Routine Computed Tomography Research Articles

Diagnostic accuracy of imaging modalities for detection of spinal metastases: a systematic review and meta-analysis.

Detecting spinal metastases is highly relevant in patients with oncological disorders as it can affect the staging and treatment of their disease. We aimed to evaluate the diagnostic performance of computed tomography (CT), magnetic resonance imaging (MRI), FDG positron emission tomography (PET)/CT, bone scintigraphy (BS), and single-photon emission computed tomography (SPECT) for spinal metastases detection. Medline, EMBASE, and Web of Science were systematically searched until March 2024 for diagnostic accuracy studies on spinal metastases detection (PROSPERO-registration: CRD42024540139). Data extraction and quality assessment using the QUADAS-2 tool were performed by two independent reviewers. Using bivariate random effects modeling, pooled sensitivities, specificities, and diagnostic odds ratios (DOR) were calculated, and hierarchical summary operating curves were constructed. Twenty-five studies (49 datasets), encompassing 3102 patients were included. Per-patient pooled sensitivities of CT, MRI, PET/CT, BS and SPECT were 70%, 93%, 82%, 75%, and 84%, respectively. Pooled specificities were 74%, 85%, 75%, 92%, and 81%, respectively. Per-lesion pooled sensitivities of CT, MRI, PET/CT, BS and SPECT were 76%, 91%, 92%, 77%, and 92%, respectively. Pooled specificities were 91%, 94%, 85%, 52%, and 86%, respectively. MRI had the highest DOR in per patient and lesion analyses. MRI had highest diagnostic accuracy for spinal metastases detection on patient and lesion level, suggesting a broader use in addition to the routine staging CT, at least in patients at high risk and where the detection of a spinal metastasis could alter therapy decisions. Herein, results should be considered with the limitations of each modality.

Visual coronary artery calcium assessment on routine chest CT can readily and cheaply identify liver transplant recipients with a low cardiac risk

Abstract Background Peri- and postoperative cardiac complications play an important role in survival of patients after liver transplantation (LT). However, the optimal approach for cardiac risk prediction in these patients has been debated on. LT recipients routinely receive non-gated computed tomography (CT) of the abdomen and chest to follow-up on their liver diseases. This study analyzed whether performance of coronary artery calcium (CAC) assessment on freely available scans can enhance cardiac risk stratification of LT recipients. Methods Consecutive LT recipients from 2008-2023 were included and analyzed retrospectively. CAC was scored visually on non-gated CT on a semi-quantitative ordinal scale and stratified in two groups according to CAC severity. Peri-operative (≤90 days) and post-operative all-cause mortality and cardiac events were analyzed. Furthermore, all-cause mortality and cardiac events were analyzed and compared between the groups with a Kaplan Meier curve and Cox proportional hazard regression. Results A total of 149 patients were included with a median age of 58 years. The median follow-up time was 5 years. The majority (74%) of patients had no or mild CAC. None of these patients died perioperatively due to cardiac causes, or experienced peri-operative cardiac events. The post-operative 10-year survival of LT recipients with no or mild calcifications was significantly better (p<0.01) than patients with severe CAC. The 10-year cardiac event-free survival was significantly better in patients with no or mild CAC (p<0.01) and the incidence increased >4-fold from only 4% in patients with no-mild CAC to 18% in patients with severe CAC. Of interest, severe CAC was a significant predictor of cardiac events (HR 4.6, p=0.02), while classical cardiovascular risk factors e.g. diabetes were not. Conclusion CAC assessment on routinely available non-gated CT can readily enhance peri- and postoperative cardiac risk stratification of LT recipients, as it identifies a selection of low-risk individuals for having peri- and post-operative cardiac events and all-cause mortality. Thereby, reducing test burden for the patients and saving healthcare expenses.

The CT-derived fat-free muscle fraction is associated with inflammation and predicts outcome in patients with aortic stenosis undergoing TAVR

Abstract Background The ESC guidelines underscore the importance of objective risk stratification in making patient-centered decision for valve interventions. However, they primarily rely on surgical risk scores, not considering essential factors such as frailty. Computed tomography (CT) is a routine part of the pre-interventional workup in patients undergoing TAVR and allows for body composition analysis, including the assessment of fat-free muscle fraction (FFMF) as an indicator of muscle quality. Purpose This study aimed to assess the correlation between FFMF and both inflammation and endocrine disorders, and to investigate the predictive value of FFMF in patients with aortic stenosis undergoing TAVR. Methods The study included 789 patients undergoing TAVR between 2017 and 2019. Evaluations involved CT scans to assess body composition. Using densitometric thresholds, the skeletal muscle area at L3/L4 level was separated into fatty and lean muscle to calculate the FFMF. The cohort was divided into tertiles of high, medium, and low FFMF, Figure 1. Results The study population was 45.5% female with a mean age of 81.2±6.0 years. Overall, 261 (33.1%) patients had a high FFMF, 293 (37.1%) had a medium FFMF, and 235 (29.8%) had a low FFMF. Patients with a low FFMF were older (82.3±5.9 vs 81.6±5.6 vs 79.8±6.2 years, p<0.01) and had higher rates of atrial fibrillation (52 vs 43 vs 37%, p<0.01), compared to those with a medium and high FFMF. Regarding body composition, low FFMF patients had a higher percentage of body fat (28.7±11.2 vs 26.8±9.1 vs 24.2±9.6%, p=0.01) and a lower percentage of body muscle (30.9±5.3 vs 31.3±4.2 vs 32.7±4.4%, p=0.03). Moreover, a low FFMF was associated with inflammation, as indicated by increased levels of C-reactive protein (6.3 vs 4.2 vs 3.1 mg/l, p<0.01) and procalcitonin (0.06 vs 0.05 vs 0.05 µg/l, p=0.01). Endocrinological assessment revealed lower levels of estradiol (6.8 vs 14.7 vs 15.0 pg/ml, p=0.02) and testosterone (0.18 vs 0.48 vs 2.35 ng/ml, p<0.01) as well as higher levels of cortisol (8.9 vs 7.7 vs 7.6μg/dl, p=0.05) in low FFMF patients. Regarding clinical outcomes, low FFMF was associated with increased one-year mortality (23.4%) compared to medium (11.6%) or low FFMF (3.8%, p<0.01), Figure 2A. This difference persisted over five years (p<0.01), Figure 2B. ROC curve analysis showed that FFMF had the strongest association with one-year mortality (AUC 0.75, p<0.01) and was superior to the STS-PROM (AUC 0.65) and EuroSCORE II (AUC 0.64). Multivariate analysis revealed that low FFMF was independently associated with mortality following TAVR (OR: 3.19 [CI: 1.64 – 6.22], p<0.01). Conclusion The CT-derived FFMF is associated with inflammation and endocrinological disorder in patients undergoing TAVR. Importantly, a low FFMF is a strong and independent predictor of dismal outcomes. FFMF assessment can seamlessly integrate into routine pre-interventional CTs, offering a promising objective parameter for outcome prediction.

Clinically relevant findings on 24-h head CT after acute stroke therapy: The 24-h CT score.

Routine head computed tomography (CT) is performed 24 h post-acute stroke thrombolysis and thrombectomy, even in patients with stable or improving clinical deficits. Predicting CT results that impact management could help prioritize patients at risk and potentially reduce unnecessary imaging. In this institutional review board (IRB)-approved retrospective study, data from 1461 consecutive acute ischemic stroke patients at our Comprehensive Stroke Center (n = 8943, 2012-2022) who received intravenous thrombolysis or endovascular therapy, exhibited stable or improving 24-h exams, and underwent 24-h follow-up head CT per standard acute stroke care guidelines. CT reports 24 h post-stroke were reviewed for edema, mass effect, herniation, and hemorrhage. The primary outcome was any clinically relevant 24-h CT finding that led to changes in antithrombotic treatment or blood pressure goals, extended intensive care unit (ICU) stays or hospitalizations, neurosurgical interventions, or administration of mannitol or hypertonic saline. Multivariable logistic regression identified independent predictors of clinically meaningful CT abnormalities. A 24-h CT score was developed and cross-validated. The mean age was 70 years, with 47% women. The median National Institutes of Health Stroke Scale (NIHSS) score at admission was 12 (interquartile range (IQR): 6-18). Stroke-related abnormalities on 24-h CT were present in 325 patients (22.2%), with 183 (12.5%) showing clinically relevant findings. Age, admission NIHSS, and blood glucose levels were independent predictors of clinically relevant 24-h CT findings. The final model C statistic was 0.72 (95% confidence interval (CI): 0.68-0.76) in the derivation cohort and 0.72 (95% CI: 0.67-0.75) in bootstrapping validation. The 24-h CT score was developed using these predictors: NIHSS score 5-15 (+3); NIHSS score ⩾16 (+5); age < 75 years (+1); admission glucose ⩾ 140 mg/dL (+1). The prevalence of clinically relevant CT findings was 4.3% in the low-risk group (24-h CT score ⩽ 4), 11.3% in the medium-risk group (score 5), and 21.4% in the high-risk group (score ⩾ 6). The 24-h CT score demonstrated good calibration. In patients undergoing thrombolysis or thrombectomy who undergo routine 24-h head CT despite remaining clinically stable or improving, only one in eight prove to have 24-h head CT findings that impact management. The 24-h CT score provides risk stratification that may improve resource utilization. A.S. and B.Z. have full access to the data used in the analysis in this article. Deidentified data will be shared after ethics approval if requested by other investigators for purposes of replicating the results.

Beyond body mass index: Body composition profiling for perioperative risk stratification in intrahepatic cholangiocarcinoma patients.

Intrahepatic cholangiocarcinoma (iCC) is an aggressive tumor, usually detected at an advanced stage. Our aim was to investigate the potential of body composition analysis (BCA) derived from presurgical staging computed tomography (CT) in predicting perisurgical complications. In this retrospective cohort study, we enrolled 86 patients who underwent CT imaging prior to liver surgery. Cox and logistic regression were performed to assess risk factors for prolonged hospital and intensive care unit (ICU) stays, as well as the occurrence of various complications. BCA parameters served as covariates besides conventional risk factors. Postoperative complications after resection of iCC significantly prolonged the overall length of hospitalization (p < .001). Presence of sarcopenia was associated with longer ICU stays. Complications were common, with 62.5% classified as Clavien-Dindo grade IIIa or lower and 37.5% as more severe. Subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) were identified as risk factors for complications, including bile leakage (in 24 cases, p = .025), pleural effusions (in 26 cases, p = .025), and intra-abdominal abscess formation (in 24 cases, p = .043). SAT was associated with severe complications requiring interventional therapy, whereas VAT was correlated with abscess formation. Despite normal prevalence of obesity (22%), body mass index (BMI) did not have an impact on the development of perioperative complications. BCA is a useful tool for preoperative risk stratification in patients with iCC and is superior to BMI assessment. Increased SAT and VAT were associated with the risk of perisurgical complications, prolonging hospitalization. Therefore, BCA derived from routine staging CT should be considered in the preoperative assessment of patients with iCC.

The determination of coefficients for size specific effective dose for adult and pediatric patients undergoing routine computed tomography examinations.

The effective dose resulting from computed tomography (CT) scans provides an assessment of the risk associated with stochastic effects but does not account for the patient's size. Advances in Monte Carlo simulations offer the potential to obtain organ dose data from phantoms of varying stature, enabling derivation of a size-specific effective doses (SEDs) representing doses to individual patients. This study aimed to compute size-specific k-conversion factors for SED in routine CT examinations for adult and pediatric patients of different sizes. Radiation interactions were simulated for adult and pediatric phantom models of various sizes using National Cancer Institute CT version 3.0.20211123. Subsequent calculations of SED were performed, and coefficients for SED were derived, considering the variations in body sizes. The results revealed a strong correlation between effective diameter and weight, observed with size-specific k-conversion factors for adult and pediatric phantoms, respectively. While size-specific k-conversion factors for CT brain remained constant in adults, values for pediatric cases varied. When using the tube current modulation (TCM) system, size-specific k-conversion factors increased in larger phantoms and decreased in smaller ones. The extent of this increase or decrease correlated with the set TCM strength. This study provides coefficients for estimating SEDs in routine CT exams. Software utilizing look-up tables of coefficients can be used to provide dose information for CT scanners at local hospitals, offering guidance to practitioners on doses to individual patients and improving radiation risk awareness in clinical practice.

Exploring bone density analysis on routine CT scans as a tool for opportunistic osteoporosis screening

The primary aim of this study was to evaluate computed tomography (CT)-based bone density analysis at the level of thoracic vertebra 12 (Th12) as a screening method for decreased bone density in patients admitted to the intensive care unit (ICU). Interobserver variability was analyzed. Secondary aims were to assess the prevalence of CT-based low bone density upon ICU admission in a cohort of COVID-19 patients and to assess the potential effect of long-term ICU stay on bone density in these patients. Retrospective single-center cohort study. ICU of the Leiden University Medical Center (LUMC), the Netherlands. Patients admitted to the ICU of the LUMC between March 1st, 2020 and February 1st, 2022 with a diagnosis of COVID-19, and a length of ICU stay of ≥ 21 days. In the included patients both baseline chest CT scans (obtained upon ICU admission) and follow-up chest CT scans (obtained ≥ 21 days after ICU admission) were available for analysis. A total of 118 CT scans in 38 patients were analyzed. There was a good interobserver variability, with an overall mean absolute difference (between measurements of three observers) of 9.7 Hounsfield Units (HU) and an intraclass correlation coefficient (ICC) of 0.93 (95% CI 0.88–0.96). The effect of intravenous contrast administration on bone density measurements was small (+ 7.5 HU (95% CI 3.4–11.5 HU)) higher in contrast enhanced CT images compared to non contrast enhanced CT images). Thirty-seven percent of patients had a bone density < 140 HU, suggestive of osteoporosis. No significant difference was found between bone density upon ICU admission and bone density at follow-up (≥ 21 days after ICU admission). Vertebral CT-based bone density analysis using routine CT scans is an easily applicable method to identify ICU patients with decreased bone density, which could enable enrollment in osteoporosis prevention programs. A high prevalence of low bone density was found in our cohort of ICU patients. There were no changes observed in bone density between baseline and follow-up measurements.

Reproducibility of CT-based opportunistic vertebral volumetric bone mineral density measurements from an automated segmentation framework

BackgroundTo investigate the reproducibility of automated volumetric bone mineral density (vBMD) measurements from routine thoracoabdominal computed tomography (CT) assessed with segmentations by a convolutional neural network and automated correction of contrast phases, on diverse scanners, with scanner-specific asynchronous or scanner-agnostic calibrations.MethodsWe obtained 679 observations from 278 CT scans in 121 patients (77 males, 63.6%) studied from 04/2019 to 06/2020. Observations consisted of two vBMD measurements from Δdifferent reconstruction kernels (n = 169), Δcontrast phases (n = 133), scan Δsessions (n = 123), Δscanners (n = 63), or Δall of the aforementioned (n = 20), and observations lacking scanner-specific calibration (n = 171). Precision was assessed using root-mean-square error (RMSE) and root-mean-square coefficient of variation (RMSCV). Cross-measurement agreement was assessed using Bland-Altman plots; outliers within 95% confidence interval of the limits of agreement were reviewed.ResultsRepeated measurements from Δdifferent reconstruction kernels were highly precise (RMSE 3.0 mg/cm3; RMSCV 1.3%), even for consecutive scans with different Δcontrast phases (RMSCV 2.9%). Measurements from different Δscan sessions or Δscanners showed decreased precision (RMSCV 4.7% and 4.9%, respectively). Plot-review identified 12 outliers from different scan Δsessions, with signs of hydropic decompensation. Observations with Δall differences showed decreased precision compared to those lacking scanner-specific calibration (RMSCV 5.9 and 3.7, respectively).ConclusionAutomatic vBMD assessment from routine CT is precise across varying setups, when calibrated appropriately. Low precision was found in patients with signs of new or worsening hydropic decompensation, what should be considered an exclusion criterion for both opportunistic and dedicated quantitative CT.Relevance statementAutomated CT-based vBMD measurements are precise in various scenarios, including cross-session and cross-scanner settings, and may therefore facilitate opportunistic screening for osteoporosis and surveillance of BMD in patients undergoing routine clinical CT scans.Key PointsArtificial intelligence-based tools facilitate BMD measurements in routine clinical CT datasets.Automated BMD measurements are highly reproducible in various settings.Reliable, automated opportunistic osteoporosis diagnostics allow for large-scale application.Graphical

Radiation Doses in Routine CT Examinations for Adult Patients in Saudi Arabia: A Systematic Review.

Computed tomography (CT) is an important imaging technique that produces detailed cross-sectional images for diagnosing medical conditions. However, the associated radiation exposure raises concerns. Establishing diagnostic reference levels (DRLs) helps identify unusual radiation doses and optimize exposure while maintaining diagnostic image quality. The purpose of this systematic review is to review the radiation doses received by adult patients in the head, chest, abdomen, pelvis, abdomen-pelvis (AP), and combined chest, abdomen, and pelvis (CAP) CT scans in Saudi Arabia. A search was conducted in several databases including PubMed and Google Scholar to identify studies that have established DRLs or determined radiation dose for adult CT examinations. Only studies that specifically assessed DRLs in actual adult patients were considered for inclusion. Out of a total of 31 articles that were identified as eligible, 13 were included after a thorough screening process. The values of CTDIv, DLP, and effective doses were determined. The review discovered that CTDIv and DLP were the most frequently used dosimetric quantities. The mean values in terms of CTDIv for head, chest, abdomen, pelvis, AP, and CAP ranged from 40.67 to 61.80 mGy, 5.80 to 14.90 mGy, 8.60 to 16.15 mGy, 10.80 to 17.35 mGy, 14.10 to 16.84 mGy, and 12.00 to 22.94 mGy, respectively. The mean values in terms of DLP for head, chest, abdomen, pelvis, AP, and CAP ranged from 757 to 1212 mGy.cm, 243 to 657 mGy.cm, 369.5 to 549 mGy.cm, 379.6 to 593 mGy.cm, 658 to 940.43 mGy.cm, and 740 to 1493.8 mGy.cm, respectively. There is a fluctuation in radiation dose among CT centers, highlighting a need to provide proper education and training to radiographers. It is recommended to establish a universally accepted standardized protocol based on weight, equivalent diameter, or cross-sectional area for accurate comparisons with national and international DRLs.

A cost-free approach to evaluating vertebral body bone density and height loss in lung transplant recipients using routine chest CT

BackgroundTo assess changes in bone density and vertebral body height of patients undergoing lung transplant surgery using computed tomography (CT). MethodsThis institutional review board (IRB) approved retrospective observational study enrolled patients with a history of lung transplant who had at least two chest CT scans. Vertebral body bone density (superior, middle, and inferior sections) and height (anterior, middle, and posterior sections) were measured at T1-T12 at baseline and follow up CT scans. Changes in the mean bone density, mean vertebral height, vertebral compression ratio (VBCR), percentage of anterior height compression (PAHC), and percentage of middle height compression (PMHC) were calculated and analyzed. ResultsA total of 93 participants with mean age of 58 ± 12.3 years were enrolled. The most common underlying disease that led to lung transplants was interstitial lung diseases (57 %). The inter-scan interval was 34.06 ± 24.8 months. There were significant changes (p-value < 0.05) in bone density at all levels from T3 to T12, with the greatest decline at the T10 level from 163.06 HU to 141.84 HU (p-value < 0.05). The average VBCR decreased from 96.91 to 96.15 (p-value < 0.05). ConclusionRoutine chest CT scans demonstrate a gradual decrease in vertebral body bone density over time in lung transplant recipients, along with evident anatomic changes such as vertebral body bone compression. This study shows that utilizing routine chest CT for lung transplant recipients can be regarded as a cost-free tool for assessing the vertebral body bone changes in these patients and potentially aiding in the prevention of complications related to osteoporosis.

Neglected Superior Ophthalmic Vein Enlargement before Delayed Symptom of Carotid-Cavernous Fistula in a Blowout Fracture: A Case Report and Literature Review.

Carotid-cavernous fistula (CCF) is a rare condition. However, it should be suspected when there are traumatic facial fractures, because if not diagnosed, it can lead to permanent damage such as blindness. Traumatic CCF often presents delayed symptoms, and delayed diagnosis without prompt treatment can lead to permanent injuries in optic and cranial nerves III, IV, V, and VI as well as intracranial hemorrhage. The routine initial modality for patients with suspected facial bone fractures is noncontrast computed tomography (CT) to identify any fracture lines and check for intracranial hemorrhage. We report a post-traumatic CCF case with a 4-day symptom delay, where left superior ophthalmic vein (SOV) enlargement was observed on the routine noncontrast facial CT with ipsilateral orbital wall fracture. When the patient first presented to the emergency room (ER), we did not detect vein enlargement on CT. Afterwards, the patient developed delayed symptoms of CCF and was readmitted to the ER. When we reanalyzed the first CT scan, an enlarged SOV was confirmed. The diagnosis was confirmed via magnetic resonance imaging angiography, and the patient was successfully treated with embolization of the fistula. Thus, we recommend reviewing ophthalmic vein enlargement that is readily identifiable through noncontrast CT for patients injured by craniofacial trauma to suspect the presence of delayed CCF at their initial presentation.

Osteoporotic vertebral compression fracture (OVCF) detection using artificial neural networks model based on the AO spine-DGOU osteoporotic fracture classification system

BackgroundOsteoporotic Vertebral Compression Fracture (OVCF) substantially reduces a person's health-related quality of life. Computer Tomography (CT) scan is currently the standard for diagnosis of OVCF. The aim of this paper was to evaluate the OVCF detection potential of artificial neural networks (ANN). MethodsModels of artificial intelligence based on deep learning hold promise for quickly and automatically identifying and visualizing OVCF. This study investigated the detection, classification, and grading of OVCF using deep artificial neural networks (ANN). Techniques: Annotation techniques were used to segregate the sagittal images of 1,050 OVCF CT pictures with symptomatic low back pain into 934 CT images for a training dataset (89%) and 116 CT images for a test dataset (11%). A radiologist tagged, cleaned, and annotated the training dataset. Disc deterioration was assessed in all lumbar discs using the AO Spine-DGOU Osteoporotic Fracture Classification System. The detection and grading of OVCF were trained using the deep learning ANN model. By putting an automatic model to the test for dataset grading, the outcomes of the ANN model training were confirmed. ResultsThe sagittal lumbar CT training dataset included 5,010 OVCF from OF1, 1942 from OF2, 522 from OF3, 336 from OF4, and none from OF5. With overall 96.04% accuracy, the deep ANN model was able to identify and categorize lumbar OVCF. ConclusionsThe ANN model offers a rapid and effective way to classify lumbar OVCF by automatically and consistently evaluating routine CT scans using AO Spine-DGOU osteoporotic fracture classification system.

Computed Tomography Evaluation of Alumina Ceramic-on-Ceramic Total Hip Arthroplasty With More Than 20 years of Follow-Up: Is a Follow-Up Computed Tomography Scan Necessary?

BackgroundCeramic-on-ceramic (CoC) bearings have been increasingly used in total hip arthroplasty (THA) because of their superior wear resistance and biocompatibility. However, there is a scarcity of reports on the computed tomography (CT) evaluation of CoC bearings with more than 10 years. The aim of this study was to evaluate the long-term CT results of THA using CoC bearings for more than 20 years of follow-up. We hypothesized that there would be no wear, osteolysis, or ceramic fracture. MethodsBetween November 1997 and June 2003, 956 hips underwent THA using alumina-on-alumina bearings at a tertiary referral hospital. Among them, 107 hips were assessed, all of which underwent a CT examination more than 20 years after the index surgery. The mean age at the time of surgery was 41 years, and a CT scan was performed at an average of 22.0 years postoperatively (range, 20.0 to 25.1). The CT scans were thoroughly assessed for osteolysis, stem notching, and ceramic component fracture. ResultsNo loosening was observed in the acetabular cup or femoral stem. Stem notching was observed in 3 hips (2.8%). In the CT scan taken after a minimum of 20 years of follow-up, 1 case (0.9%) of osteolysis around the cup and 2 cases (1.9%) of osteolysis around the femoral stem were noted. Suspected chip fractures of the ceramic insert were discovered in 4 cases (3.7%). Despite these findings, the patients remained asymptomatic, and no subsequent surgical intervention was needed after close follow-up. ConclusionsRoutine CT examinations for patients who underwent THA using CoC bearings over 20 years ago revealed unexpected findings, such as osteolysis and suspected chip fractures of the ceramic liner. However, routine CT scans may not be universally necessary. The CT evaluation in this cohort should be selectively performed for patients who have relevant clinical symptoms. Level of evidenceLevel III, Therapeutic study.

Accuracy of Phantomless Calibration of Routine Computed Tomography Scans for Opportunistic Osteoporosis Screening in the Spine Clinic.

Diagnostic accuracy study. To establish a simple method of phantomless bone mineral density (BMD) measurement by using preoperative lumbar Computed Tomography (CT) scans, and compare the accuracy of reference tissue combinations to diagnose low BMD against uncalibrated Hounsfield units (HUs). HUs are used as a measure of BMD; however, associations between HU and T-scores vary widely. Quantitative CT (qCT) scans are more accurate, but they require density calibration with an object of known density (phantom), which limits feasibility. As an emerging technique, phantomless (internal) calibration of routine CT scans may provide a good opportunity for screening. Patients who were scheduled to undergo lumbar surgery, with a preoperative CT scan, and a dual-energy x-ray absorptiometry (DXA) scan within six months were included. Four tissues were selected for calibration: subcutaneous adipose (A), erector spinae (ES), psoas (P) and aortic blood (AB). The HUs of these tissues were used in linear regression against ground-truth values. Calibrations were performed by using two different internal tissues at a time to maintain simplicity and in-office applicability.Volumetric bone mineral densities (vBMD) derived from internally calibrated CT scans were analyzed for new threshold values for low bone density. Areas under the curve (AUC) were calculated with 95% confidence intervals (CI). 45 patients were included (M/F=10/35, mean age:63.3). Calibrated vBMDs had stronger correlations with DXA T-scores when compared with HUs, with L2 exhibiting the highest coefficients. Calibration by using A and ES with the threshold of 162mg/cm3 had a sensitivity of 90% in detecting low BMD (AUC=0.671). This novel method allows simple, in-office calibration of routine preoperative CT scans without the use of a phantom. Calibration using adipose and erector spinae with a threshold of 162mg/cm3 is proposed for low bone density screening with high sensitivity (90%). Level III.

Standardised and automated assessment of head computed tomography reliably predicts poor functional outcome after cardiac arrest: a prospective multicentre study

PurposeApplication of standardised and automated assessments of head computed tomography (CT) for neuroprognostication after out-of-hospital cardiac arrest.MethodsProspective, international, multicentre, observational study within the Targeted Hypothermia versus Targeted Normothermia after out-of-hospital cardiac arrest (TTM2) trial. Routine CTs from adult unconscious patients obtained > 48 h ≤ 7 days post-arrest were assessed qualitatively and quantitatively by seven international raters blinded to clinical information using a pre-published protocol. Grey–white-matter ratio (GWR) was calculated from four (GWR-4) and eight (GWR-8) regions of interest manually placed at the basal ganglia level. Additionally, GWR was obtained using an automated atlas-based approach. Prognostic accuracies for prediction of poor functional outcome (modified Rankin Scale 4–6) for the qualitative assessment and for the pre-defined GWR cutoff < 1.10 were calculated.Results140 unconscious patients were included; median age was 68 years (interquartile range [IQR] 59–76), 76% were male, and 75% had poor outcome. Standardised qualitative assessment and all GWR models predicted poor outcome with 100% specificity (95% confidence interval [CI] 90–100). Sensitivity in median was 37% for the standardised qualitative assessment, 39% for GWR-8, 30% for GWR-4 and 41% for automated GWR. GWR-8 was superior to GWR-4 regarding prognostic accuracies, intra- and interrater agreement. Overall prognostic accuracy for automated GWR (area under the curve [AUC] 0.84, 95% CI 0.77–0.91) did not significantly differ from manually obtained GWR.ConclusionStandardised qualitative and quantitative assessments of CT are reliable and feasible methods to predict poor functional outcome after cardiac arrest. Automated GWR has the potential to make CT quantification for neuroprognostication accessible to all centres treating cardiac arrest patients.

Assessment of image quality and impact of deep learning-based software in non-contrast head CT scans

In this retrospective study, we aimed to assess the objective and subjective image quality of different reconstruction techniques and a deep learning-based software on non-contrast head computed tomography (CT) images. In total, 152 adult head CT scans (77 female, 75 male; mean age 69.4 ± 18.3 years) obtained from three different CT scanners using different protocols between March and April 2021 were included. CT images were reconstructed using filtered-back projection (FBP), iterative reconstruction (IR), and post-processed using a deep learning-based algorithm (PS). Post-processing significantly reduced noise in FBP-reconstructed images (up to 15.4% reduction) depending on the protocol, leading to improvements in signal-to-noise ratio of up to 19.7%. However, when deep learning-based post-processing was applied to FBP images compared to IR alone, the differences were inconsistent and partly non-significant, which appeared to be protocol or site specific. Subjective assessments showed no significant overall improvement in image quality for all reconstructions and post-processing. Inter-rater reliability was low and preferences varied. Deep learning-based denoising software improved objective image quality compared to FBP in routine head CT. A significant difference compared to IR was observed for only one protocol. Subjective assessments did not indicate a significant clinical impact in terms of improved subjective image quality, likely due to the low noise levels in full-dose images.

Digital phantom versus patient-specific radiation dosimetry in adult routine thorax CT examinations.

The aim of this study was to compare the organ doses assessed through a digital phantom-based and a patient specific-based dosimetric tool in adult routine thorax computed tomography (CT) examinations with reference to physical dose measurements performed in anthropomorphic phantoms. Two Monte Carlo based dose calculation tools were used to assess organ doses in routine adult thorax CT examinations. These were a digital phantom-based dosimetry tool (NCICT, National Cancer Institute, USA) and a patient-specific individualized dosimetry tool (ImpactMC, CT Imaging GmbH, Germany). Digital phantoms and patients were classified in four groups according to their water equivalent diameter (Dw). Normalized to volume computed tomography dose index (CTDIvol), organ dose was assessed for lungs, esophagus, heart, breast, active bone marrow, and skin. Organ doses were compared to measurements performed using thermoluminescent detectors (TLDs) in two physical anthropomorphic phantoms that simulate the average adult individual as a male (Alderson Research Labs, USA) and as a female (ATOM Phantoms, USA). The average percent difference of NCICT to TLD and ImpactMC to TLD dose measurements across all organs in both sexes was 13% and 6%, respectively. The average±1 standard deviation in dose values across all organs with NCICT, ImpactMC, and TLDs was±0.06 (mGy/mGy),±0.19 (mGy/mGy), and±0.13 (mGy/mGy), respectively. Organ doses decreased with increasing Dw in both NCICT and ImpactMC. Organ doses estimated with ImpactMC were in closer agreement to TLDs compared to NCICT. This may be attributed to the inherent property of ImpactMC methodology to generate phantoms that resemble the realistic anatomy of the examined patient as opposed to NCICT methodology that incorporates an anatomical discrepancy between phantoms and patients.

Coronary calcifications as assessed on routine non-gated chest CT; a gatekeeper to tailor downstream additional imaging in patients with stable chest pain

Background and aimsCurrently applied methods for risk-assessment in coronary artery disease (CAD) often overestimate patients’ risk for obstructive CAD. To enhance risk estimation, assessment of coronary artery calcium (CAC) can be applied. In 10 % of patients presenting with stable chest pain a previous non-gated computed tomography (CT) has been performed, suitable for CAC-assessment. This study is the first to investigate the clinical utility of CAC-assessment on non-gated CT for risk-assessment of obstructive CAD in symptomatic patients. MethodsFor this analysis, all patients referred for coronary computed tomography angiography (CCTA), in whom a previous non-gated chest CT was performed were included. The extent of CAC was assessed on chest CT and ordinally scored. CAD was assessed on CCTA and obstructive CAD defined as stenosis of ≥70 %. Patients were stratified according to CAC-severity and percentages of patients with obstructive CAD were compared between the CAC groups. ResultsIn total, 170 patients of 32–88 years were included and 35 % were male. The percentage of obstructive CAD between the CAC groups differed significantly (p < 0.01). A calcium score of 0 ruled out obstructive CAD irrespective of sex, pre-test probability, type of complaints and number of risk factors with a 100 % certainty. Furthermore, a mild CAC score ruled out obstructive CAD in patients with low – intermediate PTP or non-anginal complaints with 100 % certainty. ConclusionWhen available, CAC on non-gated chest CT can accurately rule out obstructive CAD and can therefore function as a radiation-free and cost-free gatekeeper for additional imaging in patients presenting with stable chest pain.

3D-Volumetric Shunt Measurement for Detection of High-Risk Esophageal Varices in Liver Cirrhosis.

Background and Objectives: Esophageal varices (EV) and variceal hemorrhages are major causes of mortality in liver cirrhosis patients. Detecting EVs early is crucial for effective management. Computed tomography (CT) scans, commonly performed for various liver-related indications, provide an opportunity for non-invasive EV assessment. However, previous CT studies focused on variceal diameter, neglecting the three-dimensional (3D) nature of varices and shunt vessels. This study aims to evaluate the potential of 3D volumetric shunt-vessel measurements from routine CT scans for detecting high-risk esophageal varices in portal hypertension. Methods: 3D volumetric measurements of esophageal varices were conducted using routine CT scans and compared to endoscopic variceal grading. Receiver operating characteristic (ROC) analyses were performed to determine the optimal cutoff value for identifying high-risk varices based on shunt volume. The study included 142 patients who underwent both esophagogastroduodenoscopy (EGD) and contrast-enhanced CT within six months. Results: The study established a cutoff value for identifying high-risk varices. The CT measurements exhibited a significant correlation with endoscopic EV grading (correlation coefficient r = 0.417, p < 0.001). A CT cutoff value of 2060 mm3 for variceal volume showed a sensitivity of 72.1% and a specificity of 65.5% for detecting high-risk varices during endoscopy. Conclusions: This study demonstrates the feasibility of opportunistically measuring variceal volumes from routine CT scans. CT volumetry for assessing EVs may have prognostic value, especially in cirrhosis patients who are not suitable candidates for endoscopy.

Radiomics and machine learning for renal tumor subtype assessment using multiphase computed tomography in a multicenter setting

ObjectivesTo distinguish histological subtypes of renal tumors using radiomic features and machine learning (ML) based on multiphase computed tomography (CT).Material and methodsPatients who underwent surgical treatment for renal tumors at two tertiary centers from 2012 to 2022 were included retrospectively. Preoperative arterial (corticomedullary) and venous (nephrogenic) phase CT scans from these centers, as well as from external imaging facilities, were manually segmented, and standardized radiomic features were extracted. Following preprocessing and addressing the class imbalance, a ML algorithm based on extreme gradient boosting trees (XGB) was employed to predict renal tumor subtypes using 10-fold cross-validation. The evaluation was conducted using the multiclass area under the receiver operating characteristic curve (AUC). Algorithms were trained on data from one center and independently tested on data from the other center.ResultsThe training cohort comprised n = 297 patients (64.3% clear cell renal cell cancer [RCC], 13.5% papillary renal cell carcinoma (pRCC), 7.4% chromophobe RCC, 9.4% oncocytomas, and 5.4% angiomyolipomas (AML)), and the testing cohort n = 121 patients (56.2%/16.5%/3.3%/21.5%/2.5%).The XGB algorithm demonstrated a diagnostic performance of AUC = 0.81/0.64/0.8 for venous/arterial/combined contrast phase CT in the training cohort, and AUC = 0.75/0.67/0.75 in the independent testing cohort. In pairwise comparisons, the lowest diagnostic accuracy was evident for the identification of oncocytomas (AUC = 0.57–0.69), and the highest for the identification of AMLs (AUC = 0.9–0.94)ConclusionRadiomic feature analyses can distinguish renal tumor subtypes on routinely acquired CTs, with oncocytomas being the hardest subtype to identify.Clinical relevance statementRadiomic feature analyses yield robust results for renal tumor assessment on routine CTs. Although radiologists routinely rely on arterial phase CT for renal tumor assessment and operative planning, radiomic features derived from arterial phase did not improve the accuracy of renal tumor subtype identification in our cohort.