the mainstay of PDAC treatment through depleting peritumoral fibrosis and killing tumor cells; however, it remains challenging due to the lack of a noninvasive imaging method evaluating fibrotic changes during AG chemotherapy. In this study, we developed a dual-modality imaging platform that enables noninvasive, dynamic, and quantitative assessment of chemotherapy-induced fibrotic changes through near-infrared fluorescence molecular imaging (FMI) and magnetic resonance imaging (MRI) using an extradomain B fibronectin (EDB-FN)-targeted imaging probe (ZD2-Gd-DOTA-Cy7). METHODS: The ZD2-Gd-DOTA-Cy7 probe was constructed by conjugating a peptide (Cys-TVRTSAD) to Gd-DOTA and the near-infrared dye Cy7. PDAC murine xenograft models were intravenously injected with ZD2-Gd-DOTA-Cy7 at a Gd concentration of 0.05 mmol/kg or free Cy7 and Gd-DOTA as control. The normalized tumor background ratio (TBR) on FMI and the T1 reduction ratio on MRI were quantitatively analyzed. For models receiving AG chemotherapy or saline, MRI/FMI was performed before and after treatment. Histological analyses were performed for validation. RESULTS: The ZD2-Gd-DOTA-Cy7 concentration showed a linear correlation with the fluorescence intensity and T1 relaxation time in vitro. The optimal imaging time was 30 min after injection of the ZD2-Gd-DOTA-Cy7 (0.05 mmol/kg), only half of the clinic dosage of gadolinium. Additionally, ZD2-Gd-DOTA-Cy7 generated a 1.44-fold and 1.90-fold robust contrast enhancement compared with Cy7 (P < 0.05) and Gd-DOTA (P < 0.05), respectively. For AG chemotherapy monitoring, the T1 reduction ratio and normalized TBR in the fibrotic tumor areas were significantly increased by 1.99-fold (P < 0.05) and 1.78-fold (P < 0.05), respectively, in the control group compared with those in the AG group. CONCLUSION: MRI/FMI with a low dose of ZD2-Gd-DOTA-Cy7 enables sensitive imaging of PDAC and the quantitative assessment of fibrotic changes during AG chemotherapy, which shows potential clinical applications for precise diagnosis, post-treatment monitoring, and disease management.

Tomoelastography and Pancreatic Extracellular Volume Fraction Derived From MRI for Predicting Clinically Relevant Postoperative Pancreatic Fistula.

BACKGROUND: Pancreatic stiffness and extracellular volume fraction (ECV) are potential imaging biomarkers for pancreatic fibrosis. Clinically relevant postoperative fistula (CR-POPF) is one of the most severe complications after pancreaticoduodenectomy. Which imaging biomarker performs better for predicting the risk of CR-POPF remains unknown. PURPOSE: To evaluate the diagnostic performance of ECV and tomoelastography-derived pancreatic stiffness for predicting the risk of CR-POPF in patients undergoing pancreaticoduodenectomy. STUDY TYPE: Prospective. POPULATION: Eighty patients who underwent multiparametric pancreatic MRI before pancreaticoduodenectomy, among whom 16 developed CR-POPF and 64 did not. FIELD STRENGTH/SEQUENCE: 3 T/tomoelastography and precontrast and postcontrast T1 mapping of the pancreas. ASSESSMENT: Pancreatic stiffness was measured on the tomographic c-map, and pancreatic ECV was calculated from precontrast and postcontrast T1 maps. Pancreatic stiffness and ECV were compared with histological fibrosis grading (F0-F3). The optimal cutoff values for predicting CR-POPF were determined, and the correlation between CR-POPF and imaging parameters was evaluated. STATISTICAL TESTS: The Spearman's rank correlation and multivariate linear regression analysis was conducted. The receiver operating characteristic curve analysis and logistic regression analysis was performed. A double-sided P < 0.05 indicated a statistically significant difference. RESULTS: Pancreatic stiffness and ECV both showed a significantly positive correlation with histological pancreatic fibrosis (r = 0.73 and 0.56, respectively). Patients with advanced pancreatic fibrosis had significantly higher pancreatic stiffness and ECV compared to those with no/mild fibrosis. Pancreatic stiffness and ECV were also correlated with each other (r = 0.58). Lower pancreatic stiffness (<1.38 m/sec), lower ECV (<0.28), nondilated main pancreatic duct (<3 mm) and pathological diagnosis other than pancreatic ductal adenocarcinoma were associated with higher risk of CR-POPF at univariate analysis, and pancreatic stiffness was independently associated with CR-POPF at multivariate analysis (odds ratio: 18.59, 95% confidence interval: 4.45, 77.69). DATA CONCLUSION: Pancreatic stiffness and ECV were associated with histological fibrosis grading, and pancreatic stiffness was an independent predictor for CR-POPF. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 5.

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.

CT surveillance for type 1 autoimmune pancreatitis: cumulative radiation dose and diagnostic performance for disease relapse.

OBJECTIVES: Long-term follow-up is essential for type 1 autoimmune pancreatitis (AIP) patients due to high relapse rates. The cumulative radiation dose from repeated CT scans during follow-up should not be ignored. We aim to investigate the cumulative radiation dose in AIP patients undergoing CT surveillance and the diagnostic performance of CT in detecting disease relapse. The diagnostic performance of MRI from a secondary cohort during the same period was also investigated. METHODS: This retrospective single-institutional study included 247 type 1 AIP patients with one or more follow-up CT scans, and 120 patients with MR follow-ups. Four metrics were utilized to report the radiation dose, including the volume computed tomography dose index, the dose length product, size-specific dose estimate and effective dose. The diagnostic performance for AIP relapse was assessed, taking the final clinical diagnosis in retrospect as the reference standard. RESULTS: With a median 2.3-year follow-up period, AIP patients followed up with CT exhibited a median cumulative radiation dose of 37.5 mSv. 11.3% of patients have accumulated doses exceeding 100 mSv. For the 169 patients followed over a year, 30.8% sustained an average annual radiation dose surpassing 20 mSv. The sensitivity/specificity/accuracy of CT for detecting abdominal organ relapse was 64.1%/99.6%/97.0%. For AIP patients followed up with MRI, the sensitivity for detecting disease relapse was 90.5%. CONCLUSION: Considering the accumulation of radiation dose in AIP patients and the insufficient sensitivity in detecting disease relapse with CT, safer and more sensitive imaging follow-up strategies should be explored. KEY POINTS: Question CT, as the primary imaging modality for autoimmune pancreatitis (AIP) follow-up, raises concerns regarding radiation exposure and lacks reported diagnostic performance in detecting AIP relapse. Findings CT in AIP follow-up causes significant cumulative radiation exposure and exhibits insufficient sensitivity in relapse detection. Clinical relevance Type 1 AIP necessitates long-term imaging follow-up, yet current guidelines lack consensus regarding the prioritization of CT or MRI for such follow-up. CT is widely used but has radiation concerns and limited sensitivity, calling for safer, efficient strategies.

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.

[Advances in Imaging-Based Evaluation of Solid Tumors Treated With Immune Checkpoint Inhibitors].

Immune checkpoint inhibitors have shown remarkable benefits in the treatment of solid tumors,while the occurrence of atypical response patterns and immune-related adverse events during treatment challenges the accuracy of therapeutic evaluation.Medical imaging is crucial for the evaluation of immunotherapy.It enables the assessment of treatment efficacy via both morphological and functional ways and offers unique a predictive value when being combined with artificial intelligence.Here we review the recent research progress in imaging-based evaluation of solid tumors treated with immune checkpoint inhibitors.

Treatment Response Assessment in Multiple Myeloma: Histogram Analysis of Total Tumor Apparent Diffusion Coefficient based on Whole-body Diffusion-weighted MR Imaging.

BACKGROUND: The International Myeloma Working Group (IMWG) consensus criteria for response assessment in multiple myeloma (MM) has methodological limitations. Whole-body diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) histogram analysis may be complementary to response assessment of MM. PURPOSE: To explore the role of histogram analysis of the ADC based on the total tumor volume (ttADC) in response assessment in patients with newly diagnosed MM (NDMM). STUDY TYPE: Retrospective. POPULATION: Thirty-six patients with NDMM. FIELD STRENGTH/SEQUENCE: 3.0T/single-shot DWI echo planar imaging (EPI) sequence with an integrated slice-by-slice shimming (iShim) technique. ASSESSMENT: Baseline (median: 1 day before treatment) and post-treatment (median: five cycles of therapy) whole-body DWI were analyzed. A region of interest (ROI) containing lesions on every section of baseline image was drawn to derive the per-patient total tumor data. Post-treatment image analysis was based on the same ROI as the corresponding baseline. Histogram metrics were extracted from both ROIs. Patients were categorized into the very good partial response or better (VGPR+) group and the less than VGPR group per the IMWG response criteria for response assessment. Progression-free survival (PFS) was also calculated. STATISTICAL TESTS: Mann-Whitney test and Fisher's exact or Chi-squared tests, Receiver operating characteristic (ROC) analysis and DeLong test, Kaplan-Meier analysis and Cox proportional hazards model. A two-tailed P-value <0.05 was considered statistically significant. RESULTS: Thirty patients were categorized into the VGPR+ group and six into the less than VGPR group. The ttADC histogram changes between post-treatment and baseline metrics (ΔttADC) revealed significant differences in all percentile values between the VGPR+ and less than VGPR groups. For distinguishing VGPR+, ΔttADC_5th percentile had the largest area under the curve (AUC) (0.950, 95% CI 0.821-0.995). Patients with lower ΔttADC_5th percentile values (cutoff point, 188.193) showed significantly longer PFS (HR = 34.911, 95% CI 6.392-190.677). DATA CONCLUSION: ttADC histogram may facilitate response assessment in patients with NDMM. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 4.

A single-center experience on endoscopic ultrasonography-guided ethanol ablation of insulinomas.

BACKGROUND/OBJECTIVES: As the most frequent functional pancreatic neuroendocrine tumor, insulinomas may cause a plethora of symptoms and severe impairment in the living of patients by endogenous hyperinsulinemia and subsequent hypoglycemia. Surgery has been regarded as the first choice although a high risk of complications. Ethanol ablation is a promising non-surgical option that could achieve tumor shrinking in a short-term period. But the impact of symptom control and the long-term efficacy lack sufficient and good-quality evidence. METHODS: A total number of 14 endoscopic ultrasonography-guided ethanol ablations were performed in 9 patients between September 2016 and September 2018 in Peking Union Medical College Hospital. The data were collected and prospectively analyzed. RESULTS: The follow-up duration ranged from 21 to 1567 days in 9 patients, with a median of 994 days. 4 patients were free from relapse during a median follow-up of 1108 days (range: 994-1567 days). In 5 patients who suffered relapses, the median duration with symptom relief after the first ablation was 128 days (range: 13-393 days). If only repeated ablation was taken into consideration, the median duration with symptom relief was 26 days (range: 1-516 days). No complications happened during the procedures. The severe complication rate after the first ablation was 0.0% (0/9), compared to 7.14% (1/14) if each procedure was counted separately. The only severe complication documented was acute pancreatitis which was completely relieved after symptomatic treatment. CONCLUSIONS: For patients who are not suitable for surgical resections, endoscopic ultrasonography-guided ethanol ablation of insulinomas could be an effective and safe alternative to relieve symptoms of hypoglycemia.

Presumed radiological diagnosis of solid pseudopapillary tumors: do we really know what we are watching?

OBJECTIVES: Little is known about the clinicians' ability to ascertain the identity of a pancreatic lesion as solid pseudopapillary tumors (SPT)preoperatively. We led this retrospective study to figure out the disease spectrum that mimic SPT, the key features of SPT and the accuracy of CT and MRI in characterizing them. METHODS: Radiological and clinical database at a tertiary pancreatic disease center (Peking Union Medical College Hospital) was searched for patients who received CT or MRI with a presumed radiological diagnosis of SPT. Those patients' clinical information and final pathological diagnosis were collected. RESULTS: During 2018.10-2021.12, 200 patients had a presumed radiological diagnosis of SPT, and 132 of them had unambiguous pathological diagnosis. SPT were confirmed in only 63.6% (84/132), while the others had a variety of neoplastic and nonneoplastic lesions, including pancreatic neuroendocrine tumors (n = 15), pseudocysts (n = 4), mucinous cystic neoplasms (n = 4), serous cystadenomas (n = 3), neural sheath tumors (n = 3), lymphoepithelial cysts (n = 2), and several very rare pathologies (n = 17). Of note, 11.4% (15/132) of those were benign or nonneoplastic lesions, while 6.8% (9/132) were neoplasms with highly aggressive nature, or pancreatic metastases, which require systematic evaluation and staging instead of upfront surgery. Retrospective radiological analysis based on key imaging features, clinical history and laboratory findings had an improved diagnostic accuracy of 78.5% with CT and 77.8% with MRI. CONCLUSIONS: There is a broad disease spectrum mimicking SPT at CT and MRI. Key imaging features, clinical information and laboratory findings must be integrated to improve the diagnostic accuracy.

CT-based radiomics nomogram for prediction of survival after transarterial chemoembolization with drug-eluting beads in patients with hepatocellular carcinoma and portal vein tumor thrombus.

OBJECTIVES: To develop and validate a CT-based radiomics model for the prediction of the overall survival (OS) of patients with hepatocellular carcinoma (HCC) and portal vein tumor thrombus (PVTT) treated with drug-eluting beads transarterial chemoembolization (DEB-TACE). METHODS: Patients were retrospectively enrolled from two institutions for the constitution of training (n = 69) and validation (n = 31) cohorts with a median follow-up of 15 months. A total of 396 radiomics features were extracted from each baseline CT image. Features selected by variable importance and minimal depth were used for random survival forest model construction. The performance of the model was assessed using the concordance index (C-index), calibration curves, integrated discrimination index (IDI), net reclassification index (NRI), and decision curve analysis. RESULTS: Type of PVTT and tumor number were proved to be significant clinical indicators for OS. Arterial phase images were used to extract radiomics features. Three radiomics features were selected for model construction. The C-index for the radiomics model was 0.759 in the training cohort and 0.730 in the validation cohort. To improve the predictive performance, clinical indicators were integrated into the radiomics model to form a combined model with a C-index of 0.814 in the training cohort and 0.792 in the validation cohort. The IDI was significant in both cohorts for the combined model versus the radiomics model in predicting 12-month OS. CONCLUSIONS: Type of PVTT and tumor number affected the OS of HCC patients with PVTT treated with DEB-TACE. Moreover, the combined clinical-radiomics model had a satisfactory performance. CLINICAL RELEVANCE STATEMENT: A CT-based radiomics nomogram, which consisted of 3 radiomics features and 2 clinical indicators, was recommended to predict 12-month overall survival of patients with hepatocellular carcinoma and portal vein tumor thrombus initially treated with drug-eluting beads transarterial chemoembolization. KEY POINTS: • Type of portal vein tumor thrombus and tumor number were significant predictors of the OS. • Integrated discrimination index and net reclassification index provided a quantitative evaluation of the incremental impact added by new indicators for the radiomics model. • A nomogram based on a radiomics signature and clinical indicators showed satisfactory performance in predicting OS after DEB-TACE.

Image quality comparison of lower extremity CTA between CT routine reconstruction algorithms and deep learning reconstruction.

BACKGROUND: To evaluate the image quality of lower extremity computed tomography angiography (CTA) with deep learning-based reconstruction (DLR) compared to model-based iterative reconstruction (MBIR), hybrid-iterative reconstruction (HIR), and filtered back projection (FBP). METHODS: Fifty patients (38 males, average age 59.8 ± 19.2 years) who underwent lower extremity CTA between January and May 2021 were included. Images were reconstructed with DLR, MBIR, HIR, and FBP. The standard deviation (SD), contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR), noise power spectrum (NPS) curves, and the blur effect, were calculated. The subjective image quality was independently evaluated by two radiologists. The diagnostic accuracy of DLR, MBIR, HIR, and FBP reconstruction algorithms was calculated. RESULTS: The CNR and SNR were significantly higher in DLR images than in the other three reconstruction algorithms, and the SD was significantly lower in DLR images of the soft tissues. The noise magnitude was the lowest with DLR. The NPS average spatial frequency (fav) values were higher using DLR than HIR. For blur effect evaluation, DLR and FBP were similar for soft tissues and the popliteal artery, which was better than HIR and worse than MBIR. In the aorta and femoral arteries, the blur effect of DLR was worse than MBIR and FBP and better than HIR. The subjective image quality score of DLR was the highest. The sensitivity and specificity of the lower extremity CTA with DLR were the highest in the four reconstruction algorithms with 98.4% and 97.2%, respectively. CONCLUSIONS: Compared to the other three reconstruction algorithms, DLR showed better objective and subjective image quality. The blur effect of the DLR was better than that of the HIR. The diagnostic accuracy of lower extremity CTA with DLR was the best among the four reconstruction algorithms.

Simulation video: a tool to evaluate communications skills in radiologist residents.

BACKGROUND: Effective communication is a crucial component of radiology resident training, and many different aspects need to be explored when teaching and evaluating communication skills. To ensure that radiology residents' communication skill levels can be measured accurately, a standardized evaluation tool has been introduced. In twenty hospitals in Beijing, simulation videos have been developed as a way to assess the communication skills of radiology residents during their certification exams, to minimize evaluating biases. This study aims to assess the performance of a simulation video model in evaluating communications skills compared to the standard patient model. METHODS: This is a retrospective observational study. The performance of standard patient and simulation video models was evaluated through an eight-year examination of communication skills in radiology residents. From 2014 to 2021, communications skill tests were administered to 1003 radiology residents in 20 hospitals in Beijing. The standardized patient (SP) model was applied in 2014, and simulation videos were used from 2015 to 2021. The difficulty and discrimination radio of the tests were evaluated. The subjective survey for candidates on two models of communication skills evaluation was performed and analyzed. RESULTS: The simulation video model evaluation demonstrated stable difficulty (ranging from 0.92 to 0.98) and discrimination ratio (ranging from 0.37 to 0.49), except for minor exceptions of discrimination in 2019 (0.58) and 2020 (0.20). Furthermore, the Kruskal-Wallis H test revealed no significant differences in average scores between 2016 (93.9 ± 4.6) and 2018 (94.5 ± 4.2), 2016 and 2019 (97.3 ± 3.9), 2017 (97.0 ± 5.6) and 2019, 2017 and 2020 (97.7 ± 4.7), as well as 2019 and 2020 exams (all p ≥ 0.05). In addition, candidates who responded to the survey preferred the simulation video model (with a 77.2% response rate), with 62.7% choosing it over the SP model for communication skills evaluation. CONCLUSION: The simulation video demonstrated a stable and better acceptable construct for assessing radiology residents' communication skills.

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.

A systematic review of prognosis predictive role of radiomics in pancreatic cancer: heterogeneity markers or statistical tricks?

OBJECTIVES: We aimed to systematically evaluate the prognostic prediction accuracy of radiomics features extracted from pre-treatment imaging in patients with pancreatic ductal adenocarcinoma (PDAC). METHODS: Radiomics literature on overall survival (OS) prediction of PDAC were all included in this systematic review. A further meta-analysis was performed on the effect size of first-order entropy. Methodological quality and risk of bias of the included studies were assessed by the radiomics quality score (RQS) and prediction model risk of bias assessment tool (PROBAST). RESULTS: Twenty-three studies were finally identified in this review. Two (8.7%) studies compared prognosis prediction ability between radiomics model and TNM staging model by C-index, and both showed a better performance of the radiomics. Twenty-one (91.3%) studies reported significant predictive values of radiomics features. Nine (39.1%) studies were included in the meta-analysis, and it showed a significant correlation between first-order entropy and OS (HR 1.66, 95%CI 1.18-2.34). RQS assessment revealed validation was only performed in 5 (21.7%) studies on internal datasets and 2 (8.7%) studies on external datasets. PROBAST showed that 22 (95.7%) studies have a high risk of bias in participants because of the retrospective study design. CONCLUSION: First-order entropy was significantly associated with OS and might improve the accuracy of PDAC prognosis prediction. Existing studies were poorly validated, and it should be noted in future studies. Modification of PROBAST for radiomics studies is necessary since the strict requirements of prospective study design may not be applicable to the demand for a large sample size in the model construction stage. KEY POINTS: • Radiomics based on the primary lesion holds great potential for prognosis prediction. First-order entropy was significantly associated with the overall survival of PDAC and might improve the accuracy of current PDAC prognosis prediction. • We strongly recommend that at least an internal validation should be conducted in any radiomics study. Attention should be paid to the complex relationships between radiomics features. • Due to the close relationship between radiomics and big data, the strict requirement of prospective study design in PROABST may not be appropriate for radiomics studies. A balance between study types and sample sizes for radiomics studies needs to be found in the model construction stage.

Clinical effectiveness of contrast medium injection protocols for 80-kV coronary and craniocervical CT angiography-a prospective multicenter observational study.

BACKGROUND AND OBJECTIVE: Decreasing X-ray tube voltage is an effective way to reduce radiation and contrast dose, especially in non-obese patients. The current study focuses on CTA in non-obese patients to evaluate image quality and feasibility of 80-kV acquisition protocols with varying iodine delivery rates (IDR) and contrast concentrations in routine clinical practice. METHODS: A prospective observational study in patients ≥ 18 years and ≤ 90 kg referred for coronary or craniocervical CTA at 10 centers in China (ClinicalTrials.gov: NCT02840903). Patients were divided into four groups: a standard 100-kV protocol (370 mgI/ml, IDR 1.48 gI/s), and three 80-kV protocols (370 mgI/ml, IDR 1.2 gI/s; 300 mgI/ml, IDR 1.2 gI/s; 300 mgI/ml, IDR 0.96gI/s). The primary outcome was contrast opacification of target vascular segments. Secondary outcomes were image quality (contrast-to-noise ratio, signal-to-noise ratio, visual image quality, and diagnostic confidence assessment), radiation, and iodine dose. RESULTS: From July 2016 to July 2017, 1213 patients were enrolled: 614 coronary and 599 craniocervical CTA. The mean contrast opacification was ≥ 300 HU for 80-kV 1.2 gI/s IDR scanned segments; IDR 0.96 gI/s led to lower opacification. Image quality and diagnostic confidence were fair to excellent (≥ 98% of images), despite lower contrast-to-noise ratios and signal-to-noise ratios in 80-kV images. Compared to the standard protocol, 80-kV protocols led to 44-52% radiation dose reductions (p < 0.001) and 19% iodine dose reductions (p < 0.001). CONCLUSION: Eighty-kilovolt 1.2 gI/s IDR protocols can be recommended for coronary and craniocervical CTA in non-obese patients, reducing radiation and iodine dose without compromising image quality. KEY POINTS: • Using low-voltage scanning CTA protocols, in which tube voltage and iodine delivery rate are reduced proportionally (voltage: 80 kV, IDR: 1.2 gI/s), reduces radiation and contrast dose without compromising image quality in routine clinical practice. • Reducing iodine delivery rate beyond direct proportionality to tube voltage is not beneficial.

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.