Diagnostic Accuracy of Simulated Low-Dose Perfusion CT to Detect Cerebral Perfusion Impairment after Aneurysmal Subarachnoid Hemorrhage: A Retrospective Analysis

Exploring the Low-Dose Limit for Focal Hepatic Lesion Detection with a Deep Learning-Based CT Reconstruction Algorithm: A Simulation Study on Patient Images

This study aims to investigate the maximum achievable dose reduction for applying a new deep learning-based reconstruction algorithm, namely the artificial intelligence iterative reconstruction (AIIR), in computed tomography (CT) for hepatic lesion detection. A total of 40 patients with 98 clinically confirmed hepatic lesions were retrospectively included. The mean volume CT dose index was 13.66 ± 1.73 mGy in routine-dose portal venous CT examinations, where the images were originally obtained with hybrid iterative reconstruction (HIR). Low-dose simulations were performed in projection domain for 40%-, 20%-, and 10%-dose levels, followed by reconstruction using both HIR and AIIR. Two radiologists were asked to detect hepatic lesion on each set of low-dose image in separate sessions. Qualitative metrics including lesion conspicuity, diagnostic confidence, and overall image quality were evaluated using a 5-point scale. The contrast-to-noise ratio (CNR) for lesion was also calculated for quantitative assessment. The lesion CNR on AIIR at reduced doses were significantly higher than that on routine-dose HIR (all p < 0.05). Lower qualitative image quality was observed as the radiation dose reduced, while there were no significant differences between 40%-dose AIIR and routine-dose HIR images. The lesion detection rate was 100%, 98% (96/98), and 73.5% (72/98) on 40%-, 20%-, and 10%-dose AIIR, respectively, whereas it was 98% (96/98), 73.5% (72/98), and 40% (39/98) on the corresponding low-dose HIR, respectively. AIIR outperformed HIR in simulated low-dose CT examinations of the liver. The use of AIIR allows up to 60% dose reduction for lesion detection while maintaining comparable image quality to routine-dose HIR.

Diagnostic performance and image quality of an image-based denoising algorithm applied to radiation dose-reduced CT in diagnosing acute appendicitis

PURPOSE

To evaluate diagnostic performance and image quality of ultralow-dose CT (ULDCT) in diagnosing acute appendicitis with an image-based deep-learning denoising algorithm (IDLDA).

METHODS

This retrospective multicenter study included 180 patients (mean ± standard deviation, 29 ± 9 years; 91 female) who underwent contrast-enhanced 2-mSv CT for suspected appendicitis from February 2014 to August 2016. We simulated ULDCT from 2-mSv CT, reducing the dose by at least 50%. Then we applied an IDLDA on ULDCT to produce denoised ULDCT (D-ULDCT). Six radiologists with different experience levels (three board-certified radiologists and three residents) independently reviewed the ULDCT and D-ULDCT. They rated the likelihood of appendicitis and subjective image qualities (subjective image noise, diagnostic acceptability, and artificial sensation). One radiologist measured image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). We used the receiver operating characteristic (ROC) analyses, Wilcoxon's signed-rank tests, and paired t-tests.

RESULTS

The area under the ROC curves (AUC) for diagnosing appendicitis ranged 0.90-0.97 for ULDCT and 0.94-0.97 for D-ULDCT. The AUCs of two residents were significantly higher on D-ULDCT (AUC difference = 0.06 [95% confidence interval, 0.01-0.11; p = .022] and 0.05 [0.00-0.10; p = .046], respectively). D-ULDCT provided better subjective image noise and diagnostic acceptability to all six readers. However, the response of board-certified radiologists and residents differed in artificial sensation (all p ≤ .003). D-ULDCT showed significantly lower image noise, higher SNR, and higher CNR (all p < .001).

CONCLUSION

An IDLDA can provide better ULDCT image quality and enhance diagnostic performance for less-experienced radiologists.

Early and delayed blood-brain barrier permeability predicts delayed cerebral ischemia and outcomes following aneurysmal subarachnoid hemorrhage

OBJECTIVES

This study aimed to monitor blood-brain barrier permeability within 24 h and during the delayed cerebral ischemia (DCI) time window (DCITW) spanning 4-14 days after aneurysmal subarachnoid hemorrhage (aSAH) and to investigate its correlation with both DCI occurrence and outcomes at three months.

METHODS

A total of 128 patients were stratified based on the DCI occurrence and three-month modified Rankin scale scores. Comparison of Ktrans at admission (admission Ktrans) and during DCITW (DCITW Ktrans) was conducted between DCI and non-DCI groups, as well as between groups with good and poor outcomes. Changes in Ktrans were also analyzed. Multivariate logistic regression analysis was performed to identify independent predictors of DCI and poor outcomes.

RESULTS

Admission Ktrans (0.58 ± 0.18 vs 0.47 ± 0.12, p = 0.002) and DCITW Ktrans (0.54 ± 0.19 vs 0.41 ± 0.14, p < 0.001) were significantly higher in the DCI group compared with the non-DCI group. Although both were higher in the poor outcome group than the good outcome group, the difference was not statistically significant at admission (0.53 ± 0.18 vs 0.49 ± 0.14, p = 0.198). Ktrans in the non-DCI group (0.47 ± 0.12 vs 0.41 ± 0.14, p = 0.004) and good outcome group (0.49 ± 0.14 vs 0.41 ± 0.14, p < 0.001) decreased significantly from the admission to DCITW. Multivariate analysis identified DCITW Ktrans and admission Ktrans as independent predictors of poor outcomes (OR = 1.73, 95%CI: 1.24-2.43, p = 0.001) and DCI (OR = 1.75, 95%CI: 1.25-2.44, p = 0.001), respectively.

CONCLUSION

Elevated Ktrans at admission is associated with the occurrence of DCI. Continuous monitoring of Ktrans from admission to DCITW can accurately identify reversible and irreversible changes and can predict outcomes at 3 months.

CLINICAL RELEVANCE STATEMENT

Ktrans measured with CT perfusion is a valuable tool for predicting both delayed cerebral ischemia and three-month outcomes following aneurysmal subarachnoid hemorrhage. Monitoring changes in Ktrans from admission to time window of delayed cerebral ischemia can guide treatment and management decisions for aneurysmal subarachnoid hemorrhage patients.

KEY POINTS

• Ktrans measured at admission and during the delayed cerebral ischemia time window (4-14 days) holds distinct clinical significance following aneurysmal subarachnoid hemorrhage. • Admission Ktrans serves as a predictor for delayed cerebral ischemia, while continuous assessment of Ktrans from admission to the delayed cerebral ischemia time window can predict three-month outcomes. • Monitoring Ktrans at different stages improves instrumental in enhancing decision-making and treatment planning for patients with aneurysmal subarachnoid hemorrhage.

AntiHalluciNet: A Potential Auditing Tool of the Behavior of Deep Learning Denoising Models in Low-Dose Computed Tomography

Gaining the ability to audit the behavior of deep learning (DL) denoising models is of crucial importance to prevent potential hallucinations and adversarial clinical consequences. We present a preliminary version of AntiHalluciNet, which is designed to predict spurious structural components embedded in the residual noise from DL denoising models in low-dose CT and assess its feasibility for auditing the behavior of DL denoising models. We created a paired set of structure-embedded and pure noise images and trained AntiHalluciNet to predict spurious structures in the structure-embedded noise images. The performance of AntiHalluciNet was evaluated by using a newly devised residual structure index (RSI), which represents the prediction confidence based on the presence of structural components in the residual noise image. We also evaluated whether AntiHalluciNet could assess the image fidelity of a denoised image by using only a noise component instead of measuring the SSIM, which requires both reference and test images. Then, we explored the potential of AntiHalluciNet for auditing the behavior of DL denoising models. AntiHalluciNet was applied to three DL denoising models (two pre-trained models, RED-CNN and CTformer, and a commercial software, ClariCT.AI [version 1.2.3]), and whether AntiHalluciNet could discriminate between the noise purity performances of DL denoising models was assessed. AntiHalluciNet demonstrated an excellent performance in predicting the presence of structural components. The RSI values for the structural-embedded and pure noise images measured using the 50% low-dose dataset were 0.57 ± 31 and 0.02 ± 0.02, respectively, showing a substantial difference with a p-value < 0.0001. The AntiHalluciNet-derived RSI could differentiate between the quality of the degraded denoised images, with measurement values of 0.27, 0.41, 0.48, and 0.52 for the 25%, 50%, 75%, and 100% mixing rates of the degradation component, which showed a higher differentiation potential compared with the SSIM values of 0.9603, 0.9579, 0.9490, and 0.9333. The RSI measurements from the residual images of the three DL denoising models showed a distinct distribution, being 0.28 ± 0.06, 0.21 ± 0.06, and 0.15 ± 0.03 for RED-CNN, CTformer, and ClariCT.AI, respectively. AntiHalluciNet has the potential to predict the structural components embedded in the residual noise from DL denoising models in low-dose CT. With AntiHalluciNet, it is feasible to audit the performance and behavior of DL denoising models in clinical environments where only residual noise images are available.

How Real Are Computed Tomography Low Dose Simulations? An Investigational In-Vivo Large Animal Study

OBJECTIVES

CT low-dose simulation methods have gained significant traction in protocol development, as they lack the risk of increased patient exposure. However, in-vivo validations of low-dose simulations are as uncommon as prospective low-dose image acquisition itself. Therefore, we investigated the extent to which simulated low-dose CT datasets resemble their real-dose counterparts.

MATERIALS AND METHODS

Fourteen veterinarian-sedated alive pigs underwent three CT scans on the same third generation dual-source scanner with 2 months between each scan. At each time, three additional scans ensued, with mAs reduced to 50%, 25%, and 10%. All scans were reconstructed using wFBP and ADMIRE levels 1-5. Matching low-dose datasets were generated from the 100% scans using reconstruction-based and DICOM-based simulations. Objective image quality (CT numbers stability, noise, and signal-to-noise ratio) was measured via consistent regions of interest. Three radiologists independently rated all possible dataset combinations per time point for subjective image quality (-1=inferior, 0=equal, 1=superior). The points were averaged for a semiquantitative score, and inter-rater-agreement was measured using Spearman's correlation coefficient. A structural similarity index (SSIM) analyzed the voxel-wise similarity of the volumes. Adequately corrected mixed-effects analysis compared objective and subjective image quality. Multiple linear regression with three-way interactions measured the contribution of dose, reconstruction mode, simulation method, and rater to subjective image quality.

RESULTS

There were no significant differences between objective and subjective image quality of reconstruction-based and DICOM-based simulation on all dose levels (p≥0.137). However, both simulation methods produced significantly lower objective image quality than real-dose images below 25% mAs due to noise overestimation (p<0.001; SSIM≤89±3). Overall, inter-rater-agreement was strong (r≥0.68, mean 0.93±0.05, 95% CI 0.92-0.94; each p<0.001). In regression analysis, significant decreases in subjective image quality were observed for lower radiation doses (b ≤ -0.387, 95%CI -0.399 to -0.358; p<0.001) but not for reconstruction modes, simulation methods, raters, or three-way interactions (p≥0.103).

CONCLUSION

Simulated low-dose CT datasets are subjectively and objectively indistinguishable from their real-dose counterparts down to 25% mAs, making them an invaluable tool for efficient low-dose protocol development.

Computed Tomography Angiography Compared with Computed Tomography Perfusion in the Diagnosis of Cerebral Vasospasm: A Systematic Review and Meta-Analysis

INTRODUCTION

Cerebral vasospasm (CV) is a serious complication after subarachnoid hemorrhage; however, swift identification can be challenging. Computed tomography perfusion (CTP) directly measures tissue perfusion and may better screen for CV compared with other modalities. This systematic review summarizes studies assessing the diagnostic performance of computed tomography angiography (CTA) and CTP in identifying CV.

METHODS

The search strategy drew from English language publications in the PubMed, Embase, Medline, and Cochrane databases from January 1996 to September 2021. Diagnosis of CV by digital subtraction angiography was the reference standard. Pooled sensitivity, specificity, positive predictive values (PPV), negative predictive values (NPV), positive likelihood ratios, negative likelihood ratios, and summary receiver operating characteristic curve were calculated. The methodological index for nonrandomized studies tool was employed to assess the quality of the studies.

RESULTS

The search generated 22 studies. Seven CTA studies and 6 CTP investigations provided sufficient data for meta-analysis. Following pooled estimates, CTA carried a sensitivity of 0.76 (95% confidence interval [CI], 0.72-0.80), specificity of 0.93 (95% CI, 0.92-0.95), PPV of 0.77 (95%, 0.76-0.79), and NPV of 0.81 (95%, 0.79-0.82). CTP carried a sensitivity of 0.86 (95%, 0.81-0.92), specificity of 0.97 (95%, 0.95-0.98), PPV of 0.94 (0.89-0.98), and NPV of 0.94 (0.91-0.97). Using the methodological index for nonrandomized studies tool, the evidence was rated as overall moderate quality.

CONCLUSIONS

This meta-analysis on the diagnostic performance of CTA and CTP in identifying CV suggests that CTP may carry greater diagnostic accuracy compared with CTA. The clinical significance of this difference should be delineated through future prospective studies.

Temporal averaging angiographic reconstructions from whole-brain CT perfusion for the detection of vasospasm

PURPOSE

The aim of this study is to evaluate the image quality and diagnostic performance of angiographic images reconstructed from whole-brain CT perfusion (CTP) using temporal averaging compared to CT angiography (CTA) for the detection of vasospasm.

MATERIALS AND METHODS

39 CT studies in 28 consecutive patients who underwent brain CTA with CTP for suspected vasospasm between September 2020 and May 2021 were retrospectively evaluated. The image quality of these two vascular imaging techniques was assessed either quantitatively (image noise, vascular enhancement, signal-to-noise (SNR) and contrast-to-noise (CNR) ratios,) and qualitatively (4 criteria assessed on a 5-point scale). Intra and interobserver agreements and a diagnostic confidence score on the diagnosis of vasospasm were measured. Radiation dose parameters (volume CT dose index (CTDI_vol) and dose-length product (DLP)) were recorded.

RESULTS

Both SNR and CNR were significantly higher with temporal averaging compared to CTA, increasing by 104% and 113%, respectively (p<0.001). The qualitative assessment found no significant difference in overall image quality between temporal averaging (4.33 ± 0.48) and brain CTA (4.19 ± 0.52) (p = 0.12).There was a significant improvement in intravascular noise and arterial contrast enhancement with temporal averaging. The evaluation of intra and interobserver agreements showed a robust concordance in the diagnosis of vasospasm between the two techniques.

CONCLUSIONS

Temporal averaging appeared as a feasible and reliable imaging technique for the detection of vasospasm. The use of temporal averaging, replacing brain CTA, could represent a new strategy of radiation and contrast material doses reduction in these patients.

Basis and current state of computed tomography perfusion imaging: a review

Computed tomography perfusion (CTP) is a functional imaging that allows for providing capillary-level hemodynamics information of the desired tissue in clinics. In this paper, we aim to offer insight into CTP imaging which covers the basics and current state of CTP imaging, then summarize the technical applications in the CTP imaging as well as the future technological potential. At first, we focus on the fundamentals of CTP imaging including systematically summarized CTP image acquisition and hemodynamic parameter map estimation techniques. A short assessment is presented to outline the clinical applications with CTP imaging, and then a review of radiation dose effect of the CTP imaging on the different applications is presented. We present a categorized methodology review on known and potential solvable challenges of radiation dose reduction in CTP imaging. To evaluate the quality of CTP images, we list various standardized performance metrics. Moreover, we present a review on the determination of infarct and penumbra. Finally, we reveal the popularity and future trend of CTP imaging.

Continuous Intraarterial Nimodipine Infusion for the Treatment of Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage: A Retrospective, Single-Center Cohort Trial

Background

Delayed cerebral ischemia (DCI) occurs after aneurysmal subarachnoid hemorrhage (aSAH). Continuous intraarterial nimodipine infusion (CIAN) is a promising approach in patients with intracranial large vessel vasospasm (LVV). The objective of this retrospective single-center cohort study was to evaluate the outcome in aSAH-patients treated with CIAN.

Methods

CIAN was initiated and ended based on the clinical evaluation and transcranial Doppler (TCD), CT-angiography, CT-perfusion (PCT), and digital subtraction angiography (DSA). Nimodipine (0.5–2.0 mg/h) was administered continuously through microcatheters placed in the extracranial internal carotid and/or vertebral artery. Primary outcome measures were Glasgow Outcome Scale (GOS) at discharge and within 1 year after aSAH, and the occurrence of minor and major (<⅓ and >⅓ of LVV-affected territory) DCI-related infarctions in subsequent CT/MRI-scans. Secondary outcome measures were CIAN-associated complications.

Results

A total of 17 patients underwent CIAN. Median onset of CIAN was 9 (3–13) days after aSAH, median duration was 5 (1–13) days. A favorable outcome (GOS 4–5) was achieved in 9 patients (53%) at discharge and in 13 patients within 1 year (76%). One patient died of posthemorrhagic cerebral edema. Minor cerebral infarctions occurred in five and major infarctions in three patients. One patient developed cerebral edema possibly due to CIAN. Normalization of PCT-parameters within 2 days was observed in 9/17 patients. Six patients showed clinical response and thus did not require PCT imaging.

Conclusion

The favorable outcome in 76% of patients after 1 year is in line with previous studies. CIAN thus may be used to treat patients with severe therapy-refractory DCI.

AI Denoising Significantly Improves Image Quality in Whole-Body Low-Dose Computed Tomography Staging

(1) Background: To evaluate the effects of an AI-based denoising post-processing software solution in low-dose whole-body computer tomography (WBCT) stagings; (2) Methods: From 1 January 2019 to 1 January 2021, we retrospectively included biometrically matching melanoma patients with clinically indicated WBCT staging from two scanners. The scans were reconstructed using weighted filtered back-projection (wFBP) and Advanced Modeled Iterative Reconstruction strength 2 (ADMIRE 2) at 100% and simulated 50%, 40%, and 30% radiation doses. Each dataset was post-processed using a novel denoising software solution. Five blinded radiologists independently scored subjective image quality twice with 6 weeks between readings. Inter-rater agreement and intra-rater reliability were determined with an intraclass correlation coefficient (ICC). An adequately corrected mixed-effects analysis was used to compare objective and subjective image quality. Multiple linear regression measured the contribution of “Radiation Dose”, “Scanner”, “Mode”, “Rater”, and “Timepoint” to image quality. Consistent regions of interest (ROI) measured noise for objective image quality; (3) Results: With good–excellent inter-rater agreement and intra-rater reliability (Timepoint 1: ICC ≥ 0.82, 95% CI 0.74–0.88; Timepoint 2: ICC ≥ 0.86, 95% CI 0.80–0.91; Timepoint 1 vs. 2: ICC ≥ 0.84, 95% CI 0.78–0.90; all p ≤ 0.001), subjective image quality deteriorated significantly below 100% for wFBP and ADMIRE 2 but remained good–excellent for the post-processed images, regardless of input (p ≤ 0.002). In regression analysis, significant increases in subjective image quality were only observed for higher radiation doses (≥0.78, 95%CI 0.63–0.93; p < 0.001), as well as for the post-processed images (≥2.88, 95%CI 2.72–3.03, p < 0.001). All post-processed images had significantly lower image noise than their standard counterparts (p < 0.001), with no differences between the post-processed images themselves. (4) Conclusions: The investigated AI post-processing software solution produces diagnostic images as low as 30% of the initial radiation dose (3.13 ± 0.75 mSv), regardless of scanner type or reconstruction method. Therefore, it might help limit patient radiation exposure, especially in the setting of repeated whole-body staging examinations.

Diagnostic Performance of a Contrast-Enhanced Ultra-Low-Dose High-Pitch CT Protocol with Reduced Scan Range for Detection of Pulmonary Embolisms

(1) Background: To evaluate the diagnostic performance of a simulated ultra-low-dose (ULD), high-pitch computed tomography pulmonary angiography (CTPA) protocol with low tube current (mAs) and reduced scan range for detection of pulmonary embolisms (PE). (2) Methods: We retrospectively included 130 consecutive patients (64 ± 16 years, 69 female) who underwent clinically indicated high-pitch CTPA examination for suspected acute PE on a 3rd generation dual-source CT scanner (SOMATOM FORCE, Siemens Healthineers, Forchheim, Germany). ULD datasets with a realistic simulation of 25% mAs, reduced scan range (aortic arch-basal pericardium), and Advanced Modeled Iterative Reconstruction (ADMIRE®, Siemens Healthineers, Forchheim, Germany) strength 5 were created. The effective radiation dose (ED) of both datasets (standard and ULD) was estimated using a dedicated dosimetry software solution. Subjective image quality and diagnostic confidence were evaluated independently by three reviewers using a 5-point Likert scale. Objective image quality was compared using noise measurements. For assessment of diagnostic accuracy, patients and pulmonary vessels were reviewed binarily for affection by PE, using standard CTPA protocol datasets as the reference standard. Percentual affection of pulmonary vessels by PE was computed for disease severity (modified Qanadli score). (3) Results: Mean ED in ULD protocol was 0.7 ± 0.3 mSv (16% of standard protocol: 4.3 ± 1.7 mSv, p < 0.001, r > 0.5). Comparing ULD to standard protocol, subjective image quality and diagnostic confidence were comparably good (p = 0.486, r > 0.5) and image noise was significantly lower in ULD (p < 0.001, r > 0.5). A total of 42 patients (32.2%) were affected by PE. ULD protocol had a segment-based false-negative rate of only 0.1%. Sensitivity for detection of any PE was 98.9% (95% CI, 97.2-99.7%), specificity was 100% (95% CI, 99.8-100%), and overall accuracy was 99.9% (95% CI, 98.6-100%). Diagnoses correlated strongly between ULD and standard protocol (Chi-square (1) = 42, p < 0.001) with a decrease in disease severity of only 0.48% (T = 1.667, p = 0.103). (4) Conclusions: Compared to a standard CTPA protocol, the proposed ULD protocol proved reliable in detecting and ruling out acute PE with good levels of image quality and diagnostic confidence, as well as significantly lower image noise, at 0.7 ± 0.3 mSv (84% dose reduction).

Cerebral CT Perfusion in Acute Stroke: The Effect of Lowering the Tube Load and Sampling Rate on the Reproducibility of Parametric Maps

The aim of this study was to define lower dose parameters (tube load and temporal sampling) for CT perfusion that still preserve the diagnostic efficiency of the derived parametric maps. Ninety stroke CT examinations from four clinical sites with 1 s temporal sampling and a range of tube loads (mAs) (100–180) were studied. Realistic CT noise was retrospectively added to simulate a CT perfusion protocol, with a maximum reduction of 40% tube load (mAs) combined with increased sampling intervals (up to 3 s). Perfusion maps from the original and simulated protocols were compared by: (a) similarity using a voxel-wise Pearson’s correlation coefficient r with in-house software; (b) volumetric analysis of the infarcted and hypoperfused volumes using commercial software. Pearson’s r values varied for the different perfusion metrics from 0.1 to 0.85. The mean slope of increase and cerebral blood volume present the highest r values, remaining consistently above 0.7 for all protocol versions with 2 s sampling interval. Reduction of the sampling rate from 2 s to 1 s had only modest impacts on a TMAX volume of 0.4 mL (IQR −1–3) (p = 0.04) and core volume of −1.1 mL (IQR −4–0) (p < 0.001), indicating dose savings of 50%, with no practical loss of diagnostic accuracy. The lowest possible dose protocol was 2 s temporal sampling and a tube load of 100 mAs.

Simulated Radiation Dose Reduction in Whole-Body CT on a 3rd Generation Dual-Source Scanner: An Intraindividual Comparison

To evaluate the effect of radiation dose reduction on image quality and diagnostic confidence in contrast-enhanced whole-body computed tomography (WBCT) staging. We randomly selected March 2016 for retrospective inclusion of 18 consecutive patients (14 female, 60 ± 15 years) with clinically indicated WBCT staging on the same 3rd generation dual-source CT. Using low-dose simulations, we created data sets with 100, 80, 60, 40, and 20% of the original radiation dose. Each set was reconstructed using filtered back projection (FBP) and Advanced Modeled Iterative Reconstruction (ADMIRE^®, Siemens Healthineers, Forchheim, Germany) strength 1–5, resulting in 540 datasets total. ADMIRE 2 was the reference standard for intraindividual comparison. The effective radiation dose was calculated using commercially available software. For comparison of objective image quality, noise assessments of subcutaneous adipose tissue regions were performed automatically using the software. Three radiologists blinded to the study evaluated image quality and diagnostic confidence independently on an equidistant 5-point Likert scale (1 = poor to 5 = excellent). At 100%, the effective radiation dose in our population was 13.3 ± 9.1 mSv. At 20% radiation dose, it was possible to obtain comparably low noise levels when using ADMIRE 5 (p = 1.000, r = 0.29). We identified ADMIRE 3 at 40% radiation dose (5.3 ± 3.6 mSv) as the lowest achievable radiation dose with image quality and diagnostic confidence equal to our reference standard (p = 1.000, r > 0.4). The inter-rater agreement for this result was almost perfect (ICC ≥ 0.958, 95% CI 0.909–0.983). On a 3rd generation scanner, it is feasible to maintain good subjective image quality, diagnostic confidence, and image noise in single-energy WBCT staging at dose levels as low as 40% of the original dose (5.3 ± 3.6 mSv), when using ADMIRE 3.

Effects of simulated dose variation on contrast-enhanced CT-based radiomic analysis for Non-Small Cell Lung Cancer

PURPOSE

To examine the potential effect of CT dose variation on radiomic features in vivo using simulated contrast-enhanced CT dose reduction in patients with non-small lung cell cancer (NSCLC).

METHODS

In this retrospective study, we included 69 patients (25 females, 44 males, median age 66 years) with histologically proven NSCLC who underwent a whole contrast-enhanced body FDG-PET/CT for primary staging. To simulate different CT dose levels, we used an algorithm to simulate low-dose CT images based on a noise model derived from phantom experiments. The tumor lesions and reference regions in the paraspinal muscle were manually segmented to obtain three-dimensional regions of interest. Radiomic feature extraction was performed using the PyRadiomics toolbox. The median relative feature value deviation was assessed for each feature and each dose level.

RESULTS

The mean segmented tumor volume was 340 ml. T-stages of the primary tumors were primarily T3/4. For NSCLCs, the median relative feature value deviation in the lowest dose images varied for the calculated features from 52.2% to -49.5%. In general, dose-dependent deviations of feature values showed a monotonous increase or decrease with decreasing dose levels. Statistical analyses revealed significant differences between the dose levels in 91% of features.

CONCLUSIONS

We examined the effects of simulated CT dose reduction on the values of radiomic features in primary NSCLC and showed significant deviations of varying degrees in numerous feature classes. This is a theoretical indicator of potential influence under real conditions, which should be taken into account in clinical use.

Evaluation of skeletal muscle perfusion in a canine hind limb ischemia model using CT perfusion imaging

PURPOSE

To evaluate skeletal muscle perfusion in a canine hind limb ischemia model using CT perfusion imaging (CTPI).

METHODS

Twelve beagles underwent embolization at the branch of the left deep femoral artery. The right hind limbs were used as controls. CTPI was performed immediately after embolization. The perfusion parameters of the regions of interest (ROI), including blood volume (BV), blood flow (BF), mean transit time (MTT) and permeability (PMB), were obtained in both the lateral and posterior hind limb muscle groups.

RESULTS

After embolization, the BV, BF and PMB values in the lateral muscles of the left hind limbs were significantly lower than those in the right hind limbs (P > 0.05), and the MTT was significantly prolonged (P > 0.05). The values for BV, BF, MTT and PMB in the posterior muscles of the left hind limbs were not significantly different from those in the right hind limbs (P > 0.05). The values for BV, BF and PMB in the lateral muscles of the left hind limbs were significantly lower than those in the posterior muscles of the left hind limbs (P > 0.05).

CONCLUSION

CTPI could be used to evaluate skeletal muscle perfusion in a canine model, which may have clinical relevance in lower limb ischemia and vascular reconstruction.

Effects of Radiation Dose Reduction on Diagnostic Accuracy of Abdominal CT in Young Adults with Suspected Acute Diverticulitis: A Retrospective Intraindividual Analysis

RATIONALE AND OBJECTIVES

To assess the effects of radiation dose reduction on image quality and diagnostic accuracy of abdominal computed tomography (CT) in young adults with suspected acute diverticulitis.

MATERIALS AND METHODS

Fifty-four patients ≤40 years who received contrast-enhanced abdominal CT for suspected acute diverticulitis were included. Low-dose CT (LDCT) datasets (25%, 50%, and 75% of the original dose) were generated using sinogram synthesis and quantum noise modeling. A five-point scale was used to assess images qualitatively (overall image quality, noise, artefacts, and sharpness) and for diagnostic confidence (5 being the best possible outcome). Furthermore, the diagnostic accuracy was determined for the presence of acute diverticulitis.

RESULTS

Among 54 patients (mean age: 35.2 ± 5.3 years, 77.8% male), the prevalence of acute diverticulitis was high (57.4%). Subjective image quality was highest for original datasets and lowest for LDCT datasets with 25% of the original dose (median [interquartile range]: 5 [5] vs. 3 [2-3], p < 0.001). Diagnostic confidence was high for all datasets down to 50% of the original dose, while 25% LDCT datasets were associated with a significantly decreased diagnostic confidence (p < 0.001). Diagnostic accuracy was high for all LDCT and original datasets (sensitivity: 100%, negative predictive value [NPV]: 100% for 75% and 100% dose levels; sensitivity: 96.8%, NPV: 95.8% for 50% dose level; sensitivity: 93.6%, NPV: 91.7% for 25% dose level, respectively). Inter-rater agreement regarding the detection of diverticulitis was almost perfect at doses ≥50% (kappa: >0.81), while lower for datasets of 25% of the original radiation dose agreement (kappa: 0.67-0.78).

CONCLUSION

Radiation dose reduction down to 50% of the original radiation exposure permits high image quality, diagnostic confidence, and accuracy for the assessment of acute diverticulitis in abdominal CT in young adults without the use of iterative reconstruction algorithms.