Optimizing resource allocation: Cost-effectiveness of specified D-dimer cut-offs in cancer patients with suspected venous thromboembolism.

An accurate diagnosis of venous thromboembolism (VTE) is crucial, given the potential for high mortality in undetected cases. Strategic D-dimer testing may aid in identifying low-risk patients, preventing overdiagnosis and reducing imaging costs. We conducted a retrospective, comparative analysis to assess the potential cost savings that could be achieved by adopting different approaches to determine the most effective D-dimer cut-off value in cancer patients with suspected VTE, compared to the commonly used rule-out cut-off level of 0.5 mg/L. The study included 526 patients (median age 65, IQR 55-75) with a confirmed cancer diagnosis who underwent D-dimer testing. Among these patients, the VTE prevalence was 29% (n = 152). Each diagnostic strategy's sensitivity, specificity, negative likelihood ratio (NLR), as well as positive likelihood ratio (PLR), and the proportion of patients exhibiting a negative D-dimer test result, were calculated. The diagnostic strategy that demonstrated the best balance between specificity, sensitivity, NLR, and PLR, utilized an inverse age-specific cut-off level for D-dimer [0.5 + (66-age) × 0.01 mg/L]. This method yielded a PLR of 2.9 at a very low NLR for the exclusion of VTE. We observed a significant cost reduction of 4.6% and 1.0% for PE and DVT, respectively. The utilization of an age-adjusted cut-off [patient's age × 0.01 mg/L] resulted in the highest cost savings, reaching 8.1% for PE and 3.4% for DVT. Using specified D-dimer cut-offs in the diagnosis of VTE could improve economics, considering the limited occurrence of confirmed cases among patients with suspected VTE.

Predictive Value of Dual-Energy CT-Derived Metrics for the Use of Bone Substitutes in Distal Radius Fracture Surgery.

(1) Background: Low bone mineral density (BMD) is a significant risk factor for complicated surgery and leads to the increased use of bone substitutes in patients with distal radius fractures (DRFs). No accepted model has yet been established to predict the use of bone substitutes to facilitate preoperative planning. (2) Methods: Unenhanced dual-energy CT (DECT) images of DRFs were retrospectively acquired between March 2016 and September 2020 using the internal PACS system. Available follow-up imaging and medical health records were reviewed to determine the use of bone substitutes. DECT-based BMD, trabecular Hounsfield units (HU), cortical HU, and cortical thickness ratio were measured in non-fractured segments of the distal radius. Diagnostic accuracy parameters were calculated for all metrics using receiver-operating characteristic (ROC) curves and associations of all metrics with the use of bone substitutes were evaluated using logistic regression models. (3) The final study population comprised 262 patients (median age 55 years [IQR 43-67 years]; 159 females, 103 males). According to logistic regression analysis, DECT-based BMD was the only metric significantly associated with the use of bone substitutes (odds ratio 0.96, p = 0.003). However, no significant associations were found for cortical HU (p = 0.06), trabecular HU (p = 0.33), or cortical thickness ratio (p = 0.21). ROC-curve analysis revealed that a combined model of all four metrics had the highest diagnostic accuracy with an area under the curve (AUC) of 0.76. (4) Conclusions: DECT-based BMD measurements performed better than HU-based measurements and cortical thickness ratio. The diagnostic performance of all four metrics combined was superior to that of the individual parameters.

Advancing Differentiation of Hepatic Metastases in Malignant Melanoma through Dual-Energy Computed Tomography Rho/Z Maps.

OBJECTIVES: The aim of this study is to evaluate the diagnostic accuracy of dual-energy computed tomography (DECT)-based Rho/Z maps in differentiating between metastases and benign liver lesions in patients diagnosed with malignant melanoma compared to conventional CT value measurements. METHODS: This retrospective study included 73 patients (mean age, 70 ± 13 years; 43 m/30 w) suffering from malignant melanoma who had undergone third-generation DECT as part of tumor staging between December 2017 and December 2021. For this study, we measured Rho (electron density) and Z (effective atomic number) values as well as Hounsfield units (HUs) in hypodense liver lesions. Values were compared, and diagnostic accuracy for differentiation was computed using receiver operating characteristic (ROC) curve analyses. Additional performed MRI or biopsies served as a standard of reference. RESULTS: A total of 136 lesions (51 metastases, 71 cysts, and 14 hemangiomas) in contrast-enhanced DECT images were evaluated. The most notable discrepancy (p < 0.001) between measured values and the highest diagnostic accuracy for distinguishing melanoma metastases from benign cysts was observed for the Z (0.992; 95% CI, 0.956-1) parameters, followed by Rho (0.908; 95% CI, 0.842-0.953) and finally HU120kV (0.829; 95% CI, 0.751-0.891). Conversely, when discriminating between liver metastases and hemangiomas, the HU120kV parameters showed the most significant difference (p < 0.001) and yielded the highest values for diagnostic accuracy (0.859; 95% CI, 0.740-0.937), followed by the Z parameters (0.790; 95% CI, 0.681-0.876) and finally the Rho values (0.621; 95% CI, 0.501-0.730). CONCLUSIONS: Rho and Z measurements derived from DECT allow for improved differentiation of liver metastases and benign liver cysts in patients with malignant melanoma compared to conventional CT value measurements. In contrast, in differentiation between liver hemangiomas and metastases, Rho/Z maps show inferior diagnostic accuracy. Therefore, differentiation between these two lesions remains a challenge for CT imaging.

Coronary Artery Disease Assessment via On-Site CT Fractional Flow Reserve in Patients Undergoing Transcatheter Aortic Valve Replacement.

Purpose To examine the clinical feasibility of workstation-based CT fractional flow reserve (CT-FFR) for coronary artery disease (CAD) evaluation during preprocedural planning in patients undergoing transcatheter aortic valve replacement (TAVR). Materials and Methods In this retrospective single-center study, 434 patients scheduled for TAVR between 2018 and 2020 were screened for study inclusion; a relevant proportion of patients (35.0% [152 of 434]) was not suitable for evaluation due to insufficient imaging properties. A total of 112 patients (mean age, 82.1 years ± 6.7 [SD]; 58 [52%] men) were included in the study. Invasive angiography findings, coronary CT angiography results, and Agatston score were acquired and compared with on-site CT-FFR computation for evaluation of CAD and prediction of major adverse cardiovascular events (MACE) within a 24-month follow-up. Results Hemodynamic relevant CAD, as suggested by CT-FFR of 0.80 or less, was found in 41 of 70 (59%) patients with stenosis of 50% or more. MACE occurred in 23 of 112 (20.5%) patients, from which 14 of 23 had stenoses with CT-FFR of 0.80 or less (hazard ratio [HR], 3.33; 95% CI: 1.56, 7.10; P = .002). CT-FFR remained a significant predictor of MACE after inclusion in a multivariable model with relevant covariables (HR, 2.89; 95% CI: 1.22, 6.86; P = .02). An Agatston score of 1000 Agatston units or more (HR, 2.25; 95% CI: 0.98, 5.21; P = .06) and stenoses of 50% or more determined via invasive angiography (HR, 0.94; 95% CI: 0.41, 2.17; P = .88) were not significant predictors of MACE. Conclusion Compared with conventional CAD markers, CT-FFR better predicted adverse outcomes after TAVR. A relevant portion of the screened cohort, however, was not suitable for CT-based CAD evaluation. Keywords: CT, Transcatheter Aortic Valve Implantation/Replacement (TAVI/TAVR), Cardiac, Coronary Arteries, Outcomes Analysis © RSNA, 2024 See also the commentary by Weir-McCall and Pugliese in this issue.

Value of Dual-Energy CT-Derived Metrics for the Prediction of Bone Non-union in Distal Radius Fractures.

RATIONALE AND OBJECTIVES: Bone non-union is a serious complication of distal radius fractures (DRF) that can result in functional limitations and persistent pain. However, no accepted method has been established to identify patients at risk of developing bone non-union yet. This study aimed to compare various CT-derived metrics for bone mineral density (BMD) assessment to identify predictive values for the development of bone non-union. MATERIALS AND METHODS: CT images of 192 patients with DRFs who underwent unenhanced dual-energy CT (DECT) of the distal radius between 03/2016 and 12/2020 were retrospectively identified. Available follow-up imaging and medical health records were evaluated to determine the occurrence of bone non-union. DECT-based BMD, trabecular Hounsfield unit (HU), cortical HU and cortical thickness ratio were measured in normalized non-fractured segments of the distal radius. RESULTS: Patients who developed bone non-union were significantly older (median age 72 years vs. 54 years) and had a significantly lower DECT-based BMD (median 68.1 mg/cm3 vs. 94.6 mg/cm3, p < 0.001). Other metrics (cortical thickness ratio, cortical HU, trabecular HU) showed no significant differences. ROC and PR curve analyses confirmed the highest diagnostic accuracy for DECT-based BMD with an area under the curve (AUC) of 0.83 for the ROC curve and an AUC of 0.46 for the PR curve. In logistic regression models, DECT-based BMD was the sole metric significantly associated with bone non-union. CONCLUSION: DECT-derived metrics can accurately predict bone non-union in patients who sustained DRF. The diagnostic performance of DECT-based BMD is superior to that of HU-based metrics and cortical thickness ratio.

Potential of Dual-Energy CT-Based Collagen Maps for the Assessment of Disk Degeneration in the Lumbar Spine.

RATIONALE AND OBJECTIVES: Lumbar disk degeneration is a common condition contributing significantly to back pain. The objective of the study was to evaluate the potential of dual-energy CT (DECT)-derived collagen maps for the assessment of lumbar disk degeneration. PATIENTS AND METHODS: We conducted a retrospective analysis of 127 patients who underwent dual-source DECT and MRI of the lumbar spine between 07/2019 and 10/2022. The level of lumbar disk degeneration was categorized by three radiologists as follows: no/mild (Pfirrmann 1&2), moderate (Pfirrmann 3&4), and severe (Pfirrmann 5). Recall (sensitivity) and accuracy of DECT collagen maps were calculated. Intraclass correlation coefficient (ICC) was used to evaluate inter-reader reliability. Subjective evaluations were performed using 5-point Likert scales for diagnostic confidence and image quality. RESULTS: We evaluated a total of 762 intervertebral disks from 127 patients (median age, 69.7 (range, 23.0-93.7), female, 56). MRI identified 230 non/mildly degenerated disks (30.2%), 484 moderately degenerated disks (63.5%), and 48 severely degenerated disks (6.3%). DECT collagen maps yielded an overall accuracy of 85.5% (1955/2286). Recall (sensitivity) was 79.3% (547/690) for the detection of no/mild lumbar disk degeneration, 88.7% (1288/1452) for the detection of moderate disk degeneration, and 83.3% (120/144) for the detection of severe disk degeneration (ICC=0.9). Subjective evaluations of DECT collagen maps showed high diagnostic confidence (median 4) and good image quality (median 4). CONCLUSION: The use of DECT collagen maps to distinguish different stages of lumbar disk degeneration may have clinical significance in the early diagnosis of disk-related pathologies in patients with contraindications for MRI or in cases of unavailability of MRI.

Dual-Energy CT Material Decomposition: The Value in the Detection of Lymph Node Metastasis from Breast Cancer.

PURPOSE: To evaluate the diagnostic performance of a dual-energy computed tomography (DECT)-based material decomposition algorithm for iodine quantification and fat fraction analysis to detect lymph node metastases in breast cancer patients. MATERIALS AND METHODS: 30 female patients (mean age, 63.12 ± 14.2 years) diagnosed with breast cancer who underwent pre-operative chest DECT were included. To establish a reference standard, the study correlated histologic repots after lymphadenectomy or confirming metastasis in previous/follow-up examinations. Iodine concentration and fat fraction were determined through region-of-interest measurements on venous DECT iodine maps. Receiver operating characteristic curve analysis was conducted to identify the optimal threshold for differentiating between metastatic and non-metastatic lymph nodes. RESULTS: A total of 168 lymph nodes were evaluated, divided into axillary (metastatic: 46, normal: 101) and intramammary (metastatic: 10, normal: 11). DECT-based fat fraction values exhibited significant differences between metastatic (9.56 ± 6.20%) and non-metastatic lymph nodes (41.52 ± 19.97%) (p < 0.0001). Absolute iodine concentrations showed no significant differences (2.25 ± 0.97 mg/mL vs. 2.08 ± 0.97 mg/mL) (p = 0.7999). The optimal fat fraction threshold for diagnosing metastatic lymph nodes was determined to be 17.75%, offering a sensitivity of 98% and a specificity of 94%. CONCLUSIONS: DECT fat fraction analysis emerges as a promising method for identifying metastatic lymph nodes, overcoming the morpho-volumetric limitations of conventional CT regarding lymph node assessment. This innovative approach holds potential for improving pre-operative lymph node evaluation in breast cancer patients, offering enhanced diagnostic accuracy.

Dual-Energy CT Iodine Uptake of Head and Neck: Definition of Reference Values in a Big Data Cohort.

BACKGROUND: Despite a considerable amount of literature on dual-energy CT (DECT) iodine uptake of the head and neck, the physiologic iodine uptake of this region has not been defined yet. This study aims to establish reference values for the iodine uptake of healthy organs to facilitate clinical application. METHODS: Consecutive venous DECT scans of the head and neck were reviewed, and unremarkable exams were included (n = 617). A total of 35 region of interest measurements were performed in 16 anatomical regions. Iodine uptake was compared among different organs/tissues and subgroup analysis was performed (male (n = 403) vs. female (n = 214); young (n = 207) vs. middle-aged (n = 206) vs. old (n = 204); and normal weight (n = 314) vs. overweight (n = 196) vs. obese (n = 107)). RESULTS: Overall mean iodine uptake values ranged between 0.5 and 9.4 mg/mL. Women showed higher iodine concentrations in the cervical vessels and higher uptake for the parotid gland, masseter muscle, submandibular glands, sublingual glands, palatine tonsils, tongue body, thyroid gland, and the sternocleidomastoid muscle than men (p ≤ 0.04). With increasing age, intravascular iodine concentrations increased as well as iodine uptake for cerebellum and thyroid gland, while values for the tongue and palatine tonsils were lower compared to younger subjects (p ≤ 0.03). Iodine concentrations for parotid glands and sternocleidomastoid muscles decreased with a higher BMI (p ≤ 0.004), while normal-weighted patients showed higher iodine values inside the jugular veins, other cervical glands, and tonsils versus patients with a higher BMI (p ≤ 0.04). CONCLUSION: physiologic iodine uptake values of cervical organs and tissues show gender-, age-, and BMI-related differences, which should be considered in the clinical routine of head and neck DECT.

From pixels to prognosis: Imaging biomarkers for discrimination and outcome prediction of pulmonary embolism : Original Research Article.

PURPOSE: Recent advancements in medical imaging have transformed diagnostic assessments, offering exciting possibilities for extracting biomarker-based information. This study aims to investigate the capabilities of a machine learning classifier that incorporates dual-energy computed tomography (DECT) radiomics. The primary focus is on discerning and predicting outcomes related to pulmonary embolism (PE). METHODS: The study included 131 participants who underwent pulmonary artery DECT angiography between January 2015 and March 2022. Among them, 104 patients received the final diagnosis of PE and 27 patients served as a control group. A total of 107 radiomic features were extracted for every case based on DECT imaging. The dataset was divided into training and test sets for model development and validation. Stepwise feature reduction identified the most relevant features, which were used to train a gradient-boosted tree model. Receiver operating characteristics analysis and Cox regression tests assessed the association of texture features with overall survival. RESULTS: The trained machine learning classifier achieved a classification accuracy of 0.94 for identifying patients with acute PE with an area under the receiver operating characteristic curve of 0.91. Radiomics features could be valuable for predicting outcomes in patients with PE, demonstrating strong prognostic capabilities in survival prediction (c-index, 0.991 [0.979-1.00], p = 0.0001) with a median follow-up of 130 days (IQR, 38-720). Notably, the inclusion of clinical or DECT parameters did not enhance predictive performance. CONCLUSION: In conclusion, our study underscores the promising potential of leveraging radiomics on DECT imaging for the identification of patients with acute PE and predicting their outcomes. This approach has the potential to improve clinical decision-making and patient management, offering efficiencies in time and resources by utilizing existing DECT imaging without the need for an additional scoring system.

Indicators for Hospitalization in Acute Pulmonary Embolism: Uncover the Association Between D-dimer Levels, Thrombus Volume and Radiomics.

BACKGROUND: The advent of advanced computed tomography (CT) technology and the field of radiomics has opened up new avenues in diagnostic assessments. Increasingly, there is substantial evidence advocating for the incorporation of quantitative imaging biomarkers in the clinical decision-making process. This study aimed to examine the correlation between D-dimer levels and thrombus size in acute pulmonary embolism (PE) combining dual-energy CT (DECT) and radiomics and to investigate the diagnostic utility of a machine learning classifier based on dual-energy computed tomography (DECT) radiomics for identifying patients with a complicated course, defined as at least hospitalization at IMC. METHODS: The study was conducted including 136 participants who underwent pulmonary artery CT angiography from January 2015 to March 2022. Based on DECT imaging, 107 radiomic features were extracted for each patient using standardized image processing. After dividing the dataset into training and test sets, stepwise feature reduction based on reproducibility, variable importance and correlation analyses were performed to select the most relevant features; these were used to train and validate the gradient-boosted tree models.Receiver operating characteristics (ROC) analysis was utilized to evaluate the association between volumetric, laboratory data and adverse outcomes. RESULTS: In the central PE group, we observed a significant correlation between thrombus volumetrics and D-dimer levels (p = 0.0037), as well as between thrombus volumetrics and hospitalization at the Intermediate Care Unit (IMC) (p = 0.0001). In contrast, no statistically significant differences were identified in thrombus sizes between patients who experienced complications and those who had a favorable course (p = 0.3162). The trained machine learning classifier achieved an accuracy of 61% and 55% in identifying patients with a complicated course, as indicated by an area under the ROC curve of 0.63 and 0.58. CONCLUSION: In conclusion, our findings indicate a positive correlation between D-dimer levels and central PE's pulmonary embolic burden. Thrombus volumetrics may serve as an indicator for complications and outcomes in acute PE patients. Thus, thrombus volumetrics, as opposed to D-dimers, could be an additional marker for evaluating embolic disease severity. Moreover, DECT-derived radiomic feature models show promise in identifying patients with a complicated course, such as hospitalization at IMC.

Incident fractures of the distal radius: Dual-energy CT-derived metrics for opportunistic risk stratification.

BACKGROUND: Dual-energy CT (DECT)-derived bone mineral density (BMD) of the distal radius and other CT-derived metrics related to bone health have been suggested for opportunistic osteoporosis screening and risk evaluation for sustaining distal radius fractures (DRFs). METHODS: The distal radius of patients who underwent DECT between 01/2016 and 08/2021 was retrospectively analyzed. Cortical Hounsfield Unit (HU), trabecular HU, cortical thickness, and DECT-based BMD were acquired from a non-fractured, metaphyseal area in all examinations. Receiver-operating characteristic (ROC) analysis was conducted to determine the area under the curve (AUC) values for predicting DRFs based on DECT-derived BMD, HU values, and cortical thickness. Logistic regression models were then employed to assess the associations of these parameters with the occurrence of DRFs. RESULTS: In this study, 263 patients (median age: 52 years; interquartile range: 36-64; 132 women; 192 fractures) were included. ROC curve analysis revealed a higher area under the curve (AUC) value for DECT-derived BMD compared to cortical HU, trabecular HU, and cortical thickness (0.91 vs. 0.61, 0.64, and 0.69, respectively; p <.001). Logistic regression models confirmed the association between lower DECT-derived BMD and the occurrence of DRFs (Odds Ratio, 0.83; p <.001); however, no influence was observed for cortical HU, trabecular HU, or cortical thickness. CONCLUSIONS: DECT can be used to assess the BMD of the distal radius without dedicated equipment such as calibration phantoms to increase the detection rates of osteoporosis and stratify the individual risk to sustain DRFs. In contrast, assessing HU-based values and cortical thickness does not provide clinical benefit.

CT-guided core needle biopsies of head and neck tumors: a comprehensive monocenter analysis of safety and outcomes.

BACKGROUND: Although core needle biopsy is an important tool in minimally invasive tissue sampling and diagnostics for head and neck masses, comprehensive data about safety and outcomes is lacking. PURPOSE: To retrospectively evaluate the diagnostic performance and safety of computed tomography (CT)-guided percutaneous core needle biopsy of head and neck masses. MATERIAL AND METHODS: This retrospective single-center study included patients from 04/2007 to 12/2021, and a total of 156 core needle biopsies were evaluated. The initial histopathological results were compared with the long-term final diagnosis to evaluate the diagnostic yield of CT-guided core needle biopsies. The patients' age, sex, and history of malignancy, as well as procedural complications and radiation exposure were collected. RESULTS: A total of 156 biopsies of 150 patients (mean age 56 years ± 17; 89 men) were evaluated. 57.3% (86/150) of patients had a history of malignancy. 55.1% (86/156) of the lesions were accessed by an infrahyoid needle approach. 92.9% (145/156) of biopsies yielded conclusive results. There were no false positives and 4 false negatives, resulting in a total false negative rate of 2.7% (4/145) and a total diagnostic yield of 90.4% (141/156). There were nine puncture-related complications (9/156-5.7%). None of the complications required further reintervention. The average dose length product was 311.3 mGy × cm. CONCLUSION: CT-guided core needle biopsies of head and neck masses showed excellent results with high diagnostic yield and clinical safety. CLINICAL RELEVANCE STATEMENT: General anesthesia for open biopsy carries a higher risk for elderly patients, and fine needle aspiration has a poor reputation in terms of its diagnostic yield. This study focuses on safety and diagnostic yield of CT-guided core needle biopsies. KEY POINTS: • CT-guided core needle biopsy in head and neck tumors was a reliable and safe procedure. • The most common cause for an inconclusive biopsy result was a shortage of tissue collected during the biopsy. • During our study period of nearly 15 years, the radiation exposure of head and neck biopsies decreased.

Imaging-based risk stratification of patients with pulmonary embolism based on dual-energy CT-derived radiomics.

BACKGROUND: Technological progress in the acquisition of medical images and the extraction of underlying quantitative imaging data has introduced exciting prospects for the diagnostic assessment of a wide range of conditions. This study aims to investigate the diagnostic utility of a machine learning classifier based on dual-energy computed tomography (DECT) radiomics for classifying pulmonary embolism (PE) severity and assessing the risk for early death. METHODS: Patients who underwent CT pulmonary angiogram (CTPA) between January 2015 and March 2022 were considered for inclusion in this study. Based on DECT imaging, 107 radiomic features were extracted for each patient using standardized image processing. After dividing the dataset into training and test sets, stepwise feature reduction based on reproducibility, variable importance and correlation analyses were performed to select the most relevant features; these were used to train and validate the gradient-boosted tree models. RESULTS: The trained machine learning classifier achieved a classification accuracy of .90 for identifying high-risk PE patients with an area under the receiver operating characteristic curve of .59. This CT-based radiomics signature showed good diagnostic accuracy for risk stratification in individuals presenting with central PE, particularly within higher risk groups. CONCLUSION: Models utilizing DECT-derived radiomics features can accurately stratify patients with pulmonary embolism into established clinical risk scores. This approach holds the potential to enhance patient management and optimize patient flow by assisting in the clinical decision-making process. It also offers the advantage of saving time and resources by leveraging existing imaging to eliminate the necessity for manual clinical scoring.

Diagnostic performance of modern computed tomography in cruciate ligament injury detection: A comprehensive study.

BACKGROUND: This study aimed to evaluate the clinical utility of modern single and dual-energy computed tomography (CT) for assessing the integrity of the cruciate ligaments in patients that sustained acute trauma. METHODS: Patients who underwent single- or dual-energy CT followed by 3 Tesla magnetic resonance imaging (MRI) or knee joint arthroscopy between 01/2016 and 12/2022 were included in this retrospective, monocentric study. Three radiologists specialized in musculoskeletal imaging independently evaluated all CT images for the presence of injury to the cruciate ligaments. An MRI consensus reading of two experienced readers and arthroscopy provided the reference standard. Diagnostic accuracy parameters and area under the receiver operator characteristic curve (AUC) were the primary metrics for diagnostic performance. RESULTS: CT images of 204 patients (median age, 49 years; IQR 36 - 64; 113 males) were evaluated. Dual-energy CT yielded significantly higher diagnostic accuracy and AUC for the detection of injury to the anterior (94% [240/255] vs 75% [266/357] and 0.89 vs 0.66) and posterior cruciate ligaments (95% [243/255] vs 87% [311/357] and 0.90 vs 0.61) compared to single-energy CT (all parameters, p <.005). Diagnostic confidence and image quality were significantly higher in dual-energy CT compared to single-energy CT (all parameters, p <.005). CONCLUSIONS: Modern dual-energy CT is readily available and can serve as a screening tool for detecting or excluding cruciate ligament injuries in patients with acute trauma. Accurate diagnosis of cruciate ligament injuries is crucial to prevent adverse outcomes, including delayed treatment, chronic instability, or long-term functional limitations.

Does Dual-Energy Computed Tomography Material Decomposition Improve Radiomics Capability to Predict Survival in Head and Neck Squamous Cell Carcinoma Patients? A Preliminary Investigation.

OBJECTIVE: Our study objective was to explore the additional value of dual-energy CT (DECT) material decomposition for squamous cell carcinoma of the head and neck (SCCHN) survival prognostication. METHODS: A group of 50 SCCHN patients (male, 37; female, 13; mean age, 63.6 ± 10.82 years) with baseline head and neck DECT between September 2014 and August 2020 were retrospectively included. Primary tumors were segmented, radiomics features were extracted, and DECT material decomposition was performed. We used independent train and validation datasets with cross-validation and 100 independent iterations to identify prognostic signatures applying elastic net (EN) and random survival forest (RSF). Features were ranked and intercorrelated according to their prognostic importance. We benchmarked the models against clinical parameters. Intraclass correlation coefficients were used to analyze the interreader variation. RESULTS: The exclusively radiomics-trained models achieved similar ( P = 0.947) prognostic performance of area under the curve (AUC) = 0.784 (95% confidence interval [CI], 0.775-0.812) (EN) and AUC = 0.785 (95% CI, 0.759-0.812) (RSF). The additional application of DECT material decomposition did not improve the model's performance (EN, P = 0.594; RSF, P = 0.198). In the clinical benchmark, the top averaged AUC value of 0.643 (95% CI, 0.611-0.675) was inferior to the quantitative imaging-biomarker models ( P < 0.001). A combined imaging and clinical model did not improve the imaging-based models ( P > 0.101). Shape features revealed high prognostic importance. CONCLUSIONS: Radiomics AI applications may be used for SCCHN survival prognostication, but the spectral information of DECT material decomposition did not improve the model's performance in our preliminary investigation.

Comparison of Microwave and Radiofrequency Ablation for the Treatment of Small- and Medium-Sized Hepatocellular Carcinomas in a Prospective Randomized Trial.

PURPOSE: To compare the therapeutic response and clinical outcome of CT-guided percutaneous microwave (MWA) and radiofrequency ablation (RFA) for the treatment of small- and medium-sized HCC. MATERIALS AND METHODS: In this prospective trial, 50 patients with HCC were randomly assigned to MWA or RFA treatment. MRI was performed 24 h before and after ablation and subsequently in 3-month intervals. Ablation volumes, ablation durations, adverse events (AE), technique efficacy, technical success, local tumor progression (LTP), disease-free survival (DFS), intrahepatic distant recurrence (IDR), and overall survival (OS) rates were evaluated. RESULTS: The mean ablation volume was 66.5 cm³ for MWA and 29.2  cm³ for RFA (p < 0.01). The mean ablation durations for MWA and RFA were 11.2 ±â€Š4.0 min and 16.3 ±â€Š4.7 min, respectively (p < 0.01). Six mild AEs were documented (p > 0.05). All treatments had a technical success rate and a technique efficacy rate of 100 % (50/50, p = 1.00). LTP within 2 years occurred in 1/25 (4 %) in the MWA group and in 4/25 (16 %) in the RFA group (p = 0.06). IDR within 2 years was 8/25 (32 %) for MWA and 14/25 (56 %) for RFA (p < 0.05). The median DFS was 24.5 months and 13.4 months for MWA and RFA, respectively (p = 0.02). The 1-, 2-, 3-year OS rates were 100 %, 80 %, 72 % in the MWA group and 72 %, 64 %, 60 % in the RFA group, respectively (p ≥ 0.14). CONCLUSION: The clinical outcome after MWA or RFA for HCC treatment was very similar with no significant differences in LTP or OS. However, MWA shows a trend toward better DFS with fewer IDRs than RFA. KEY POINTS: · MWA allows for larger ablation volumes and a shorter treatment duration compared to RFA in patients with HCC.. · MWA shows a trend toward better disease-free survival and fewer intrahepatic distant recurrences compared to RFA.. · The three-year survival rates show no significant difference between the two methods..

Improved Coronary Artery Visualization Using Virtual Monoenergetic Imaging from Dual-Layer Spectral Detector CT Angiography.

Background: To evaluate if coronary CT angiography (CCTA) monoenergetic reconstructions, obtained with a dual-layer spectral detector computed tomography (DLCT) system, offer improved image quality compared with 120 kVp conventional images without affecting the quantitative assessment of coronary stenoses. Methods: Fifty CCTA datasets (30 men; mean age: 61.6 ± 12.3 years) acquired with a DLCT system were reconstructed using virtual monoenergetic images (VMI) from 40 to 100 keV with 10 keV increment and compared with conventional images. An analysis of objective image quality was performed, evaluating the signal- and contrast-to-noise ratio. For the subjective assessment, two readers used a 5-point Likert scoring system to evaluate sharpness, noise, demarcation of coronary plaques, vascular contrast, and an overall score. Furthermore, coronary stenoses were analyzed for each vessel to describe the diagnostic agreement between monoenergetic images and conventional images. Results: The objective image analysis showed that all reconstructions from 70 keV to 40 keV show higher SNR (from 61.33 ± 12.46 to 154.22 ± 42.91, respectively) and CNR (from 51.45 ± 11.19 to 135.63 ± 39.38, respectively) compared with conventional images (all p < 0.001). The 40 keV monoenergetic images obtained the best average score for sharpness, vascular contrast, and for the overall impression (all with p < 0.001). The detection and grading of stenoses of the coronary arteries with conventional and monoenergetic images at 70 keV and 40 keV showed an overall excellent interobserver agreement (k= 0.81 [0.72-0.91]). Conclusions: The 40 keV virtual monoenergetic images obtained with a DLCT system allow the objective and subjective image quality of coronary CT angiography to be improved.

Dual-Energy CT-based Opportunistic Volumetric Bone Mineral Density Assessment of the Distal Radius.

Background In patients with distal radius fractures (DRFs), low bone mineral density (BMD) is associated with bone substitute use during surgery and bone nonunion, but BMD information is not regularly available. Purpose To evaluate the feasibility of dual-energy CT (DECT)-based BMD assessment from routine examinations in the distal radius and the relationship between the obtained BMD values, the occurrence of DRFs, bone nonunion, and use of surgical bone substitute. Materials and Methods Scans in patients who underwent routine dual-source DECT in the distal radius between January 2016 and December 2021 were retrospectively acquired. Phantomless BMD assessment was performed using the delineated trabecular bone of a nonfractured segment of the distal radius and both DECT image series. CT images and health records were examined to determine fracture severity, surgical management, and the occurrence of bone nonunion. Associations of BMD with the occurrence of DRFs, bone nonunion, and bone substitute use at surgical treatment were examined with generalized additive models and receiver operating characteristic analysis. Results This study included 263 patients (median age, 52 years; IQR, 36-64 years; 132 female patients), of whom 192 were diagnosed with fractures. Mean volumetric BMD was lower in patients who sustained a DRF (93.9 mg/cm3 vs 135.4 mg/cm3; P < .001), required bone substitutes (79.6 mg/cm3 vs 95.5 mg/cm3; P < .001), and developed bone nonunion (71.1 mg/cm3 vs 96.5 mg/cm3; P < .001). Receiver operating characteristic curve analysis identified these patients with an area under the curve of 0.71-0.91 (P < .001). Lower BMD increased the risk to sustain DRFs, develop bone nonunion, and receive bone substitutes at surgery (P < .001). Conclusion DECT-based BMD assessment at routine examinations is feasible and could help predict surgical bone substitute use and the occurrence of bone nonunion in patients with DRFs. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Carrino in this issue.

Advanced biomedical imaging for accurate discrimination and prognostication of mediastinal masses.

BACKGROUND: To investigate the potential of radiomic features and dual-source dual-energy CT (DECT) parameters in differentiating between benign and malignant mediastinal masses and predicting patient outcomes. METHODS: In this retrospective study, we analysed data from 90 patients (38 females, mean age 51 ± 25 years) with confirmed mediastinal masses who underwent contrast-enhanced DECT. Attenuation, radiomic features and DECT-derived imaging parameters were evaluated by two experienced readers. We performed analysis of variance (ANOVA) and Chi-square statistic tests for data comparison. Receiver operating characteristic curve analysis and Cox regression tests were used to differentiate between mediastinal masses. RESULTS: Of the 90 mediastinal masses, 49 (54%) were benign, including cases of thymic hyperplasia/thymic rebound (n = 10), mediastinitis (n = 16) and thymoma (n = 23). The remaining 41 (46%) lesions were classified as malignant, consisting of lymphoma (n = 28), mediastinal tumour (n = 4) and thymic carcinoma (n = 9). Significant differences were observed between benign and malignant mediastinal masses in all DECT-derived parameters (p ≤ .001) and 38 radiomic features (p ≤ .044) obtained from contrast-enhanced DECT. The combination of these methods achieved an area under the curve of .98 (95% CI, .893-1.000; p < .001) to differentiate between benign and malignant masses, with 100% sensitivity and 91% specificity. Throughout a follow-up of 1800 days, a multiparametric model incorporating radiomic features, DECT parameters and gender showed promising prognostic power in predicting all-cause mortality (c-index = .8 [95% CI, .702-.890], p < .001). CONCLUSIONS: A multiparametric approach combining radiomic features and DECT-derived imaging biomarkers allows for accurate and noninvasive differentiation between benign and malignant masses in the anterior mediastinum.

Injury patterns of the spine following blunt trauma: A per-segment analysis of spinal structures and their detection rates in CT and MRI.

Rationale and objectives: To provide a detailed analysis of injury patterns of the spine following blunt trauma and establish the role of supplementary MRI by evaluating discrepancies in the detection rates of damaged structures in CT and MRI. Method: 216 patients with blunt trauma to the spine who underwent CT followed by supplementary MRI were included in this study. Two board-certified radiologists blinded to clinical symptoms and injury mechanisms independently interpreted all acquired CT and MRI images. The interpretation was performed using a dedicated catalogue of typical findings associated with spinal trauma and assessed for spinal stability using the AO classification systems. Results: Lesions to structures associated with spinal instability were present in 31.0% in the cervical spine, 12.3% in the thoracic spine, and 29.9% in the lumbar spine. In all spinal segments, MRI provided additional information regarding potentially unstable injuries. Novel information derived from supplementary MRI changed clinical management in 3.6% of patients with injury to the cervical spine. No change in clinical management resulted from novel information on the thoracolumbar spine. Patients with injuries to the vertebral body, intervertebral disc, or spinous process were significantly more likely to benefit from supplementary MRI. Conclusion: In patients that sustained blunt spinal trauma, supplementary MRI of the cervical spine should routinely be performed to detect injuries that require surgical treatment, whereas CT is the superior imaging modality for the detection of unstable injuries in the thoracolumbar spine.