Insights into Imaging最新文献

Objective: To develop and validate a CT-based radiomics model to predict immunotherapy response in unresectable gastric cancer and explore its underlying biological mechanisms.

Materials and methods: This retrospective study included 368 unresectable gastric cancer patients receiving programmed death-1/programmed death ligand-1 (PD-1/PD-L1) inhibitors combined with chemotherapy from two centers. Patients were divided into training (n = 231), internal validation (n = 97), and external validation (n = 40) cohorts. Radiomics model was constructed using portal venous phase CT images, and a radiomics score (Radscore) was calculated for each patient. Five machine learning models incorporating clinical factors and Radscore were developed and compared. The best-performing model was used to construct a nomogram. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA). Immune cell infiltration analysis was performed using data from The Cancer Genome Atlas (TCGA) cohort.

Results: The radiomics signature, comprising 15 selected features, showed good predictive performance across all cohorts: training (AUC = 0.868), internal validation (AUC = 0.816), and external validation (AUC = 0.793). The logistic regression model demonstrated the highest and most consistent performance, with AUC values of 0.886, 0.831, and 0.826, respectively. The developed nomogram showed satisfactory calibration and clinical utility. Immune infiltration analysis revealed significant associations between Radscore and infiltration levels of activated CD4+ memory T cells, regulatory T cells, and CD8+ T cells.

Conclusions: The CT-based radiomics nomogram showed promise for personalizing immunotherapy treatment strategies in unresectable gastric cancer. The association between the Radscore and immune cell infiltration provided insights into its biological basis.

Critical relevance statement: This rigorously validated CT radiomics nomogram critically advances gastric cancer immunotherapy prediction, offering clinical radiology a non-invasive, biologically-informed tool to guide personalized treatment decisions.

Key points: CT radiomics provided a reliable marker for predicting gastric cancer immunotherapy response. The developed Radscore correlated with immune cell infiltration, offering biological insights. A nomogram integrating the Radscore and clinical factors showed robust predictive performance.

Objectives: Lung ultrasound (LUS) has evolved into a widely used tool for the assessment of pleural artifacts (PA), yet the field remains trapped in a terminology Tower of Babel. A proliferation of terms has fragmented the literature, obstructed communication, and hindered progress toward standardization.

Materials and methods: Between January and February 2025, a structured but unsystematic literature review was conducted via Google Scholar to identify terminology used for PA. Twelve distinct terms were identified: A-lines, B-lines, comet-tail artifact, vertical artifact, horizontal artifact, reverberation artifact, mirror-image artifact, ring-down artifact, interstitial syndrome, wet lung, dry lung, and aurora sign. Relevant publications were selected based on predefined keyword combinations and expert review. An analysis of terminology usage was performed for 2000-2025.

Results: The analysis revealed an increase in PA mentions from 751 (2000-2004) to 16,269 (2020-2025), representing more than a twenty-fold increase (+2,066%). Eleven of the twelve PAs showed significant annual growth; only the aurora sign did not demonstrate a consistent increase in usage over time.

Conclusion: The simultaneous increase in nearly all terms for the same physical phenomena reflects a persistent lack of consensus in the literature. While other imaging fields, such as computed tomography, have adopted standardized glossaries like that of the Fleischner Society, LUS remains without a unified terminology. A shared, technology-independent vocabulary is needed to ensure clarity, comparability, and future progress in LUS.

Critical relevance statement: A shared, technology-independent vocabulary is needed to ensure clarity, comparability, and future progress in lung ultrasound (LUS).

Key points: Standardized studies and methodological progress require a unified nomenclature. The ultrasound community currently lacks consistent terminology for pleural artifacts (PA). A consensus, unified terminology for PA is urgently needed.

Obesity is a complex chronic disease with a rising global prevalence and significant health implications. The laparoscopic Roux-en-Y gastric bypass (LRYGB) is one of the most widely performed bariatric procedures worldwide, ensuring significant weight loss and reducing obesity-related comorbidities. However, the risk of postoperative complications remains considerable. Multidetector computed tomography (MDCT) is regarded as the primary imaging modality for the assessment of suspected complications, due to its high diagnostic accuracy. This review offers a comprehensive overview of early (≤ 30 days) and late (> 30 days) postoperative complications, including anastomotic leak, abscess, hemorrhage, small bowel obstruction (SBO), internal hernia, gastro-gastric fistula, intussusception, and marginal ulcer, with emphasis on characteristic MDCT features. Due to its advantage as a dynamic method, upper gastrointestinal (Gl) studies with oral contrast material may be helpful for the diagnosis of leak and gastro-gastric fistula formation. A comprehensive understanding of the altered postoperative anatomy and the specific radiological signs of complications are essential for accurate MDCT interpretation, minimizing diagnostic errors and enabling timely, targeted clinical intervention. Today, MRI can be considered a problem-solver through its possibility of combining static with dynamic sequences in selected cases. In this narrative review, we highlight the most frequent complications of Roux-en-Y gastric bypass (LRYGB), allowing radiologists to become familiar with the typical radiological features and pitfalls in MDCT, upper GI studies, and MRI, when facing this type of surgery. CRITICAL RELEVANCE STATEMENT: Postoperative complications following laparoscopic LRYGB can pose considerable diagnostic challenges. Although MDCT is the most important modality, upper GI studies (for leakage or suspected gastro-gastric fistula) and increasingly MRI (for pouch problems or in pregnant patients) can improve diagnostic accuracy and support effective clinical decision-making. KEY POINTS: LRYGB complications are challenging due to altered anatomy and distinct imaging features. Postoperative bleeding, leaks with/without abscess, small bowel obstruction, and internal hernia are the most common serious complications. MDCT evaluation and reporting should be structured and focus on characteristic CT signs to support accurate imaging diagnosis.

Objective: Radiologists often face challenges in differentiating benign from malignant sacral bone lesions due to their similar imaging characteristics. This study aimed to develop an ensemble deep learning (DL) model that can preoperatively distinguish between benign and malignant sacral tumors using noncontrast computed tomography images.

Materials and methods: Preoperative sacral CT scans from 569 patients with confirmed sacral lesions were analyzed. Data from Center 1 were utilized in model development and internal test via fivefold cross-validation, and those from Centers 2 and 3 were employed in external test. Various ensemble models combining human-readable interpretation and DL were developed. The diagnostic performance of the models and radiologists was assessed using metrics such as precision, recall, accuracy, area under the curve (AUC), F1 score, and confusion matrix. Furthermore, the clinical benefits derived from radiologists' interpretations and supported by the DL model were evaluated.

Results: The ensemble model, which integrates 3D-DenseNet121 with human interpretation, exhibited the most robust performance. The ensemble model demonstrated high performance on the internal and external test sets and achieved AUCs of 0.9139 and 0.8713, F1 scores of 0.9054 and 0.8571, precision of 0.9041 and 0.8824, recall of 0.9136 and 0.8333, and accuracy of 0.8630 and 0.8182, respectively. Across the external test cohort, all radiologists experienced improvements in AUC, accuracy, sensitivity, and specificity. Notably, junior radiologists demonstrated significant improvements compared with senior radiologists.

Conclusion: The potential clinical application of the DL model lies in its capacity to considerably enhance the diagnostic efficiency of radiologists.

Critical relevance statement: This study presents the first ensemble deep learning model integrating 3D-DenseNet121 with radiologists' interpretation for preoperative differentiation of sacral tumors on noncontrast CT that improved diagnostic performance across all experience levels, particularly for junior radiologists.

Key points: First artificial intelligence-radiologist ensemble for noncontrast computed tomography (NCCT)-based sacral tumor classification. Boosts all radiologists' performance, with the greatest gains for juniors, potentially reducing referrals. Enables reliable NCCT diagnosis, overcoming contrast/magnetic resonance imaging dependency in musculoskeletal oncology.

Reports of work-related stress among healthcare workers in all disciplines have increased sharply in recent years, and radiology is no exception. Rising demand, relentless pressures and reduced time for meaningful human contact are all contributing. Against this backdrop, it is more important than ever that we recognise the characteristics of a happy radiology department and then consider strategies which we can deploy as individuals to keep us happy and healthy at work. CRITICAL RELEVANCE STATEMENT: The article discusses the importance of a healthy radiology department culture and describes the strategies which an individual radiologist can employ to maximise their own wellbeing in the face of relentless, increasing workload pressure. KEY POINTS: The frequency of burnout is increasing among radiologists. A happy work environment is essential for providing optimal patient care. There are strategies which an individual radiologist can employ to maintain their own well-being in the face of relentless increasing pressure.

Objective: Non-contrast CT (NCCT), CT perfusion (CTP), and CT angiography (CTA) are recommended for predicting delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (aSAH). However, not all patients can undergo all three examinations on admission. We aimed to compare the predictive abilities of NCCT, CTP, and CTA for DCI.

Materials and methods: This retrospective study enrolled consecutive aSAH patients admitted to our center between November 2015 and September 2023. NCCT, CTP, and CTA models were constructed using logistic regression analyses adjusted for confounders. The model performances were assessed by discrimination and calibration. Internal validation was conducted using bootstrapping. The predictive abilities were further evaluated in subgroup analyses.

Results: A total of 950 patients (median [IQR] age: 59 [51-68] years; 651 women) were enrolled, of whom 246 (25.9%) developed DCI. The NCCT model had an area under the curve (AUC) of 0.837 (95% CI: 0.808-0.866), and was superior to the CTP (AUC: 0.783; 95% CI: 0.748-0.818; p < 0.001) and CTA (AUC: 0.760; 95% CI: 0.723-0.797; p < 0.001) models. All three models had good calibration ability (all p > 0.05). Internal validation showed satisfactory discrimination ability (optimism-adjusted AUC: 0.840 for the NCCT model, 0.785 for the CTP model, and 0.761 for the CTA model). The NCCT and CTP models exhibited similar predictive abilities (AUC: 0.763 vs. 0.735; p = 0.399) in the poor-grade aSAH (World Federation of Neurological Surgeons 4-5) group.

Conclusion: The NCCT model performed better than the CTP and CTA models for predicting DCI and was comparable to the CTP model in poor-grade aSAH patients.

Critical relevance statement: For most aneurysmal subarachnoid hemorrhage patients, non-contrast CT performed at emergency admission is sufficient to evaluate disease severity and reliably predict the risk of delayed cerebral ischemia.

Key points: More straightforward and reliable indicators are required to facilitate early delayed cerebral ischemia prediction. The non-contrast CT model, utilizing admission variables, was most predictive of delayed cerebral ischemia. Non-contrast CT at admission reliably predicts delayed cerebral ischemia risk and severity in most aneurysmal subarachnoid hemorrhage patients.

Objective: This study aimed to evaluate the predictive value of quantitative gadobenate dimeglumine-enhanced MRI parameters in aggressiveness and prognosis of intrahepatic mass-forming cholangiocarcinoma (IMCC).

Materials and methods: A total of 158 patients with IMCC who underwent preoperative MRI at three centers were included, and their clinical and imaging data were analyzed retrospectively. Multimodal quantitative parameters were measured in various tumor areas, including relative intensity ratio (RIR) and relative enhancement ratio (RER) of the central and rim areas of the tumor to the liver in the hepatobiliary phase, and the center area-tumor volume ratio. Patients were classified into low-aggressiveness (Ki-67 LI < 25%) and high-aggressiveness (Ki-67 LI ≥ 25%) groups based on the Ki-67 labeling index (LI). Potential risk factors of aggressiveness were determined using multivariate logistic regression analysis. The prediction efficacy of factors was assessed using receiver operating characteristic (ROC) curves. Overall survival (OS) and disease-free survival (DFS) were evaluated using the Cox proportional-hazards regression model.

Results: The volume ratio (VR) and RIR_rim were independent risk factors for aggressiveness (p < 0.05). The area under the ROC curve was 0.803 [95% confidence interval (CI), 0.728-0.878] and 0.799 (95% CI, 0.727-0.872), both higher than that of CA19-9 ≥ 34 U/mL and intratumoral necrosis (all, p < 0.05). VR and RIR_rim were identified as independent predictors of OS and DFS in patients with IMCC (p < 0.05).

Conclusion: The multimodal quantitative MRI parameters, VR and RIR_rim, were effective risk factors for predicting both aggressiveness and prognoses in patients with IMCC.

Critical relevance statement: Noninvasive MRI hepatobiliary-phase quantification stratified aggressiveness and prognosis in intrahepatic mass-forming cholangiocarcinoma. It might provide important clinical information for treatment strategies.

Key points: The volume ratio (VR), relative intensity ratio (RIR_rim), CA19-9 ≥ 34 U/mL, and necrosis were independent predictors of high aggressiveness. The VR, RIR_rim, CA19-9 ≥ 34 U/mL, and tumor boundary were independent predictors of poorer overall survival. The VR, RIR_rim, CA19-9 ≥ 34 U/mL, tumor boundary, and tumor maximum size ≥ 3 cm were independent predictors of shorter disease-free survival.

Objectives: This study aimed to establish and validate nomograms integrating the Node-Reporting and Data System (Node-RADS) score and clinical variables to predict overall survival (OS) and progression-free survival (PFS) in patients with International Federation of Obstetrics and Gynecology (FIGO) 2018 stage IIICr cervical cancer receiving definitive chemoradiotherapy.

Materials and methods: A retrospective two-center cohort study was conducted, enrolling eligible patients treated between March 2011 and December 2022. Nomograms were established based on least absolute shrinkage and selection operator (LASSO) regression, and Cox regression was used to identify prognostic features. The performance of the nomograms was assessed using receiver operating characteristic curves (ROC), calibration curves, and decision curve analysis (DCA).

Results: A total of 307 eligible patients were analyzed. For OS, independent prognostic factors included para-aortic lymph node (PALN) metastasis, non-squamous histology, Node-RADS score, and lymph node (LN) boost irradiation ≥ 60 Gy EQD2 (Equivalent dose in 2Gy fractions); for PFS, these were T stage, non-squamous histology, and LN boost irradiation ≥ 60 Gy EQD2. Nomograms outperformed FIGO 2009/2018 staging in discrimination and clinical utility, with calibration curves showing good agreement between predicted and observed outcomes. Kaplan-Meier analysis linked higher Node-RADS scores, PALN metastasis, > 3 positive LNs, and LN boost irradiation < 60 Gy EQD2 to poorer OS and PFS.

Conclusion: A nomogram incorporating the Node-RADS score, which is significantly associated with survival, can serve as a potential prognostic marker to assist clinicians in making informed decisions and developing individualized treatment strategies. Notably, the inherent treatment-selection bias in the retrospective design limits its direct therapeutic implications.

Critical relevance statement: Node-RADS-based nomograms offer superior risk stratification and prognosis prediction for stage IIICr cervical cancer patients.

Key points: The nomogram incorporating the Node-Reporting and Data System (Node-RADS) score can serve as a potential prognostic marker to assist clinicians. The nomogram incorporating the Node-RADS score, which integrated clinicopathological data and therapies, outperformed Federation of Obstetrics and Gynecology (FIGO) staging in discriminative ability and clinical utility. Higher Node-RADS scores correlated with worse survival outcomes of patients, and lymph node (LN) boost irradiation ≥ 60 Gy EQD2 might provide survival benefits.

This review aims to provide a comprehensive pictorial review of low-flow vascular malformations (LFVMs) of the central nervous system (CNS) without arteriovenous shunting, focusing on their epidemiology, pathophysiology, imaging features, and associations with other vascular anomalies. LFVMs - developmental venous anomalies (DVAs), cavernous malformations (CMs), brain capillary telangiectasias (BCTs), and sinus pericranii (SP) - are typically benign and incidental but may cause symptoms or hemorrhage. Differentiating LFVMs from neoplastic, inflammatory, or high-flow vascular lesions is critical to avoid misdiagnosis and inappropriate treatment. MRI is the reference technique. DVAs show a "caput medusae" venous pattern; CMs have a mulberry-like core with a complete hemosiderin rim on T2*/SWI; BCTs are often occult on routine MRI but may display brush-like enhancement and subtle SWI hypointensity; SP consists of an extracranial venous mass communicating with a dural sinus through a transosseous vein. Familiarity with the imaging spectrum and typical associations of CNS LFVMs enables confident diagnosis and helps avoid unnecessary invasive procedures. CRITICAL RELEVANCE STATEMENT: By illustrating key imaging features of low-flow CNS vascular malformations, this article critically addresses frequent diagnostic pitfalls. It advances radiological practice by guiding differentiation from neoplastic or high-flow lesions and improving multidisciplinary patient care. KEY POINTS: LFVMs (DVAs, CMs, capillary telangiectasia, SP) are frequently incidental but may cause hemorrhage, seizures, or neurological deficits. DVAs are typically benign drainage variants; hemodynamic congestion on perfusion weighted imaging explains occasional symptoms and the frequent association with acquired CMs. CMS presents as "mulberry-shaped" lesions with a hemosiderin rim on SWI sequences, reflecting microhemorrhages and the absence of intervening brain parenchyma. Capillary telangiectasia most often occurs in the pons; recognition of the characteristic SWI hypointensity with faint enhancement prevents misdiagnosis as a neoplasm or ischemia. AP shows trans‑osseous venous channels connecting dural sinuses to epicranial varices; CT characterizes bony defects, and MRI depicts venous communication.