Potential radiation dose reduction in clinical photon-counting CT by the small pixel effect: ultra-high resolution (UHR) acquisitions reconstructed to standard resolution.

OBJECTIVE: To assess the potential dose reduction achievable with clinical photon-counting CT (PCCT) in ultra-high resolution (UHR) mode compared to acquisitions using the standard resolution detector mode (Std). MATERIALS AND METHODS: With smaller detector pixels, PCCT achieves far higher spatial resolution than energy-integrating (EI) CT systems. The reconstruction of UHR acquisitions to the lower spatial resolution of conventional systems results in an image noise and radiation dose reduction. We quantify this small pixel effect in measurements of semi-anthropomorphic abdominal phantoms of different sizes as well as in a porcine knuckle in the first clinical PCCT system by using the UHR mode (0.2 mm pixel size at isocenter) in comparison to the standard resolution mode (0.4 mm). At different slice thicknesses (0.4 up to 4 mm) and dose levels between 4 and 12 mGy, reconstructions using filtered backprojection were performed to the same target spatial resolution, i.e., same modulation transfer function, using both detector modes. Image noise and the resulting potential dose reduction was quantified as a figure of merit. RESULTS: Images acquired using the UHR mode yield lower noise in comparison to acquisitions using standard pixels at the same resolution and noise level. This holds for sharper convolution kernels at the spatial resolution limit of the standard mode, e.g., up to a factor 3.2 in noise reduction and a resulting potential dose reduction of up to almost 90%. CONCLUSION: Using sharper convolution kernels, UHR acquisitions allow for a significant dose reduction compared to acquisitions using the standard detector mode. CLINICAL RELEVANCE: Acquisitions should always be performed using the ultra-high resolution detector mode, if possible, to benefit from the intrinsic noise and dose reduction. KEY POINTS: • Ionizing radiation used in computed tomography examinations is a concern to public health. • The ultra-high resolution of novel photon-counting systems can be invested towards a noise and dose reduction if only a spatial resolution below the resolution limit of the detector is desired. • Acquisitions should always be performed in ultra-high resolution mode, if possible, to benefit from an intrinsic dose reduction.

How subjective CT image quality assessment becomes surprisingly reliable: pairwise comparisons instead of Likert scale.

OBJECTIVES: The aim of this study is to improve the reliability of subjective IQ assessment using a pairwise comparison (PC) method instead of a Likert scale method in abdominal CT scans. METHODS: Abdominal CT scans (single-center) were retrospectively selected between September 2019 and February 2020 in a prior study. Sample variance in IQ was obtained by adding artificial noise using dedicated reconstruction software, including reconstructions with filtered backprojection and varying iterative reconstruction strengths. Two datasets (each n = 50) were composed with either higher or lower IQ variation with the 25 original scans being part of both datasets. Using in-house developed software, six observers (five radiologists, one resident) rated both datasets via both the PC method (forcing observers to choose preferred scans out of pairs of scans resulting in a ranking) and a 5-point Likert scale. The PC method was optimized using a sorting algorithm to minimize necessary comparisons. The inter- and intraobserver agreements were assessed for both methods with the intraclass correlation coefficient (ICC). RESULTS: Twenty-five patients (mean age 61 years ± 15.5; 56% men) were evaluated. The ICC for interobserver agreement for the high-variation dataset increased from 0.665 (95%CI 0.396-0.814) to 0.785 (95%CI 0.676-0.867) when the PC method was used instead of a Likert scale. For the low-variation dataset, the ICC increased from 0.276 (95%CI 0.034-0.500) to 0.562 (95%CI 0.337-0.729). Intraobserver agreement increased for four out of six observers. CONCLUSION: The PC method is more reliable for subjective IQ assessment indicated by improved inter- and intraobserver agreement. CLINICAL RELEVANCE STATEMENT: This study shows that the pairwise comparison method is a more reliable method for subjective image quality assessment. Improved reliability is of key importance for optimization studies, validation of automatic image quality assessment algorithms, and training of AI algorithms. KEY POINTS: • Subjective assessment of diagnostic image quality via Likert scale has limited reliability. • A pairwise comparison method improves the inter- and intraobserver agreement. • The pairwise comparison method is more reliable for CT optimization studies.

Assessing GPT-4 multimodal performance in radiological image analysis.

OBJECTIVES: This study aims to assess the performance of a multimodal artificial intelligence (AI) model capable of analyzing both images and textual data (GPT-4V), in interpreting radiological images. It focuses on a range of modalities, anatomical regions, and pathologies to explore the potential of zero-shot generative AI in enhancing diagnostic processes in radiology. METHODS: We analyzed 230 anonymized emergency room diagnostic images, consecutively collected over 1 week, using GPT-4V. Modalities included ultrasound (US), computerized tomography (CT), and X-ray images. The interpretations provided by GPT-4V were then compared with those of senior radiologists. This comparison aimed to evaluate the accuracy of GPT-4V in recognizing the imaging modality, anatomical region, and pathology present in the images. RESULTS: GPT-4V identified the imaging modality correctly in 100% of cases (221/221), the anatomical region in 87.1% (189/217), and the pathology in 35.2% (76/216). However, the model's performance varied significantly across different modalities, with anatomical region identification accuracy ranging from 60.9% (39/64) in US images to 97% (98/101) and 100% (52/52) in CT and X-ray images (p < 0.001). Similarly, pathology identification ranged from 9.1% (6/66) in US images to 36.4% (36/99) in CT and 66.7% (34/51) in X-ray images (p < 0.001). These variations indicate inconsistencies in GPT-4V's ability to interpret radiological images accurately. CONCLUSION: While the integration of AI in radiology, exemplified by multimodal GPT-4, offers promising avenues for diagnostic enhancement, the current capabilities of GPT-4V are not yet reliable for interpreting radiological images. This study underscores the necessity for ongoing development to achieve dependable performance in radiology diagnostics. CLINICAL RELEVANCE STATEMENT: Although GPT-4V shows promise in radiological image interpretation, its high diagnostic hallucination rate (> 40%) indicates it cannot be trusted for clinical use as a standalone tool. Improvements are necessary to enhance its reliability and ensure patient safety. KEY POINTS: GPT-4V's capability in analyzing images offers new clinical possibilities in radiology. GPT-4V excels in identifying imaging modalities but demonstrates inconsistent anatomy and pathology detection. Ongoing AI advancements are necessary to enhance diagnostic reliability in radiological applications.

CT image quality evaluation in the age of deep learning: trade-off between functionality and fidelity.

OBJECTIVE: To quantitatively compare DLIR and ASiR-V with realistic anatomical images. METHODS: CT scans of an anthropomorphic phantom were acquired using three routine protocols (brain, chest, and abdomen) at four dose levels, with images reconstructed at five levels of ASiR-V and three levels of DLIR. Noise power spectrum (NPS) was estimated using a difference image by subtracting two matching images from repeated scans. Using the max-dose FBP reconstruction as the ground truth, the structure similarity index (SSIM) and gradient magnitude (GM) of difference images were evaluated. Image noise magnitude (σ), frequency location of the NPS peak (fpeak), mean SSIM (MSSIM), and mean GM (MGM) were used as quantitative metrics to compare image quality, for each anatomical region, protocol, algorithm, dose level, and slice thickness. RESULTS: Image noise had a strong (R2 > 0.99) power law relationship with dose for all algorithms. For the abdomen and chest, fpeak shifted from 0.3 (FBP) down to 0.15 mm-1 (ASiR-V 100%) with increasing ASiR-V strength but remained 0.3 mm-1 for all DLIR levels. fpeak shifted down for the brain protocol with increasing DLIR levels. Three levels of DLIR produced similar image noise levels as ASiR-V 40%, 80%, and 100%, respectively. DLIR had lower MSSIM but higher MGM than ASiR-V while matching imaging noise. CONCLUSION: Compared to ASiR-V, DLIR presents trade-offs between functionality and fidelity: it has a noise texture closer to FBP and more edge enhancement, but reduced structure similarity. These trade-offs and unique protocol-dependent behaviors of DLIR should be considered during clinical implementation and deployment. KEY POINTS: • DLIR reconstructed images demonstrate closer noise texture and lower structure similarity to FBP while producing equivalent noise levels comparable to ASiR-V. • DLIR has additional edge enhancement as compared to ASiR-V. • DLIR has unique protocol-dependent behaviors that should be considered for clinical implementation.

Reproducibility of a combined artificial intelligence and optimal-surface graph-cut method to automate bronchial parameter extraction.

OBJECTIVES: Computed tomography (CT)-based bronchial parameters correlate with disease status. Segmentation and measurement of the bronchial lumen and walls usually require significant manpower. We evaluate the reproducibility of a deep learning and optimal-surface graph-cut method to automatically segment the airway lumen and wall, and calculate bronchial parameters. METHODS: A deep-learning airway segmentation model was newly trained on 24 Imaging in Lifelines (ImaLife) low-dose chest CT scans. This model was combined with an optimal-surface graph-cut for airway wall segmentation. These tools were used to calculate bronchial parameters in CT scans of 188 ImaLife participants with two scans an average of 3 months apart. Bronchial parameters were compared for reproducibility assessment, assuming no change between scans. RESULTS: Of 376 CT scans, 374 (99%) were successfully measured. Segmented airway trees contained a mean of 10 generations and 250 branches. The coefficient of determination (R2) for the luminal area (LA) ranged from 0.93 at the trachea to 0.68 at the 6th generation, decreasing to 0.51 at the 8th generation. Corresponding values for Wall Area Percentage (WAP) were 0.86, 0.67, and 0.42, respectively. Bland-Altman analysis of LA and WAP per generation demonstrated mean differences close to 0; limits of agreement (LoA) were narrow for WAP and Pi10 (± 3.7% of mean) and wider for LA (± 16.4-22.8% for 2-6th generations). From the 7th generation onwards, there was a sharp decrease in reproducibility and a widening LoA. CONCLUSION: The outlined approach for automatic bronchial parameter measurement on low-dose chest CT scans is a reliable way to assess the airway tree down to the 6th generation. STATEMENT ON CLINICAL RELEVANCE: This reliable and fully automatic pipeline for bronchial parameter measurement on low-dose CT scans has potential applications in screening for early disease and clinical tasks such as virtual bronchoscopy or surgical planning, while also enabling the exploration of bronchial parameters in large datasets. KEY POINTS: • Deep learning combined with optimal-surface graph-cut provides accurate airway lumen and wall segmentations on low-dose CT scans. • Analysis of repeat scans showed that the automated tools had moderate-to-good reproducibility of bronchial measurements down to the 6th generation airway. • Automated measurement of bronchial parameters enables the assessment of large datasets with less man-hours.

Does dual-layer spectral detector CT provide added value in predicting spread through air spaces in lung adenocarcinoma? A preliminary study.

OBJECTIVES: To examine the predictive value of dual-layer spectral detector CT (DLCT) for spread through air spaces (STAS) in clinical lung adenocarcinoma. METHODS: A total of 225 lung adenocarcinoma cases were retrospectively reviewed for demographic, clinical, pathological, traditional CT, and spectral parameters. Multivariable logistic regression analysis was carried out based on three logistic models, including a model using traditional CT features (traditional model), a model using spectral parameters (spectral model), and an integrated model combining traditional CT and spectral parameters (integrated model). Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were performed to assess these models. RESULTS: Univariable analysis showed significant differences between the STAS and non-STAS groups in traditional CT features, including nodule density (p < 0.001), pleural indentation types (p = 0.006), air-bronchogram sign (p = 0.031), the presence of spiculation (p < 0.001), long-axis diameter of the entire nodule (LD) (p < 0.001), and consolidation/tumor ratio (CTR) (p < 0.001). Multivariable analysis revealed that LD > 20 mm (odds ratio [OR] = 2.271, p = 0.025) and CTR (OR = 24.208, p < 0.001) were independent predictors in the traditional model, while electronic density (ED) in the venous phase was an independent predictor in the spectral (OR = 1.062, p < 0.001) and integrated (OR = 1.055, p < 0.001) models. The area under the curve (AUC) for the integrated model (0.84) was the highest (spectral model, 0.83; traditional model, 0.80), and the difference between the integrated and traditional models was statistically significant (p = 0.015). DCA showed that the integrated model had superior clinical value versus the traditional model. CONCLUSIONS: DLCT has added value for STAS prediction in lung adenocarcinoma. CLINICAL RELEVANCE STATEMENT: Spectral CT has added value for spread through air spaces prediction in lung adenocarcinoma so may impact treatment planning in the future. KEY POINTS: • Electronic density may be a potential spectral index for predicting spread through air spaces in lung adenocarcinoma. • A combination of spectral and traditional CT features enhances the performance of traditional CT for predicting spread through air spaces.

CT-based preoperative risk assessment of prolonged urine leak in patients undergoing partial nephrectomy.

OBJECTIVES: This study aims to evaluate risk factors of prolonged urine leak following partial nephrectomy (PN) to identify objective imaging characteristics on preoperative CT. METHODS: A total of 865 patients who underwent PN and had preoperative CT and postoperative imaging were included. We set a twofold size-matched control group without urine leak, with all tumors located ≤ 4 mm to the collecting system to identify imaging parameters that increase the risk of urine leak other than tumor size and location. Four CT parameters that show the relationship of the tumor and collecting system, namely, curvilinear border length, protruding distance, margin at the interface, and pelvicalyceal contact, were analyzed. Multivariate logistic regression analyses were performed to identify significant predictors of urine leak. The diagnostic performance of the significant parameters was evaluated using the area under the receiver operating characteristic curve (AUC). RESULTS: Fifty-three of 865 patients (6.1%) demonstrated urine leak. Compared with the control group, urine leak group showed longer curvilinear border length, longer protruding distance, frequent non-smooth contact interface, and frequent direct pelvicalyceal contact (p < 0.05 for all). In the multivariate analysis, pelvicalyceal contact was the independent predictor of urine leak (OR = 2.62; 95% C.I 1.02-6.63). Combining four CT parameters, an AUC of 0.70 with a sensitivity of 58.5% and a specificity of 79.2% for identifying urine leak after PN could be obtained. CONCLUSIONS: The four CT features that describe the relationship between the tumor and collecting system might be useful for evaluating the risk of urine leak before PN. KEY POINTS: • Four CT parameters (curvilinear border length, protruding distance, margin at the interface, and pelvicalyceal contact) were significantly associated with postoperative urine leak after partial nephrectomy. • A comprehensive preoperative imaging evaluation of the relationship between the tumor and renal sinus may help in selecting the optimal surgical options and afford better patient counseling of complication risk.

Dual-energy CT kidney stone characterization-can diagnostic accuracy be achieved at low radiation dose?

OBJECTIVES: To assess the accuracy of low-dose dual-energy computed tomography (DECT) to differentiate uric acid from non-uric acid kidney stones in two generations of dual-source DECT with stone composition analysis as the reference standard. METHODS: Patients who received a low-dose unenhanced DECT for the detection or follow-up of urolithiasis and stone extraction with stone composition analysis between January 2020 and January 2022 were retrospectively included. Collected stones were characterized using X-ray diffraction. Size, volume, CT attenuation, and stone characterization were assessed using DECT post-processing software. Characterization as uric acid or non-uric acid stones was compared to stone composition analysis as the reference standard. Sensitivity, specificity, and accuracy of stone classification were computed. Dose length product (DLP) and effective dose served as radiation dose estimates. RESULTS: A total of 227 stones in 203 patients were analyzed. Stone composition analysis identified 15 uric acid and 212 non-uric acid stones. Mean size and volume were 4.7 mm × 2.8 mm and 114 mm3, respectively. CT attenuation of uric acid stones was significantly lower as compared to non-uric acid stones (p < 0.001). Two hundred twenty-five of 227 kidney stones were correctly classified by DECT. Pooled sensitivity, specificity, and accuracy were 1.0 (95%CI: 0.97, 1.00), 0.93 (95%CI: 0.68, 1.00), and 0.99 (95%CI: 0.97, 1.00), respectively. Eighty-two of 84 stones with a diameter of ≤ 3 mm were correctly classified. Mean DLP was 162 ± 57 mGy*cm and effective dose was 2.43 ± 0.86 mSv. CONCLUSIONS: Low-dose dual-source DECT demonstrated high accuracy to discriminate uric acid from non-uric acid stones even at small stone sizes. KEY POINTS: • Two hundred twenty-five of 227 stones were correctly classified as uric acid vs. non-uric acid stones by low-dose dual-energy CT with stone composition analysis as the reference standard. • Pooled sensitivity, specificity, and accuracy for stone characterization were 1.0, 0.93, and 0.99, respectively. • Low-dose dual-energy CT for stone characterization was feasible in the majority of small stones < 3 mm.

Deep learning-based reconstruction can improve the image quality of low radiation dose head CT.

OBJECTIVES: To evaluate the image quality of deep learning-based reconstruction (DLR), model-based (MBIR), and hybrid iterative reconstruction (HIR) algorithms for lower-dose (LD) unenhanced head CT and compare it with those of standard-dose (STD) HIR images. METHODS: This retrospective study included 114 patients who underwent unenhanced head CT using the STD (n = 57) or LD (n = 57) protocol on a 320-row CT. STD images were reconstructed with HIR; LD images were reconstructed with HIR (LD-HIR), MBIR (LD-MBIR), and DLR (LD-DLR). The image noise, gray and white matter (GM-WM) contrast, and contrast-to-noise ratio (CNR) at the basal ganglia and posterior fossa levels were quantified. The noise magnitude, noise texture, GM-WM contrast, image sharpness, streak artifact, and subjective acceptability were independently scored by three radiologists (1 = worst, 5 = best). The lesion conspicuity of LD-HIR, LD-MBIR, and LD-DLR was ranked through side-by-side assessments (1 = worst, 3 = best). Reconstruction times of three algorithms were measured. RESULTS: The effective dose of LD was 25% lower than that of STD. Lower image noise, higher GM-WM contrast, and higher CNR were observed in LD-DLR and LD-MBIR than those in STD (all, p ≤ 0.035). Compared with STD, the noise texture, image sharpness, and subjective acceptability were inferior for LD-MBIR and superior for LD-DLR (all, p < 0.001). The lesion conspicuity of LD-DLR (2.9 ± 0.2) was higher than that of HIR (1.2 ± 0.3) and MBIR (1.8 ± 0.4) (all, p < 0.001). Reconstruction times of HIR, MBIR, and DLR were 11 ± 1, 319 ± 17, and 24 ± 1 s, respectively. CONCLUSION: DLR can enhance the image quality of head CT while preserving low radiation dose level and short reconstruction time. KEY POINTS: • For unenhanced head CT, DLR reduced the image noise and improved the GM-WM contrast and lesion delineation without sacrificing the natural noise texture and image sharpness relative to HIR. • The subjective and objective image quality of DLR was better than that of HIR even at 25% reduced dose without considerably increasing the image reconstruction times (24 s vs. 11 s). • Despite the strong noise reduction and improved GM-WM contrast performance, MBIR degraded the noise texture, sharpness, and subjective acceptance with prolonged reconstruction times relative to HIR, potentially hampering its feasibility.

Lung ultrasonography versus chest CT for assessing peripheric pulmonary lesions in hemorrhagic fever with renal syndrome: a prospective comparative study in China.

OBJECTIVES: To compare the performances of lung ultrasonography (LUS) versus chest CT for assessing peripheric pulmonary lesions in hemorrhagic fever with renal syndrome (HFRS). METHODS: Paired LUS and chest CT scan were prospectively performed and compared when in diagnosing five pathologies including region with alveolar-interstitial pattern (RAIP), alveolar-interstitial syndrome (AIS), lung consolidation, pleural effusion (PE), and pericardial effusion, in each patient with HFRS. RESULTS: Forty-four patients (aged 39.9 ± 15.0 years, 35 males) were included, from which 68 paired LUS and chest CT imaging data of 816 lung regions were obtained and analyzed. Compared with chest CT, LUS showed high sensitivity (92.19-100%) and negative predictive value (95.9-100%), but relatively low specificity (39.47-97.21%) and positive predictive value (37.5-76.47%) for diagnosing the above pathologies. McNemer's test showed LUS detected more positive findings than chest CT (all p ≤ 0.002). There was a strong correlation between LUS and chest CT scores (rs = 0.7141, p < 0.0001) and both scores correlated with the disease severity, hospital days, and partial laboratory profiles in HFRS patients. CONCLUSIONS: LUS was comparable with chest CT for diagnosing peripheric pulmonary lesions and clinical assessment in patients with HFRS. Given the high sensitivity and negative predictive value compared with chest CT, LUS can be used as an excellent rule-out tool in HFRS, while its use in rule-in still requires more evidence. Considering the obvious advantages of LUS being a bedside, less expansive, and non-radiating exam, future multi-center randomized LUS versus chest CT studies may help to guide the preferred method. KEY POINTS: • LUS could detect more positive findings than chest CT in assessing peripheric pulmonary lesions in patients with hemorrhagic fever with renal syndrome (HFRS). • Compared with chest CT, LUS showed high sensitivity but relatively low specificity when diagnosing the peripheric pulmonary lesions caused by HFRS. • Both LUS and chest CT scores correlated with the disease severity, hospital days, and partial laboratory profiles in HFRS.

Lung shrinking assessment on HRCT with elastic registration technique for monitoring idiopathic pulmonary fibrosis.

OBJECTIVES: Evaluation and follow-up of idiopathic pulmonary fibrosis (IPF) mainly rely on high-resolution computed tomography (HRCT) and pulmonary function tests (PFTs). The elastic registration technique can quantitatively assess lung shrinkage. We aimed to investigate the correlation between lung shrinkage and morphological and functional deterioration in IPF. METHODS: Patients with IPF who underwent at least two HRCT scans and PFTs were retrospectively included. Elastic registration was performed on the baseline and follow-up HRCTs to obtain deformation maps of the whole lung. Jacobian determinants were calculated from the deformation fields and after logarithm transformation, log_jac values were represented on color maps to describe morphological deterioration, and to assess the correlation between log_jac values and PFTs. RESULTS: A total of 69 patients with IPF (male 66) were included. Jacobian maps demonstrated constriction of the lung parenchyma marked at the lung base in patients who were deteriorated on visual and PFT assessment. The log_jac values were significantly reduced in the deteriorated patients compared to the stable patients. Mean log_jac values showed positive correlation with baseline percentage of predicted vital capacity (VC%) (r = 0.394, p < 0.05) and percentage of predicted forced vital capacity (FVC%) (r = 0.395, p < 0.05). Additionally, the mean log_jac values were positively correlated with pulmonary vascular volume (r = 0.438, p < 0.01) and the number of pulmonary vascular branches (r = 0.326, p < 0.01). CONCLUSIONS: Elastic registration between baseline and follow-up HRCT was helpful to quantitatively assess the morphological deterioration of lung shrinkage in IPF, and the quantitative indicator log_jac values were significantly correlated with PFTs. KEY POINTS: • The elastic registration on HRCT was helpful to quantitatively assess the deterioration of IPF. • Jacobian logarithm was significantly reduced in deteriorated patients and mean log_jac values were correlated with PFTs. • The mean log_jac values were related to the changes of pulmonary vascular volume and the number of vascular branches.

Efficacy of two opportunistic methods for screening osteoporosis in lumbar spine surgery patients.

PURPOSE: Hounsfield unit (HU) measurements and vertebral bone quality (VBQ) scores are opportunistic screening methods for evaluating bone quality. Since studies comparing the efficacies of the two methods are rare, this retrospective study aimed to examine the efficacy of VBQ scores compared with that of HU measurements for diagnosing osteoporosis in lumbar spine surgery patients. METHODS: We selected patients who had undergone spinal surgery between January 2020 and May 2022 from our database. The VBQ scores based on magnetic resonance imaging (MRI) and HU measurements based on computed tomography (CT) were calculated. Correlation analysis of the dual-energy X-ray absorptiometry (DEXA) T score and study parameters was performed. The Delong test and decision curve analysis (DCA) were used to compare the efficacies of the two methods. RESULTS: We included 118 consecutive patients who underwent selective spinal surgery. The VBQ score and HU measurement were significantly correlated with the DEXA T score. Based on the Delong test, HU measurement predicted osteoporosis more effectively than the VBQ score did. The DCA revealed that the VBQ score performed better than the HU measurement did. CONCLUSIONS: The calculation of VBQ scores is a novel opportunistic screening method for diagnosing osteoporosis; however, CT-based HU measurements outperform MRI-based VBQ scores. HU measurements can be used as a screening method when pre-operative CT scans are available.

Effect of Denosumab or Alendronic Acid on the Progression of Aortic Stenosis: A Double-Blind Randomized Controlled Trial.

BACKGROUND: Valvular calcification is central to the pathogenesis and progression of aortic stenosis, with preclinical and observational studies suggesting that bone turnover and osteoblastic differentiation of valvular interstitial cells are important contributory mechanisms. We aimed to establish whether inhibition of these pathways with denosumab or alendronic acid could reduce disease progression in aortic stenosis. METHODS: In a single-center, parallel group, double-blind randomized controlled trial, patients >50 years of age with calcific aortic stenosis (peak aortic jet velocity >2.5 m/s) were randomized 2:1:2:1 to denosumab (60 mg every 6 months), placebo injection, alendronic acid (70 mg once weekly), or placebo capsule. Participants underwent serial assessments with Doppler echocardiography, computed tomography aortic valve calcium scoring, and 18F-sodium fluoride positron emission tomography and computed tomography. The primary end point was the calculated 24-month change in aortic valve calcium score. RESULTS: A total of 150 patients (mean age, 72±8 years; 21% women) with calcific aortic stenosis (peak aortic jet velocity, 3.36 m/s [2.93-3.82 m/s]; aortic valve calcium score, 1152 AU [655-2065 AU]) were randomized and received the allocated trial intervention: denosumab (n=49), alendronic acid (n=51), and placebo (injection n=25, capsule n=25; pooled for analysis). Serum C-terminal telopeptide, a measure of bone turnover, halved from baseline to 6 months with denosumab (0.23 [0.18-0.33 µg/L] to 0.11 µg/L [0.08-0.17 µg/L]) and alendronic acid (0.20 [0.14-0.28 µg/L] to 0.09 µg/L [0.08-0.13 µg/L]) but was unchanged with placebo (0.23 [0.17-0.30 µg/L] to 0.26 µg/L [0.16-0.31 µg/L]). There were no differences in 24-month change in aortic valve calcium score between denosumab and placebo (343 [198-804 AU] versus 354 AU [76-675 AU]; P=0.41) or alendronic acid and placebo (326 [138-813 AU] versus 354 AU [76-675 AU]; P=0.49). Similarly, there were no differences in change in peak aortic jet velocity or 18F-sodium fluoride aortic valve uptake. CONCLUSIONS: Neither denosumab nor alendronic acid affected progression of aortic valve calcification in patients with calcific aortic stenosis. Alternative pathways and mechanisms need to be explored to identify disease-modifying therapies for the growing population of patients with this potentially fatal condition. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02132026.

Preoperative prediction of inadvertent enterotomy during adhesive small bowel obstruction surgery using combination of CT features.

OBJECTIVES: The purpose of this study was to identify the preoperative CT features that are associated with inadvertent enterotomy (IE) during adhesive small bowel obstruction (ASBO) surgery. METHODS: From January 2015 to December 2019, all patients with ASBO who underwent an abdominal CT were reviewed. Abdominal CT were retrospectively reviewed by two radiologists with a consensus read in case of disagreement. IE during ASBO surgery was retrospectively recorded. Univariate and multivariate analyses of CT features associated with IE were performed and a simple CT score was built to stratify the risk of IE. This score was validated in an independent retrospective cohort. Abdominal CT of the validation cohort was reviewed by a third independent reader. RESULTS: Among the 368 patients with ASBO during the study period, 169 were surgically treated, including 129 ASBO for single adhesive band and 40 for matted adhesions. Among these, there were 47 IE. By multivariate analysis, angulation of the transitional zone (OR = 4.19, 95% CI [1.10-18.09]), diffuse intestinal adhesions (OR = 4.87, 95% CI [1.37-19.76]), a fat notch sign (OR = 0.32, 95% CI [0.12-0.85]), and mesenteric haziness (OR = 0.13, 95% CI [0.03-0.48]) were independently associated with inadvertent enterotomy occurrence. The simple CT score built to stratify risk of IE displayed an AUC of 0.85 (95% CI [0.80-0.90]) in the study sample and 0.88 (95% CI [0.80-0.96]) in the validation cohort. CONCLUSION: A simple preoperative CT score is able to inform the surgeon about a high risk of IE and therefore influence the surgical procedure. KEY POINTS: • In this retrospective study of 169 patients undergoing abdominal surgery for adhesive small bowel obstruction, 47 (28%) inadvertent enterotomy occurred. • A simple preoperative CT score enables accurate stratification of inadvertent enterotomy risk (area under the curve 0.85). • By multivariable analysis, diffuse intestinal adhesions and angulation of the transitional zone were predictive of inadvertent enterotomy occurrence.

Air embolism in CT-guided transthoracic needle biopsy: emphasis on pulmonary vein injury.

OBJECTIVE: To assess whether pulmonary vein injury is detectable on CT and associated with air embolism after percutaneous transthoracic needle biopsy (PTNB) in a tertiary referral hospital. METHODS: Between January 2012 and November 2021, 11,691 consecutive CT-guided PTNBs in 10,685 patients were retrospectively evaluated. Air embolism was identified by reviewing radiologic reports. Pulmonary vein injury was defined as the presence of the pulmonary vein in the needle pathway or shooting range of the cutting needle with the presence of parenchymal hemorrhage. The association between pulmonary vein injury and air embolism was assessed using logistic regression analysis in matched patients with and without air embolism with a ratio of 1:4. RESULTS: A total of 27 cases of air embolism (median age, 67 years; range, 48-80 years; 24 men) were found with an incidence of 0.23% (27/11,691). Pulmonary vein injury during the procedures was identifiable on CT in 24 of 27 patients (88.9%), whereas it was 1.9% (2/108) for matched patients without air embolism The veins beyond the target lesion (70.8% [17/24]) were injured more frequently than the veins in the needle pathway before the target lesion (29.2% [7/24]). In univariable and multivariable analyses, pulmonary vein injury was associated with air embolism (odds ratio, 485.19; 95% confidence interval, 68.67-3428.19, p <.001). CONCLUSION: Pulmonary vein injury was detected on CT and was associated with air embolism. Avoiding pulmonary vein injury with careful planning of the needle pathway on CT may reduce air embolism risk. KEY POINTS: • Pulmonary vein injury during CT-guided biopsy was identifiable on CT in most of the patients (88.9% [24/27]). • The veins beyond the target lesion (70.8% [17/24]) were injured more frequently than the veins in the needle pathway before the target lesion (29.2% [7/24]). • Avoiding the distinguishable pulmonary vein along the pathway or shooting range of the needle on CT may reduce the air embolism risk.

Comparison of chest CT severity scoring systems for COVID-19.

PURPOSE: To compare the diagnostic performance and inter-observer agreement of five different CT chest severity scoring systems for COVID-19 to find the most precise one with the least interpretation time. METHODS AND MATERIALS: This retrospective study included 85 patients (54 male and 31 female) with PCR-confirmed COVID-19. They underwent CT to assess the severity of pulmonary involvement. Three readers were asked to assess the pulmonary abnormalities and score the severity using five different systems, including chest CT severity score (CT-SS), chest CT score, total severity score (TSS), modified total severity score (m-TSS), and 3-level chest CT severity score. Time consumption on reporting of each system was calculated. RESULTS: Two hundred fifty-five observations were reported for each system. There was a statistically significant inter-observer agreement in assessing qualitative lung involvement using the m-TSS and the other four quantitative systems. The ROC curves revealed excellent and very good diagnostic accuracy for all systems when cutoff values for detection severe cases were > 22, > 17, > 12, and > 26 for CT-SS, chest CT score, TSS, and 3-level CT severity score. The AUC was very good (0.86), excellent (0.90), very good (0.89), and very good (0.86), respectively. Chest CT score showed the highest specificity (95.2%) in discrimination of severe cases. Time consumption on reporting was significantly different (< 0.001): CT-SS > 3L-CT-SS > chest CT score > TSS. CONCLUSION: All chest CT severity scoring systems in this study demonstrated excellent inter-observer agreement and reasonable performance to assess COVID-19 in relation to the clinical severity. CT-SS and TSS had the highest specificity and least time for interpretation. KEY POINTS: • All chest CT severity scoring systems discussed in this study revealed excellent inter-observer agreement and reasonable performance to assess COVID-19 in relation to the clinical severity. • Chest CT scoring system and TSS had the highest specificity. • Both TSS and m-TSS consumed the least time compared to the other three scoring systems.

Diagnostic accuracy of color-coded virtual noncalcium reconstructions derived from portal venous phase dual-energy CT in the assessment of lumbar disk herniation.

OBJECTIVES: To investigate the diagnostic accuracy of color-coded contrast-enhanced dual-energy CT virtual noncalcium (VNCa) reconstructions for the assessment of lumbar disk herniation compared to unenhanced VNCa imaging. METHODS: A total of 91 patients were retrospectively evaluated (65 years ± 16; 43 women) who had undergone third-generation dual-source dual-energy CT and 3.0-T MRI within an examination interval up to 3 weeks between November 2019 and December 2020. Eight weeks after assessing unenhanced color-coded VNCa reconstructions for the presence and degree of lumbar disk herniation, corresponding contrast-enhanced portal venous phase color-coded VNCa reconstructions were independently analyzed by the same five radiologists. MRI series were additionally analyzed by one highly experienced musculoskeletal radiologist and served as reference standard. RESULTS: MRI depicted 210 herniated lumbar disks in 91 patients. VNCa reconstructions derived from contrast-enhanced CT scans showed similar high overall sensitivity (93% vs 95%), specificity (94% vs 95%), and accuracy (94% vs 95%) for the assessment of lumbar disk herniation compared to unenhanced VNCa images (all p > .05). Interrater agreement in VNCa imaging was excellent for both, unenhanced and contrast-enhanced CT (κ = 0.84 vs κ = 0.86; p > .05). Moreover, ratings for diagnostic confidence, image quality, and noise differed not significantly between unenhanced and contrast-enhanced VNCa series (all p > .05). CONCLUSIONS: Color-coded VNCa reconstructions derived from contrast-enhanced dual-energy CT yield similar diagnostic accuracy for the depiction of lumbar disk herniation compared to unenhanced VNCa imaging and therefore may improve opportunistic retrospective lumbar disk herniation assessment, particularly in case of staging CT examinations. KEY POINTS: • Color-coded dual-source dual-energy CT virtual noncalcium (VNCa) reconstructions derived from portal venous phase yield similar high diagnostic accuracy for the assessment of lumbar disk herniation compared to unenhanced VNCa CT series (94% vs 95%) with MRI serving as a standard of reference. • Diagnostic confidence, image quality, and noise levels differ not significantly between unenhanced and contrast-enhanced portal venous phase VNCa dual-energy CT series. • Dual-source dual-energy CT might have the potential to improve opportunistic retrospective lumbar disk herniation assessment in CT examinations performed for other indications through reconstruction of VNCa images.

Dual energy CT arthrography in shoulder instability: successful iodine removal with virtual non-contrast images and accurate 3D reformats of the glenoid for assessment of bone loss.

OBJECTIVE: To evaluate the image quality of dual energy CT (DECT) of the shoulder after arthrography and of virtual non-contrast (VNC) 3D reformats of the glenoid and to compare glenoid measurements on VNC 3D reformats and on 2D CTs. MATERIALS AND METHODS: DECT arthrography (80 kV/140 kV) was performed in 42 shoulders of 41 patients with instability using diluted iodinated contrast media (80 mg/ml). VNC images and VNC 3D reformats of the glenoid were calculated using image postprocessing. Dose parameters, CT values of intraarticular iodine and muscle, image contrast (iodine/muscle), and image quality (5-point scale: 1 = worst, 5 = best) were evaluated. Two independent readers assessed glenoid morphology and performed glenoid measurements on 2D and 3D images. RESULTS: Calculation of VNC images and VNC 3D reformats was successful in 42/42 shoulders (100%). The effective dose was mean 1.95 mSv (± 0.9 mSv). CT values of iodine and muscle were mean 1014.6 HU (± 235.8 HU) and 64.5 HU(± 8.6 HU), respectively, and image contrast was mean 950.2 HU (± 235.5 HU). Quality of cross-sectional images, VNC images, and VNC 3D reformats was rated good (median 4 (4-5), 4 (3-4), 4 (3-5), respectively). Detection of an osseous defect was equal on 2D and 3D images (13/42, P > 0.99) with no difference for measurement of the glenoid diameter with mean 28.3 mm (± 2.8 mm) vs. 28.4 mm (± 2.9 mm) (P = 0.5), width of the glenoid defect with 3.2 mm (± 2.1 mm) vs. 3.1 mm (± 2.3 mm) (P = 0.84), surface area with 638.5 mm2 (± 127 mm2) vs. 640.8 mm2 (± 129.5 mm2) (P = 0.47), and surface area of the defect with 46.6 mm2 (± 44.3 mm2) vs. 47.2 mm2 (± 48.0 mm2) (P = 0.73), respectively. CONCLUSION: DECT shoulder arthrography is feasible and allows successful iodine removal with generation of VNC images and accurate VNC 3D reformats of the glenoid for assessment of bone loss.

Computed tomography semi-automated lung volume quantification in SARS-CoV-2-related pneumonia.

OBJECTIVES: To evaluate a semi-automated segmentation and ventilated lung quantification on chest computed tomography (CT) to assess lung involvement in patients affected by SARS-CoV-2. Results were compared with clinical and functional parameters and outcomes. METHODS: All images underwent quantitative analyses with a dedicated workstation using a semi-automatic lung segmentation software to compute ventilated lung volume (VLV), Ground-glass opacity (GGO) volume (GGO-V), and consolidation volume (CONS-V) as absolute volume and as a percentage of total lung volume (TLV). The ratio between CONS-V, GGO-V, and VLV (CONS-V/VLV and GGO-V/VLV, respectively), TLV (CONS-V/TLV, GGO-V/TLV, and GGO-V + CONS-V/TLV respectively), and the ratio between VLV and TLV (VLV/TLV) were calculated. RESULTS: A total of 108 patients were enrolled. GGO-V/TLV significantly correlated with WBC (r = 0.369), neutrophils (r = 0.446), platelets (r = 0.182), CRP (r = 0.190), PaCO2 (r = 0.176), HCO3- (r = 0.284), and PaO2/FiO2 (P/F) values (r = - 0.344). CONS-V/TLV significantly correlated with WBC (r = 0.294), neutrophils (r = 0.300), lymphocytes (r = -0.225), CRP (r = 0.306), PaCO2 (r = 0.227), pH (r = 0.162), HCO3- (r = 0.394), and P/F (r = - 0.419) values. Statistically significant differences between CONS-V, GGO-V, GGO-V/TLV, CONS-V/TLV, GGO-V/VLV, CONS-V/VLV, GGO-V + CONS-V/TLV, VLV/TLV, CT score, and invasive ventilation by ET were found (all p < 0.05). CONCLUSION: The use of quantitative semi-automated algorithm for lung CT elaboration effectively correlates the severity of SARS-CoV-2-related pneumonia with laboratory parameters and the need for invasive ventilation. KEY POINTS: • Pathological lung volumes, expressed both as GGO-V and as CONS-V, can be considered a useful tool in SARS-CoV-2-related pneumonia. • All lung volumes, expressed themselves and as ratio with TLV and VLV, correlate with laboratory data, in particular C-reactive protein and white blood cell count. • All lung volumes correlate with patient's outcome, in particular concerning invasive ventilation.

Pelvic bone CT: can tin-filtered ultra-low-dose CT and virtual radiographs be used as alternative for standard CT and digital radiographs?

OBJECTIVES: To compare ultra-low-dose CT (ULD-CT) of the osseous pelvis with tin filtration to standard clinical CT (CT), and to assess the quality of computed virtual pelvic radiographs (VRs). METHODS: CT protocols were optimized in a phantom and three pelvic cadavers. Thirty prospectively included patients received both standard CT (automated tube voltage selection and current modulation) and tin-filtered ULD-CT of the pelvis (Sn140kV/50mAs). VRs of ULD-CT data were computed using an adapted cone beam-based projection algorithm and were compared to digital radiographs (DRs) of the pelvis. CT and DR dose parameters and quantitative and qualitative measures (1 = worst, 4 = best) were compared. CT and ULD-CT were assessed for osseous pathologies. RESULTS: Dose reduction of ULD-CT was 84% compared to CT, with a median effective dose of 0.38 mSv (quartile 1-3: 0.37-0.4 mSv) versus 2.31 mSv (1.82-3.58 mSv; p < .001), respectively. Mean dose of DR was 0.37 mSv (± 0.14 mSv). The median signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of bone were significantly higher for CT (64.3 and 21.5, respectively) compared to ULD-CT (50.4 and 18.8; p ≤ .01), while ULD-CT was significantly more dose efficient (figure of merit (FOM) 927.6) than CT (FOM 167.6; p < .001). Both CT and ULD-CT were of good image quality with excellent depiction of anatomy, with a median score of 4 (4-4) for both methods (p = .1). Agreement was perfect between both methods regarding the prevalence of assessed osseous pathologies (p > .99). VRs were successfully calculated and were equivalent to DRs. CONCLUSION: Tin-filtered ULD-CT of the pelvis at a dose equivalent to standard radiographs is adequate for assessing bone anatomy and osseous pathologies and had a markedly superior dose efficiency than standard CT. KEY POINTS: • Ultra-low-dose pelvic CT with tin filtration (0.38 mSv) can be performed at a dose of digital radiographs (0.37 mSv), with a dose reduction of 84% compared to standard CT (2.31 mSv). • Tin-filtered ultra-low-dose CT had lower SNR and CNR and higher image noise than standard CT, but showed clear depiction of anatomy and accurate detection of osseous pathologies. • Virtual pelvic radiographs were successfully calculated from ultra-low-dose CT data and were equivalent to digital radiographs.