Comparison of diagnostic value of technetium 99m-labeled red blood cell computed single photon emission computed tomography/computed tomography (99mTc-RBC SPECT/CT) and contrast-enhanced multidetector computed tomography (MDCT) for small bowel bleeding: a retrospective study.

Background: Although small bowel bleeding is relatively rare, it is a potentially fatal disease, and its diagnosis still faces challenges. Technetium 99m-labeled red blood cell computed single photon emission computed tomography/computed tomography (99mTc-RBC SPECT/CT) and contrast-enhanced multidetector computed tomography (MDCT) are common imaging methods for diagnosing small bowel bleeding, but there have been no studies comparing their diagnostic efficacy for this purpose. This study aims to compare the diagnostic value of 99mTc-RBC SPECT/CT and contrast-enhanced MDCT for small bowel bleeding. Methods: A total of 44 patients (30 males and 14 females, median age of 64 years) definitively diagnosed with small bowel bleeding and 15 non-small bowel bleeding patients (8 males and 7 females, median age of 66 years) were consecutively included in this study. All patients underwent 99mTc-RBC SPECT/CT and contrast-enhanced MDCT examinations at Beijing Friendship Hospital of Capital Medical University between January 2020 to September 2023. The definitive diagnosis had been made through surgery or colonoscopy, or through patient history, patient management, and clinical follow-up. We collected clinical data of the participants. 99mTc-RBC SPECT/CT and contrast-enhanced MDCT were reviewed in a blinded fashion for accuracy of detection of active bleeding as well as the active small bowel bleeding location. Results: Among the 59 patients, the accuracy, sensitivity, and specificity of 99mTc-RBC SPECT were 27.3%, 93.3%, and 92.3%; for 99mTc-RBC SPECT/CT they were 76.3%, 40.5%, and 93.3%; whereas for contrast-enhanced MDCT they were 45.8%, 27.3%, and 100%, respectively. The diagnostic accuracy of 99mTc-RBC SPECT/CT for jejunal and ileal bleeding was high, at 100% and 86.4%, respectively. Meanwhile, 99mTc-RBC SPECT/CT had a higher accuracy in diagnosing more causes of small bowel bleeding. In 59 patients, the combination of 99mTc-RBC SPECT/CT and contrast-enhanced MDCT accurately diagnosed small bowel bleeding and provided precise localization in 50 patients, resulting in the accuracy, sensitivity, and specificity of 84.7%, 79.5%, and 100.0%, respectively. Conclusions: 99mTc-RBC SPECT/CT has high diagnostic value in diagnosing small bowel bleeding and is superior to 99mTc-RBC SPECT and contrast-enhanced MDCT. The combination of 99mTc-RBC SPECT/CT and contrast-enhanced MDCT can further improve the diagnostic accuracy of diagnosis, and can accurately guide the diagnosis and treatment of small bowel bleeding.

Comparison of the clinicoradiological features and outcomes of lymphoepithelioma-like cholangiocarcinoma and conventional intrahepatic cholangiocarcinoma: A propensity score matching analysis.

BACKGROUND/PURPOSE: Lymphoepithelioma-like cholangiocarcinoma (LELCC) is a rare variant of intrahepatic cholangiocarcinoma (ICC). We aim to analyze the differences in the clinical and radiological features of LELCC and ICC. METHODS: Between January 2003 and December 2019, a total of 21 patients diagnosed with LELCC were retrospectively enrolled, and 84 patients with ICC were selected through propensity score matching by sex, age, and initial cancer stage. The clinical characteristics, pathological findings, and radiological features were analyzed. The differences in overall survival (OS) between LELCC and ICC were evaluated using the Kaplan-Meier method. RESULTS: The serum carbohydrate antigen 19-9 (CA 19-9) level was higher in the ICC group than in the LELCC group (77.9 vs 30.0 U/mL, p = 0.004). Non-rim arterial phase hyperenhancement (47.1% vs 13.7%, p = 0.005) and portovenous washout (35.3% vs 4.1%, p = 0.001) were more frequently observed in the LELCC group than in the ICC group. Intrahepatic duct dilatation was a distinct feature of the ICC group. The 5-year OS rates in the LELCC and ICC groups were 69.3% and 58.2%, respectively (p = 0.047). The 5-year OS of patients with stages I and II LELCC between ICC were not significantly different (90.0% vs 83.4%, p = 0.464). However, the 5-year OS of patients with stages III and IV LELCC was more favorable than that of patients with ICC (29.2% vs 23.0%, p = 0.017). CONCLUSIONS: LELCC had a favorable outcome and several different clinicoradiological features compared with ICC.

Radiomics analysis in predicting vascular invasion in gastric cancer based on enhanced CT: a preliminary study.

BACKGROUND: Vascular invasion (VI) is closely related to the metastasis, recurrence, prognosis, and treatment of gastric cancer. Currently, predicting VI preoperatively using traditional clinical examinations alone remains challenging. This study aims to explore the value of radiomics analysis based on preoperative enhanced CT images in predicting VI in gastric cancer. METHODS: We retrospectively analyzed 194 patients with gastric adenocarcinoma who underwent enhanced CT examination. Based on pathology analysis, patients were divided into the VI group (n = 43) and the non-VI group (n = 151). Radiomics features were extracted from arterial phase (AP) and portal venous phase (PP) CT images. The radiomics score (Rad-score) was then calculated. Prediction models based on image features, clinical factors, and a combination of both were constructed. The diagnostic efficiency and clinical usefulness of the models were evaluated using receiver operating characteristic (ROC) curves and decision curve analysis (DCA). RESULTS: The combined prediction model included the Rad-score of AP, the Rad-score of PP, Ki-67, and Lauren classification. In the training group, the area under the curve (AUC) of the combined prediction model was 0.83 (95% CI 0.76-0.89), with a sensitivity of 64.52% and a specificity of 92.45%. In the validation group, the AUC was 0.80 (95% CI 0.67-0.89), with a sensitivity of 66.67% and a specificity of 88.89%. DCA indicated that the combined prediction model might have a greater net clinical benefit than the clinical model alone. CONCLUSION: The integrated models, incorporating enhanced CT radiomics features, Ki-67, and clinical factors, demonstrate significant predictive capability for VI. Moreover, the radiomics model has the potential to optimize personalized clinical treatment selection and patient prognosis assessment.

A Rare Case of Symptomatic Anomalous Origin of the Right Coronary Artery With a High Interarterial Course Between the Pulmonary Artery and the Aorta.

The congenital anomalous origin of the right coronary artery (AORCA) with an incongruous course is a rare malformation that can manifest as exertional chest pain, syncope, arrhythmias, heart failure, and sudden cardiac death. We present a case of a 42-year-old male with a history of hypercholesterolemia who presented with chest pain and dizziness upon exertion for two weeks. The physical examination was unremarkable, and the patient was hemodynamically stable. Initial blood tests were normal. Electrocardiogram (ECG) showed sinus bradycardia at 56 bpm without ST or T wave changes. A cardiac stress test indicated antero-apical inducible ischemia with a moderate probability of stress-induced ischemia. Computed tomography angiography (CTA) revealed an AORCA with a high interarterial course between the pulmonary artery and the aorta. Subsequent left heart catheterization confirmed the anomalous origin and revealed atherosclerotic disease. This anomaly was identified as the cause of the patient's symptoms due to the compression of the right coronary artery (RCA). The patient was treated with aspirin and statin and underwent successful internal mammary artery-RCA bypass grafting. Postoperatively, the patient's symptoms resolved, and there were no further episodes of chest pain.

Evaluating Microsoft Bing with ChatGPT-4 for the assessment of abdominal computed tomography and magnetic resonance images.

PURPOSE: To evaluate the performance of Microsoft Bing with ChatGPT-4 technology in analyzing abdominal computed tomography (CT) and magnetic resonance images (MRI). METHODS: A comparative and descriptive analysis was conducted using the institutional picture archiving and communication systems. A total of 80 abdominal images (44 CT, 36 MRI) that showed various entities affecting the abdominal structures were included. Microsoft Bing's interpretations were compared with the impressions of radiologists in terms of recognition of the imaging modality, identification of the imaging planes (axial, coronal, and sagittal), sequences (in the case of MRI), contrast media administration, correct identification of the anatomical region depicted in the image, and detection of abnormalities. RESULTS: Microsoft Bing detected that the images were CT scans with 95.4% accuracy (42/44) and that the images were MRI scans with 86.1% accuracy (31/36). However, it failed to detect one CT image (2.3%) and misidentified another CT image as an MRI (2.3%). On the other hand, it also misidentified four MRI as CT images (11.1%) and one as an X-ray (2.7%). Bing achieved an 83.75% success rate in correctly identifying abdominal regions, with 90% accuracy for CT scans (40/44) and 77.7% for MRI scans (28/36). Concerning the identification of imaging planes, Bing achieved a success rate of 95.4% for CT images and 83.3% for MRI. Regarding the identification of MRI sequences (T1-weighted and T2-weighted), the success rate was 68.75%. In the identification of the use of contrast media for CT scans, the success rate was 64.2%. Bing detected abnormalities in 35% of the images but achieved a correct interpretation rate of 10.7% for the definite diagnosis. CONCLUSION: While Microsoft Bing, leveraging ChatGPT-4 technology, demonstrates proficiency in basic task identification on abdominal CT and MRI, its inability to reliably interpret abnormalities highlights the need for continued refinement to enhance its clinical applicability. CLINICAL SIGNIFICANCE: The contribution of large language models (LLMs) to the diagnostic process in radiology is still being explored. However, with a comprehensive understanding of their capabilities and limitations, LLMs can significantly support radiologists during diagnosis and improve the overall efficiency of abdominal radiology practices. Acknowledging the limitations of current studies related to ChatGPT in this field, our work provides a foundation for future clinical research, paving the way for more integrated and effective diagnostic tools.

Spectrum of imaging findings of primary bone lymphoma in pediatric patients.

Primary bone lymphoma, a rare oncologic entity, may initially present with minimal symptoms. Presenting symptoms range from local pain and mild systemic symptoms to large palpable masses and pathologic fractures. The term "primary bone lymphoma" indicates the finding of bone involvement without other organ sites for at least 6 months. Although some radiological features may raise suspicion about this tumor form, there are no pathognomonic imaging findings, and the diagnosis will likely be delayed for a long time. The most critical radiological feature is soft tissue involvement associated with a preserved cortical layer, much more than expected for an infiltrating lesion. Anyway, very different radiological findings may be displayed in patients with primary bone lymphoma. Although these radiological features of primary bone lymphoma have been discussed in the literature by various authors, there is little data concerning imaging in pediatric patients. This paper aims to depict the possible spectrum of imaging features of primary bone lymphoma in the pediatric age, providing an exemplification pictorial essay extracted from a single institution experience in the year range period 2006-2022.

Variability of radiological and clinical features in cases with usual interstitial pneumonia without honeycombing.

BACKGROUND: Usual interstitial pneumonia (UIP) cases without honeycombing (possible UIP) included various CT features and was often difficult to diagnose. PURPOSE: This study aimed to classify the cases with possible UIP on CT features using cluster analysis and evaluate the features of subsets of participants and the correlation of prognosis. MATERIALS AND METHODS: The study included 85 patients with possible UIP in the 2011 idiopathic pulmonary fibrosis (IPF) guideline with radiological diagnosis. All cases underwent surgical biopsies and were diagnosed by multidisciplinary discussion (MDD) from the nationwide registry in Japan. The readers evaluated pulmonary opacity, nodules, cysts, and predominant distribution which were reclassified by IPF guidelines in 2018. Additionally, cases were classified into four groups by cluster analysis based on CT findings. The differences in survival among IPF classification and the clusters were evaluated. RESULTS: Cases were diagnosed as IPF (n = 55), NSIP (n = 4), unclassifiable (n = 23), and others (n = 3) by MDD. Cluster analysis revealed 4 clusters by CT features (n = 47, 16, 19 and 3, respectively). Cluster 1 had fewer lesions overall. Cluster 2 have many pure ground-glass opacities and ground-glass opacities with reticulation. Cluster 3 had many reticular opacities and nodules with few lower predominant distributions. Cluster 4 was characterized by peribronchovascular consolidation.The mean survival time of cluster 1 (4518 days) was significantly better than cluster 2, 3, and 4 (1843, 2196, and 1814 days, respectively) (p = 0.03). CONCLUSION: In conclusion, UIP without honeycombing included various CT patterns and MDD diagnoses. Significangly differences in prognosis were observed among clusters classified by CT findings.

Imaging findings of thoracic manifestations of Crohn's disease and ulcerative colitis.

Thoracic manifestations of inflammatory bowel disease (IBD) are rare, occurring in less than 1% of patients. Unlike most other extra-intestinal manifestations, they predominate in patients with ulcerative colitis rather than in Crohn's disease. In most patients, thoracic involvement follows the onset of IBD by several years. However, thoracic involvement may also occur synchronously or even precede the onset of digestive symptoms. The thoracic manifestations of IBD include airway involvement and parenchymal lung abnormalities. Airways are the most frequent anatomical site for thoracic involvement in IBD. Airway manifestations usually develop several years after the onset of intestinal manifestations, preferentially when the latter are stable or in remission. Airway manifestations include bronchial wall thickening, bronchiectasis, small airway disease, and tracheal wall thickening. Parenchymal lung abnormalities are less prevalent in IBD and include organizing pneumonia, necrobiotic nodules, noncaseating granulomatous nodules, drug-induced pneumonia, and rarely interstitial lung diseases. The differential diagnosis between organizing pneumonia, necrobiotic nodules, and noncaseating granulomatous nodules is difficult and usually requires histopathological analysis for a definite diagnosis. Radiologists play a key role in the detection of thoracic manifestations of Crohn's disease and ulcerative colitis and, therefore, need to be familiar with their imaging findings. This article aims to offer an overview of the imaging findings of thoracic manifestations in patients with Crohn's disease or ulcerative colitis. CRITICAL RELEVANCE STATEMENT: Thoracic manifestations of Crohn's disease and ulcerative colitis include tracheal involvement, bronchiectasis, small airway disease, and parenchymal lung abnormalities such as organizing pneumonia and necrobiotic nodules. These rare manifestations (< 1% of patients) more often affect patients with ulcerative colitis. KEY POINTS: Thoracic manifestations of inflammatory bowel disease are rare, occurring in less than 1% of patients. Thoracic manifestations are more frequent in patients with ulcerative colitis than Crohn's disease. Bronchial disease is the most frequent thoracic manifestation of Crohn's disease and ulcerative colitis.

Non-contrast spectral CT vs chemical-shift MRI in discriminating lipid-poor adrenal lesions.

OBJECTIVES: To compare the diagnostic performance of conventional non-contrast CT, dual-energy spectral CT, and chemical-shift MRI (CS-MRI) in discriminating lipid-poor adenomas (> 10-HU on non-contrast CT) from non-adenomas. METHODS: A total of 110 patients (69 men; 41 women; mean age 66.5 ± 13.4 years) with 80 lipid-poor adenomas and 30 non-adenomas who underwent non-contrast dual-layer spectral CT and CS-MRI were retrospectively identified. For each lesion, non-contrast attenuation on conventional 120-kVp images, ΔHU-index ([attenuation difference between virtual monoenergetic 140-keV and 40-keV images]/conventional attenuation × 100), and signal intensity index (SI-index) were quantified. Each parameter was compared between adenomas and non-adenomas using the Mann-Whitney U-test. The area under the receiver operating characteristic curve (AUC) and sensitivity to achieve > 95% specificity for adenoma diagnosis were determined. RESULTS: Conventional non-contrast attenuation was lower in adenomas than in non-adenomas (22.4 ± 8.6 HU vs 32.8 ± 48.5 HU), whereas ΔHU-index (148.0 ± 103.2 vs 19.4 ± 25.8) and SI-index (41.6 ± 19.6 vs 4.2 ± 10.2) were higher in adenomas (all, p < 0.001). ΔHU-index showed superior performance to conventional non-contrast attenuation (AUC: 0.919 [95% CI: 0.852-0.963] vs 0.791 [95% CI: 0.703-0.863]; sensitivity: 75.0% [60/80] vs 27.5% [22/80], both p < 0.001), and near equivalent to SI-index (AUC: 0.952 [95% CI: 0.894-0.984], sensitivity 85.0% [68/80], both p > 0.05). Both the ΔHU-index and SI-index provided a sensitivity of 96.0% (48/50) for hypoattenuating adenomas (≤ 25 HU). For hyperattenuating (> 25 HU) adenomas, SI-index showed higher sensitivity than ΔHU-index (66.7% [20/30] vs 40.0% [12/30], p = 0.022). CONCLUSIONS: Non-contrast spectral CT and CS-MRI outperformed conventional non-contrast CT in distinguishing lipid-poor adenomas from non-adenomas. While CS-MRI demonstrated superior sensitivity for adenomas measuring > 25 HU, non-contrast spectral CT provided high discriminative values for adenomas measuring ≤ 25 HU. CLINICAL RELEVANCE STATEMENT: Spectral attenuation analysis improves the diagnostic performance of non-contrast CT in discriminating lipid-poor adrenal adenomas, potentially serving as an alternative to CS-MRI and obviating the necessity for additional diagnostic workup in indeterminate adrenal incidentalomas, particularly for lesions measuring ≤ 25 HU. KEY POINTS: Incidental adrenal lesion detection has increased as abdominal CT use has become more frequent. Non-contrast spectral CT and CS-MRI differentiated lipid-poor adenomas from non-adenomas better than conventional non-contrast CT. For lesions measuring ≤ 25 HU, spectral CT may obviate the need for additional evaluation.

Metastatic Lung Adenocarcinomas: Development and Evaluation of Radiomic-Based Methods to Measure Baseline Intra-Patient Inter-Tumor Lesion Heterogeneity.

Radiomics has traditionally focused on individual tumors, often neglecting the integration of metastatic disease, particularly in patients with non-small cell lung cancer. This study sought to examine intra-patient inter-tumor lesion heterogeneity indices using radiomics, exploring their relevance in metastatic lung adenocarcinoma. Consecutive adults newly diagnosed with metastatic lung adenocarcinoma underwent contrast-enhanced CT scans for lesion segmentation and radiomic feature extraction. Three methods were devised to measure distances between tumor lesion profiles within the same patient in radiomic space: centroid to lesion, lesion to lesion, and primitive to lesion, with subsequent calculation of mean, range, and standard deviation of these distances. Associations between HIs, disease control rate, objective response rate to first-line treatment, and overall survival were explored. The study included 167 patients (median age 62.3 years) between 2016 and 2019, divided randomly into experimental (N = 117,546 lesions) and validation (N = 50,232 tumor lesions) cohorts. Patients without disease control/objective response and with poorer survival consistently systematically exhibited values of all heterogeneity indices. Multivariable analyses revealed that the range of primitive-to-lesion distances was associated with disease control in both cohorts and with objective response in the validation cohort. This metrics showed univariable associations with overall survival in the experimental. In conclusion, we proposed original methods to estimate the intra-patient inter-tumor lesion heterogeneity using radiomics that demonstrated correlations with patient outcomes, shedding light on the clinical implications of inter-metastases heterogeneity. This underscores the potential of radiomics in understanding and potentially predicting treatment response and prognosis in metastatic lung adenocarcinoma patients.

An integrated nomogram combining clinical and radiomic features of hyperattenuated imaging markers to predict malignant cerebral edema following endovascular thrombectomy.

Background: Malignant cerebral edema (MCE), a potential complication following endovascular thrombectomy (EVT) in the treatment of acute ischemic stroke (AIS), can result in significant disability and mortality. This study aimed to develop a nomogram model based on the hyperattenuated imaging marker (HIM), characterized by hyperattenuation on head noncontrast computed tomography (CT) immediately after thrombectomy, to predict MCE in patients receiving EVT. Methods: In this retrospective cohort study, we selected 151 patients with anterior circulation large-vessel occlusion who received endovascular treatment. The patients were randomly allocated into training (n=121) and test (n=30) cohorts. HIM was used to extract radiomics characteristics. Conventional clinical and radiological features associated with MCE were also extracted. A model based on extreme gradient boosting (XGBoost) machine learning using fivefold cross-validation was employed to acquire radiomics and clinical features. Based on HIM, clinical and radiological signatures were used to construct a prediction nomogram for MCE. Subsequently, the signatures were merged through logistic regression (LR) analysis in order to create a comprehensive clinical radiomics nomogram. Results: A total of 28 patients out of 151 (18.54%) developed MCE. The analysis of the receiver operating characteristic curve indicated an area under the curve (AUC) of 0.999 for the prediction of MCE in the training group and an AUC of 0.938 in the test group. The clinical and radiomics nomogram together showed the highest accuracy in predicting outcomes in both the training and test groups. Conclusions: The novel nomogram, which combines clinical manifestations and imaging findings based on postinterventional HIM, may serve as a predictor for MCE in patients experiencing AIS after EVT.

Insights about cervical lymph nodes: Evaluating deep learning-based reconstruction for head and neck computed tomography scan.

Purpose: This study aimed to investigate differences in cervical lymph node image quality on dual-energy computed tomography (CT) scan with datasets reconstructed using filter back projection (FBP), hybrid iterative reconstruction (IR), and deep learning-based image reconstruction (DLIR) in patients with head and neck cancer. Method: Seventy patients with head and neck cancer underwent follow-up contrast-enhanced dual-energy CT examinations. All datasets were reconstructed using FBP, hybrid IR with 30 % adaptive statistical IR (ASiR-V), and DLIR with three selectable levels (low, medium, and high) at 2.5- and 0.625-mm slice thicknesses. Herein, signal, image noise, signal-to-noise ratio, and contrast-to-noise ratio of lymph nodes and overall image quality, artifact, and noise of selected regions of interest were evaluated by two radiologists. Next, cervical lymph node sharpness was evaluated using full width at half maximum. Results: DLIR exhibited significantly reduced noise, ranging from 3.8 % to 35.9 % with improved signal-to-noise ratio (11.5-105.6 %) and contrast-to-noise ratio (10.5-107.5 %) compared with FBP and ASiR-V, for cervical lymph nodes (p < 0.001). Further, 0.625-mm-thick images reconstructed using DLIR-medium and DLIR-high had a lower noise than 2.5-mm-thick images reconstructed using FBP and ASiR-V. The lymph node margins and vessels on DLIR-medium and DLIR-high were sharper than those on FBP and ASiR-V (p < 0.05). Both readers agreed that DLIR had a better image quality than the conventional reconstruction algorithms. Conclusion: DLIR-medium and -high provided superior cervical lymph node image quality in head and neck CT. Improved image quality affords thin-slice DLIR images for dose-reduction protocols in the future.

Deep learning image reconstruction for low-kiloelectron volt virtual monoenergetic images in abdominal dual-energy CT: medium strength provides higher lesion conspicuity.

BACKGROUND: The best settings of deep learning image reconstruction (DLIR) algorithm for abdominal low-kiloelectron volt (keV) virtual monoenergetic imaging (VMI) have not been determined. PURPOSE: To determine the optimal settings of the DLIR algorithm for abdominal low-keV VMI. MATERIAL AND METHODS: The portal-venous phase computed tomography (CT) scans of 109 participants with 152 lesions were reconstructed into four image series: VMI at 50 keV using adaptive statistical iterative reconstruction (Asir-V) at 50% blending (AV-50); and VMI at 40 keV using AV-50 and DLIR at medium (DLIR-M) and high strength (DLIR-H). The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of nine anatomical sites were calculated. Noise power spectrum (NPS) using homogenous region of liver, and edge rise slope (ERS) at five edges were measured. Five radiologists rated image quality and diagnostic acceptability, and evaluated the lesion conspicuity. RESULTS: The SNR and CNR values, and noise and noise peak in NPS measurements, were significantly lower in DLIR images than AV-50 images in all anatomical sites (all P < 0.001). The ERS values were significantly higher in 40-keV images than 50-keV images at all edges (all P < 0.001). The differences of the peak and average spatial frequency among the four reconstruction algorithms were significant but relatively small. The 40-keV images were rated higher with DLIR-M than DLIR-H for diagnostic acceptance (P < 0.001) and lesion conspicuity (P = 0.010). CONCLUSION: DLIR provides lower noise, higher sharpness, and more natural texture to allow 40 keV to be a new standard for routine VMI reconstruction for the abdomen and DLIR-M gains higher diagnostic acceptance and lesion conspicuity rating than DLIR-H.

Aortic Valve Calcium Score: Applications in Clinical Practice and Scientific Research-A Narrative Review.

In this narrative review, we investigate the essential role played by the computed tomography Aortic Valve Calcium Score (AVCS) in the cardiovascular diagnostic landscape, with a special focus on its implications for clinical practice and scientific research. Calcific aortic valve stenosis is the most prevalent type of aortic stenosis (AS) in industrialized countries, and due to the aging population, its prevalence is increasing. While transthoracic echocardiography (TTE) remains the gold standard, AVCS stands out as an essential complementary tool in evaluating patients with AS. The advantage of AVCS is its independence from flow; this allows for a more precise evaluation of patients with discordant findings in TTE. Further clinical applications of AVCS include in the assessment of patients before transcatheter aortic valve replacement (TAVR), as it helps in predicting outcomes and provides prognostic information post-TAVR. Additionally, we describe different AVCS thresholds regarding gender and the anatomical variations of the aortic valve. Finally, we discuss various scientific studies where AVCS was applied. As AVCS has some limitations, due to the pathophysiologies of AS extending beyond calcification and gender differences, scientists strive to validate contrast-enhanced AVCS. Furthermore, research on developing radiation-free methods of measuring calcium content is ongoing.

Improvement of Breast Cancer Detection Using Dual-Layer Spectral CT.

This study aimed to investigate the diagnostic performance of breast mass detection on monoenergetic image data at 40 keV (MonoE40) and on iodine maps (IM) compared with conventional image data (CI). In this prospective single-center case-control study, 50 breast cancer patients were examined using contrast-enhanced dual-layer spectral CT. For qualitative and quantitative comparison of MonoE40 and IM with CI image data, four blinded, independent readers assessed 300 randomized single slices (two slices for each imaging type per case) with or without cancerous lesions for the presence of a breast mass. Detection sensitivity and specificity were calculated and readers rated their subjective diagnostic certainty. For statistical analysis of sensitivity and specificity, a paired t-test and ANOVA were used (significance level p = 0.05). A total of 50 female patients (median age 51 years, range 28-83 years) participated. IM had the highest overall scores in sensitivity and specificity for breast cancer detection, with 0.97 ± 0.06 and 0.95 ± 0.07, respectively, compared with 0.90 ± 0.04 and 0.92 ± 0.06 in CI. MonoE40 yielded a sensitivity of 0.96 ± 0.02 and specificity of 0.94 ± 0.08. All differences in sensitivity and specificity between MonoE or IM and CI were statistically significant (p < 0.001). The superiority of IM sensitivity and specificity was most pronounced in patients with dense breasts. Spectral CT improved the detection of breast cancer with higher sensitivity and specificity compared to conventional image data in our study.

Dual-energy CT in differentiating benign gallbladder wall thickening from wall thickening type of gallbladder cancer.

OBJECTIVE: To evaluate the performance of dual-energy computed tomography (DECT) in differentiating non-acute benign from malignant gallbladder wall thickening (GBWT). METHODS: This prospective study comprised consecutive adults with GBWT who underwent late arterial phase (LAP) and portal venous phase (PVP) DECT between January 2022 and May 2023. The final diagnosis was based on histopathology or 3-6 months follow-up imaging. DECT images in LAP and PVP were assessed independently by two radiologists. The demographic, qualitative, and quantitative parameters were compared between two groups Multivariate logistic regression was performed to determine the association between the aforementioned factors and malignant GBWT. RESULTS: Seventy-five patients (mean age 56 ± 12.8 years, 46 females) were included. Forty-two patients had benign, and 33 had malignant GBWT. In the overall group, female gender (p = 0.018), lymphadenopathy (p = 0.011), and omental nodules (p = 0.044) were significantly associated with malignant GBWT. None of the DECT features differed significantly between benign and malignant GBWT in overall group. In the xanthogranulomatous cholecystitis (XGC, n = 9) vs. gallbladder cancer (GBC) (n = 33) subgroup, mean attenuation value at 140 keV LAP VMI was significantly associated with malignant GBWT [p = 0.023, area under curve 0.759 (95%CI 0.599-0.919)]. CONCLUSION: DECT-generated quantitative parameters do not add value in differentiating non-acute benign from malignant GBWT. However, DECT may have a role in differentiating XGC from GBC in a selected subgroup of patients. Further, larger studies may be necessary to confirm these findings. CLINICAL RELEVANCE STATEMENT: In patients with non-acute gallbladder wall thickening in whom there is suspicion of xanthogranulomatous cholecystitis (XGC), DECT findings may allow differentiation of XGC from wall thickening type of gallbladder cancer. KEY POINTS: Differentiation of benign and malignant gallbladder wall thickening (GBWT) at CT is challenging. Quantitative dual energy CT (DECT) features do not provide additional value in differentiating benign and malignant GBWT. DECT may be helpful in a subgroup of patients to differentiate xanthogranulomatous cholecystitis from gallbladder cancer.

Prediction of tumor regression grade in far-advanced gastric cancer after preoperative immuno-chemotherapy using dual-energy CT-derived extracellular volume fraction.

OBJECTIVES: This study examines the effectiveness of dual-energy CT (DECT) delayed-phase extracellular volume (ECV) fraction in predicting tumor regression grade (TRG) in far-advanced gastric cancer (FAGC) patients receiving preoperative immuno-chemotherapy. MATERIALS AND METHODS: A retrospective analysis was performed on far-advanced gastric adenocarcinoma patients treated with preoperative immuno-chemotherapy at our institution from August 2019 to March 2023. Patients were categorized based on their TRG into pathological complete response (pCR) and non-pCR groups. ECV was determined using the delayed-phase iodine maps. In addition, tumor iodine densities and standardized iodine ratios were meticulously analyzed using the triple-phase enhanced iodine maps. Univariate analysis with five-fold cross-validation and Spearman correlation determined DECT parameters and clinical indicators association with pCR. The predictive accuracy of these parameters for pCR was evaluated using a weighted logistic regression model with five-fold cross-validation. RESULTS: Of the 88 patients enrolled (mean age 60.8 ± 11.1 years, 63 males), 21 (23.9%) achieved pCR. Univariate analysis indicated ECV's significant role in differentiating between pCR and non-pCR groups (average p value = 0.021). In the logistic regression model, ECV independently predicted pCR with an average odds ratio of 0.911 (95% confidence interval, 0.798-0.994). The model, incorporating ECV, tumor area, and IDAV (the relative change rate of iodine density from venous phase to arterial phase), showed an average area under curves (AUCs) of 0.780 (0.770-0.791) and 0.766 (0.731-0.800) for the training and validation sets, respectively, in predicting pCR. CONCLUSION: DECT-derived ECV fraction is a valuable predictor of TRG in FAGC patients undergoing preoperative immuno-chemotherapy. CLINICAL RELEVANCE STATEMENT: This study demonstrates that DECT-derived extracellular volume fraction is a reliable predictor for pathological complete response in far-advanced gastric cancer patients receiving preoperative immuno-chemotherapy, offering a noninvasive tool for identifying potential treatment beneficiaries.