Insights into Imaging最新文献

Objectives: Waiting for postoperative pathologic confirmation of visceral pleural invasion (VPI) may delay treatment decisions. This study aimed to develop a contrast-enhanced CT-based radiomics model for preoperative prediction of VPI in early-stage non-small cell lung cancer (NSCLC).

Materials and methods: We retrospectively enrolled 523 surgically resected NSCLC patients (195 with VPI, 328 without VPI) with clinically staged IA based on preoperative imaging between December 2019 and June 2022. Patients were randomly divided into training, validation, and testing sets at a ratio of 5:2:3. For each patient, 13 CT features were recorded, including the types I-V tumor relationships to the pleura. Regions of interest (ROIs) were segmented semi-automatically using deep learning. Least absolute shrinkage and selection operator (LASSO) regression was applied to select key radiomics features. Three models were developed: a CT-feature model, a radiomics model, and a combined model. The performance and clinical utility of these models were evaluated using the area under the curve (AUC) and decision curve analysis.

Results: The tumor relationship to the pleura, density, maximum diameter, and spiculation were selected to construct the CT-feature model. A total of 10 optimal features formed the radiomics model. The radiomics model achieved an AUC of 0.812 in the testing set, outperforming the CT-feature model (0.714). Furthermore, the combined model showed a slightly higher AUC (0.825) compared to the radiomics model.

Conclusions: The radiomics model demonstrated satisfactory performance for predicting VPI in early-stage NSCLC, outperforming the CT-feature model. The integration of radiomics and CT features may provide enhanced predictive value.

Critical relevance statement: This study constructed a contrast-enhanced CT-based radiomics model with promising performance for the preoperative prediction of VPI, which aims to guide treatment planning for early-stage NSCLC.

Key points: VPI affects the tumor-node-metastasis (TNM) staging of tumors and subsequent treatment strategies. The radiomics model outperformed the CT-feature model in predicting VPI. The contrast-enhanced CT-based radiomics model may be valuable for optimizing clinical decision-making.

Objectives: Androgen deprivation therapy (ADT) is essential for treating prostate cancer (PCa) but is limited by tumor heterogeneity. This study develops a non-invasive multiparametric Magnetic Resonance Imaging (mpMRI) radiomics framework to predict ADT response and improve risk stratification.

Materials and methods: A cohort of 550 ADT-treated PCa patients from three centers was analyzed. Patients were randomly divided into training (n = 270) and internal validation (n = 115) cohorts. An external test cohort (n = 165) from Centers 2 and 3 was used for generalizability. Radiomics models based on T2-weighted and diffusion-weighted imaging (DWI), habitat radiomics, and a 3D Vision Transformer (ViT) deep learning model were developed. Ensemble integration of these models was performed, with SHapley Additive exPlanations (SHAP) used for interpretability. Predictive performance was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC).

Results: Habitat radiomics outperformed conventional radiomics in Gleason score stratification. For predicting ADT treatment efficacy, the radiomics model achieved AUCs of 0.969 (training), 0.767 (internal validation), and 0.771 (test). The habitat model showed AUCs of 0.987, 0.849, and 0.820, while the ViT model achieved AUCs of 0.831, 0.805, and 0.796. The ensemble model reached the highest AUC of 0.886. SHAP analysis shows that the ViT model contributes most to the combined model, followed by the habitat model, with the radiomics model contributing the least.

Conclusion: mpMRI-based habitat radiomics enables precise risk stratification in PCa. Integrated with conventional radiomics and deep learning, it forms a robust framework for predicting ADT response and guiding personalized treatment.

Critical relevance statement: This study demonstrates that integrating habitat radiomics with deep learning improves the prediction of androgen deprivation therapy response in PCa, advancing personalized radiological decision-making through interpretable multi-model analysis of tumor microenvironment heterogeneity.

Key points: Multi-model integration of habitat radiomics and 3D Vision Transformer achieves superior prediction for ADT response compared to conventional methods. Habitat radiomics outperforms traditional radiomics in Gleason score stratification. SHAP analysis provides clinical interpretability, identifying key model linked to ADT outcomes for actionable insights.

Objectives: To propose an easy-to-use binary scoring system for background signal intensity changes in prostate MRI that may affect diagnostic image interpretation and to evaluate its impact on cancer detection.

Materials and methods: This retrospective single-center study included 200 patients. Four readers independently assigned background scores of A or B according to the proposed scoring system and assessed the presence or absence of cancer. Light's kappa was used to evaluate inter-reader agreement on the score and on the presence of clinically significant prostate cancer in dependence of the score. Sensitivity and specificity in detecting clinically significant cancer were assessed relative to histology as the gold standard.

Results: Due to suboptimal image quality according to the PI-QUAL score, 45 patients were secondarily excluded. Inter-reader agreement on the score was substantial (kappa = 0.62, 95% CI = 0.54-0.71). Inter-reader agreement on the presence of cancer was higher for a background score A (kappa = 0.49, 95% CI = 0.38-0.61) than B (kappa = 0.34, 95% CI = 0.20-0.51). Sensitivity in detecting cancer was high regardless of the background score (86.61% and 89.42% for scores A and B), while specificity decreased markedly in readers with little experience (53.47% and 43.75% for scores A and B), potentially increasing false positives.

Conclusion: After further validation, the easy-to-use binary background score could enable routine evaluation of normal changes in the peripheral zone, identifying cases with increased false-positive risk among inexperienced readers.

Critical relevance statement: The easy-to-use binary background score for daily clinical routine allows the communication of potential diagnostic uncertainties in mpMRI image interpretation of the prostate that arise due to normal changes in the peripheral zone, especially for less experienced readers.

Key points: An easy-to-use binary scoring system for addressing background signal intensity changes in the prostate is proposed for MRI interpretation. Inter-reader agreement of the score was substantial, and agreement between readers regarding the presence or absence of cancer was higher for a background score of A than B. The background score could be used to communicate a potential diagnostic uncertainty related to the normal change in the peripheral zone, particularly for less experienced readers.

Objectives: In this retrospective study, we aimed to assess the predictive value of the Carotid Plaque-RADS (Reporting and Data System) for coronary functional stenosis in candidates for carotid revascularization, using high-resolution magnetic resonance imaging (HR-MRI) coupled with computed tomography-derived fractional flow reserve (CT-FFR).

Materials and methods: A retrospective analysis was performed on data of 101 patients with carotid atherosclerosis who underwent HR-MRI for Carotid Plaque evaluation, and CT-FFR for coronary assessment was conducted. Patients were divided into two groups based on a CT-FFR threshold of ≤ 0.80. Logistic regression, correlation analyses, and receiver operating characteristic curve analyses were used to identify predictors of coronary functional stenosis.

Results: In the functional stenosis group (n = 76), both plaque volume and Carotid Plaque-RADS categories had higher values than those observed in the non-functional group (n = 25). Univariate analysis showed that Carotid Plaque-RADS, Carotid Plaque volume, and hypertension were associated with functional stenosis. After adjustment, Carotid Plaque-RADS remained an independent predictor (odds ratio: 2.35, p < 0.01) and demonstrated the strongest correlation (ρ = 0.51, p < 0.01). It also demonstrated good diagnostic performance (area under the curve [AUC]: 0.81; sensitivity: 85%; specificity: 68%) and favorable clinical utility on decision curve analysis. In an exploratory analysis, Carotid Plaque-RADS was also moderately correlated with CAD-RADS (ρ = 0.37, p < 0.01) and predicted CAD-RADS ≥ 3 with good discrimination (AUC: 0.72).

Conclusion: Carotid Plaque-RADS is an independent, noninvasive predictor of coronary functional stenosis in candidates for carotid revascularization.

Critical relevance statement: Carotid Plaque-RADS provides a noninvasive imaging-based tool that independently predicts coronary functional stenosis, thereby enhancing preoperative coronary risk stratification and supporting integrated cardiovascular management in candidates for carotid revascularization.

Key points: Carotid revascularization candidates face high coronary risk. Carotid Plaque-RADS independently predicts coronary functional stenosis. Carotid Plaque-RADS enhances preoperative coronary risk stratification.

Oncologic imaging plays a critical role in the diagnosis, staging, treatment planning, and follow-up of cancer patients. Recent advancements in computed tomography, particularly the development of photon-counting detector CT (PCCT), have introduced new opportunities for improving diagnostic accuracy and tissue characterization, while reducing contrast agent usage and radiation exposure. By offering ultra-high spatial resolution, enhanced contrast-to-noise ratio, and intrinsic spectral capabilities, PCCT addresses many limitations of conventional energy-integrating detector CT (EID-CT) and unlocks new possibilities for quantitative imaging. This review explores the emerging applications of PCCT across various tumor types-including thoracic, abdominal, and musculoskeletal malignancies-highlighting its potential to improve cancer imaging and patient care. CRITICAL RELEVANCE STATEMENT: Photon-counting detector CT (PCCT) offers several advantages in oncologic imaging, providing superior spatial resolution, spectral imaging capabilities, and reduced radiation dose, enhancing lesion characterization and precise treatment planning, making PCCT a valuable tool for personalized cancer care. KEY POINTS: CT has a crucial role in oncological imaging, supporting diagnosis, staging, treatment planning and follow-up. Compared to EID-CT, PCCT offers higher spatial and contrast resolution, reduces artifacts and image noise and provides spectral data enabling quantitative assessment. PCCT may improve cancer imaging by increasing diagnostic accuracy, with better detection of small lesions, enhanced soft tissue contrast, and enabling quantitative iodine uptake evaluation.

Objectives: To evaluate patient acceptance and feedback regarding supplemental imaging modalities: automated whole-breast ultrasound (ABUS), contrast-enhanced mammography (CEM), and abbreviated breast MRI (AB-MRI) within the BRAID (Breast Screening: Risk Adaptive Imaging for Density) trial.

Materials and methods: An adapted Testing Morbidities Index questionnaire was utilised to capture participant experiences and perceptions (January-April 2024) related to AB-MRI, ABUS and CEM. Likert-scale questions assessed discomfort, anxiety, and overall satisfaction for each imaging modality, while thematic analysis was applied to free-text patient feedback. Additionally, reasons for withdrawal were recorded for each modality.

Results: Among 159 women providing feedback, 57/159 (35.8%) underwent ABUS, 52/159 (32.7%) CEM, and 50/159 (31.5%) AB-MRI. Acceptability of ABUS, CEM and AB-MRI was rated similarly to mammography by 71/159 (64.8%) of these respondents, with 72/159 (45.3%) considering them superior. Mild-to-moderate discomfort due to breast compression was reported for ABUS and CEM, whereas AB-MRI resulted in the least discomfort. Pre-procedural anxiety was observed across all imaging modalities, particularly with contrast-enhanced techniques; however, experiences were generally well-tolerated. Effective communication and pre-test information reduced anxiety levels, with most participants willing to repeat the procedures. 151/984 (15.3%) withdrawals in BRAID were due to adverse patient experiences, with contrast-enhanced techniques accounting for most of these withdrawals (CEM: 69/151, 45.7%; AB-MRI: 66/151, 43.7%; ABUS: 12/151, 7.9%). The main reasons for withdrawal were unhappiness with the allocated imaging arm and discomfort or anxiety during the procedure.

Conclusion: Supplemental imaging modalities are generally well-accepted by patients with benefit throughout gained by clear communication and preparedness.

Critical relevance statement: Feedback from a subgroup of women participating in the BRAID trial shows that supplemental imaging alongside routine screening is well-accepted. Clear communication and empathetic care further improve acceptance, supporting a shift toward personalised breast cancer screening for women with dense breasts.

Key points: Understanding women's imaging experiences is essential for optimising breast screening practices. Acceptability of supplemental imaging was rated similar to or better than mammography by most participants. Clear, empathetic communication reduced anxiety and improved experience with contrast-enhanced imaging.

Prostate cancer is the most commonly diagnosed cancer among men in 112 countries, accounting for approximately 15% of all cancer cases. Whilst the 5-year survival rate for localised disease exceeds 90%, there is a significant drop to 50% if metastases are present. Following the VISION and TheraP trials, ¹⁷⁷Lu-PSMA-therapy was approved for treatment of metastatic castrate resistant prostate cancer by the FDA and EMA 2022. Patient selection for ¹⁷⁷Lu-PSMA-therapy is now relatively well defined, guided by PSMA-PET/CT criteria established in pivotal trials. Nevertheless, clinical consensus on appropriate criteria is still evolving, and additional imaging modalities such as ¹⁸F-FDG PET, post-therapy SPECT/CT, or emerging techniques such as whole-body diffusion-weighted MRI may serve as valuable adjuncts to identify PSMA-negative or treatment-resistant disease that may not be apparent on PSMA-PET/CT alone. This review examines the current evidence on imaging biomarkers and complementary diagnostic techniques used for patient selection, treatment monitoring, and response assessment in [¹⁷⁷Lu]Lu-PSMA-617 therapy for metastatic castrate resistant prostate cancer. Baseline imaging biomarkers on PSMA-PET/CT, such as mean standardised uptake value (SUV_mean), PSMA-avid total tumour volume, and inter-lesional PSMA heterogeneity, have shown promise in predicting treatment response and assessing outcomes. Additionally, statistical prognostic models have been developed to predict treatment efficacy, though further validation is required. Imaging plays a crucial role and should be considered alongside blood biomarkers, clinic-demographic history, and circulating tumour markers to improve patient selection for ¹⁷⁷Lu-PSMA-therapy. CRITICAL RELEVANCE STATEMENT: PSMA-PET/CT is the established imaging modality for patient selection for ¹⁷⁷Lu-PSMA-therapy, while ¹⁸F-FDG PET, post-therapy SPECT/CT, and emerging techniques such as whole-body diffusion-weighted MRI can be adjunctive for patient selection, response assessment and long-term monitoring. KEY POINTS: PSMA-PET/CT is the mainstay for patient selection for ¹⁷⁷Lu-PSMA-therapy. ¹⁸F-FDG PET, SPECT/CT or whole-body diffusion-weighted MRI could be used as adjuncts. Interim and longitudinal PSMA-PET/CT offer sensitive detection of progression, quantitative biomarkers for response assessment, and standardised frameworks. Advances in AI, radiomics, and standardisation frameworks may refine prognostication, enable personalised dosimetry, and integrate imaging biomarkers into clinical practice, though further validation is required.

Reporting and Data Systems (RADS) aim at standardizing imaging acquisition, interpretation, lexicon, and reporting standards in specific patient populations, facilitating the communication between radiologists and clinicians. While the adoption of RADS has been supported by several studies and guidelines, with some of them endorsed by the American College of Radiology, the clinical adoption of the RADS algorithm remains heterogeneous among general practice radiologists worldwide, being lower in non-academic and young radiologists. This article aims to provide an updated review, aimed at young and general radiologists, of the RADS alphabet, discussing the main applications and imaging criteria with tips for their correct use in clinical practice. The following RADS will be discussed: BI-RADS, Bone-RADS, C-RADS, CAD-RADS, LI-RADS, Lung-RADS, MET-RADS-P, MY-RADS, NI-RADS, Node-RADS, O-RADS, ONCO-RADS, PI-RADS, ST-RADS, TI-RADS, and VI-RADS. CRITICAL RELEVANCE STATEMENT: A comprehensive guide aimed at young and general radiologists featuring all of the major RADS with the objective to foster their implementation in clinical practice, which could be beneficial in a further standardization of the medical reports and in the communication between radiologists and clinicians. KEY POINTS: RADS are outlined to enhance communication efficacy between radiologists and clinicians. Updated overview of RADS frameworks, detailing applications, imaging criteria, and advancements. RADS' implementation remains a challenge, but can be addressed.

Objectives: To assess the correlation between the functional liver imaging score (FLIS) and FibroScan^®-derived fibrosis stage, and to determine whether incorporating parenchymal heterogeneity (FLIS-H) improves its association with fibrosis and clinical scores.

Materials and methods: This retrospective single-centre study included 113 patients who underwent FibroScan^® and hepatocyte-specific contrast-enhanced MRI within a median interval of 4 days. FLIS was calculated, and the parenchymal heterogeneity score was added to FLIS (FLIS-H; range 0-8). Inter-reader agreement was evaluated using a two-way random-effects intraclass correlation coefficient (ICC). Correlations between FLIS/FLIS-H and fibrosis stage/clinical scores (Child-Pugh, MELD, ALBI) were assessed using Spearman's rank correlation. Steiger's z-test and Zou's method were used to compare correlations.

Results: A total of 113 patients (67 men; mean age 56.6 ± 13.5 years) were evaluated. Inter-reader agreement was excellent for FLIS (ICC 0.994; 95% CI: 0.975-1.000), heterogeneity (ICC 0.949; 95% CI: 0.901-0.984), and FLIS-H (ICC 0.974; 95% CI: 0.957-0.989). FLIS showed significant negative correlations with Child-Pugh (ρ = -0.2664, p = 0.0087), ALBI (ρ = -0.3076, p = 0.0022), and fibrosis stage (ρ = -0.3207, p < 0.001). FLIS-H demonstrated stronger correlations with Child-Pugh (ρ = -0.4167, p < 0.001), ALBI (ρ = -0.5243, p < 0.001), MELD (ρ = -0.2360, p = 0.020), and fibrosis stage (ρ = -0.5270, p < 0.001). Steiger's z-test confirmed that correlations were significantly improved with FLIS-H for ALBI (z = -3.03, p = 0.0025), Child-Pugh (z = -2.01, p = 0.045), and fibrosis stage (z = -2.90, p = 0.0038).

Conclusion: FLIS correlates significantly with fibrosis stage and clinical scores. Incorporating parenchymal heterogeneity into FLIS enhances these associations and may provide a superior method for liver assessment.

Critical relevance: This study introduces a modified FLIS version (FLIS-H) that integrates parenchymal heterogeneity and demonstrates superior correlation with elastography-derived fibrosis stages and clinical scoring systems, offering a practical improvement for non-invasive assessment in routine practice.

Key points: FLIS has no reported correlation with elastography-based liver fibrosis staging. Parenchymal heterogeneity is not included as a parameter in the standard FLIS. Integrating heterogeneity improves correlation with fibrosis stage and clinical scores. FLIS-H enables fast, reliable, structure-function liver assessment in clinical radiology.

Objectives: To determine the rate of malignancy upgrade in MRI-only B3 lesions and to identify clinical, imaging, and histological features that can predict upgrade.

Materials and methods: This retrospective single-center study included MRI-only lesions diagnosed as B3 after MRI-guided vacuum-assisted biopsy and excised between January 2007 and March 2023. We calculated upgrade rates for the entire series and for subgroups based on possible risk factors. To analyze variables considered risk factors for upgrade, we used logistic regression, calculating odds ratios (OR) and their 95% confidence intervals (CI).

Results: Of 592 lesions biopsied, 89 (15.03%) were classified as B3. After excluding 30 lesions because excisional specimen results were unavailable, we analyzed 59 lesions in 51 patients. Biopsy classified 15 (25.4%) lesions as pure atypical ductal hyperplasia (ADH), 27 (45.8%) as pure flat epithelial atypia (FEA), 12 (20.3%) as mixed lesions, and 5 (8.5%) as lobular neoplasia. A total of 7 (11.9%) lesions were upgraded to malignancy (71.4% to ductal carcinoma in situ, 14.3% to invasive ductal carcinoma, and 4.3% to invasive lobular carcinoma). Although histological type was not associated with upgrade to malignancy (p = 0.47), 20% of pure ADH and only 3.7% of pure FEA lesions were upgraded. Larger lesion size on MRI was associated with upgrade [6.25% of lesions ≤ 20 mm vs. 36.4% of those > 20 mm, p = 0.02; OR 8.57 (95% CI: 1.57‒46.71) p = 0.01].

Conclusion: Lesion size may predict upgrade in MRI-only B3 lesions independent of histological type; imaging follow-up may suffice for FEA lesions measuring < 20 mm.

Critical relevance statement: Considering lesion size and histological type could help define the management of MRI-only lesions classified as B3 after MRI-guided vacuum-assisted biopsy.

Key points: The management of MRI-only B3 lesions has yet to be established. Lesion size is a relevant factor to consider when deciding clinical management in MRI-only B3 lesions. Conservative management appears to be safe in selected flat epithelial atypia lesions (< 20 mm).