Reproducibility assessment of rapid strains in cardiac MRI: Insights and recommendations for clinical application

PURPOSE

Studies have shown the incremental value of strain imaging in various cardiac diseases. However, reproducibility and generalizability has remained an issue of concern. To overcome this, simplified algorithms such as rapid atrioventricular strains have been proposed. This multicenter study aimed to assess the reproducibility of rapid strains in a real-world setting and identify potential predictors for higher interobserver variation.

METHODS

A total of 4 sites retrospectively identified 80 patients and 80 healthy controls who had undergone cardiac magnetic resonance imaging (CMR) at their respective centers using locally available scanners with respective field strengths and imaging protocols. Strain and volumetric parameters were measured at each site and then independently re-evaluated by a blinded core lab. Intraclass correlation coefficients (ICC) and Bland-Altman plots were used to assess inter-observer agreement. In addition, backward multiple linear regression analysis was performed to identify predictors for higher inter-observer variation.

RESULTS

There was excellent agreement between sites in feature-tracking and rapid strain values (ICC ≥ 0.96). Bland-Altman plots showed no significant bias. Bi-atrial feature-tracking and rapid strains showed equally excellent agreement (ICC ≥ 0.96) but broader limits of agreement (≤18.0 % vs. ≤3.5 %). Regression analysis showed that higher field strength and lower temporal resolution (>30 ms) independently predicted reduced interobserver agreement for bi-atrial strain parameters (ß = 0.38, p = 0.02 for field strength and ß = 0.34, p = 0.02 for temporal resolution).

CONCLUSION

Simplified rapid left ventricular and bi-atrial strain parameters can be reliably applied in a real-world multicenter setting. Due to the results of the regression analysis, a minimum temporal resolution of 30 ms is recommended when assessing atrial deformation.

A novel reporting workflow for automated integration of artificial intelligence results into structured radiology reports

OBJECTIVES

Artificial intelligence (AI) has tremendous potential to help radiologists in daily clinical routine. However, a seamless, standardized, and time-efficient way of integrating AI into the radiology workflow is often lacking. This constrains the full potential of this technology. To address this, we developed a new reporting pipeline that enables automated pre-population of structured reports with results provided by AI tools.

METHODS

Findings from a commercially available AI tool for chest X-ray pathology detection were sent to an IHE-MRRT-compliant structured reporting (SR) platform as DICOM SR elements and used to automatically pre-populate a chest X-ray SR template. Pre-populated AI results could be validated, altered, or deleted by radiologists accessing the SR template. We assessed the performance of this newly developed AI to SR pipeline by comparing reporting times and subjective report quality to reports created as free-text and conventional structured reports.

RESULTS

Chest X-ray reports with the new pipeline could be created in significantly less time than free-text reports and conventional structured reports (mean reporting times: 66.8 s vs. 85.6 s and 85.8 s, respectively; both p < 0.001). Reports created with the pipeline were rated significantly higher quality on a 5-point Likert scale than free-text reports (p < 0.001).

CONCLUSION

The AI to SR pipeline offers a standardized, time-efficient way to integrate AI-generated findings into the reporting workflow as parts of structured reports and has the potential to improve clinical AI integration and further increase synergy between AI and SR in the future.

CRITICAL RELEVANCE STATEMENT

With the AI-to-structured reporting pipeline, chest X-ray reports can be created in a standardized, time-efficient, and high-quality manner. The pipeline has the potential to improve AI integration into daily clinical routine, which may facilitate utilization of the benefits of AI to the fullest.

KEY POINTS

• A pipeline was developed for automated transfer of AI results into structured reports. • Pipeline chest X-ray reporting is faster than free-text or conventional structured reports. • Report quality was also rated higher for reports created with the pipeline. • The pipeline offers efficient, standardized AI integration into the clinical workflow.

Feature-Tracking Strain Parameters Differ Between Highly Accelerated and Conventional Acquisitions: A Multisoftware Assessment

BACKGROUND

Cardiac magnetic resonance imaging protocols have been adapted to fit the needs for faster, more efficient acquisitions, resulting in the development of highly accelerated, compressed sensing-based (CS) sequences. The aim of this study was to evaluate intersoftware and interacquisition differences for postprocessing software applied to both CS and conventional cine sequences.

MATERIALS AND METHODS

A total of 106 individuals (66 healthy volunteers, 40 patients with dilated cardiomyopathy, 51% female, 38±17 y) underwent cardiac magnetic resonance at 3T with retrospectively gated conventional cine and CS sequences. Postprocessing was performed using 2 commercially available software solutions and 1 research prototype from 3 different developers. The agreement of clinical and feature-tracking strain parameters between software solutions and acquisition types was assessed by Bland-Altmann analyses and intraclass correlation coefficients. Differences between softwares and acquisitions were assessed using Kruskal-Wallis analysis of variances. In addition, receiver operating characteristic curve-derived cutoffs were used to evaluate whether sequence-specific cutoffs influence disease classification.

RESULTS

There were significant intersoftware ( P <0.002 for all except LV end-diastolic volume per body surface area) and interacquisition differences ( P <0.02 for all except end-diastolic volume per body surface area from Neosoft, left ventricular mass per body surface area from cvi42 and TrufiStrain and global circumferential strain from Neosoft). However, the intraclass correlation coefficients between acquisitions were strong-to-excellent for all parameters (all ≥0.81). In comparing individual softwares to a pooled mean, Bland-Altmann analyses revealed smaller magnitudes of bias for cine acquisition than for CS acquisition. In addition, the application of conventional cutoffs to CS measurements did not result in the false reclassification of patients.

CONCLUSION

Significantly lower magnitudes of strain and volumetric parameters were observed in retrospectively gated CS acquisitions, despite strong-to-excellent agreement amongst software solutions and acquisition types. It remains important to be aware of the acquisition type in the context of follow-up examinations, where different cutoffs might lead to misclassifications.

Photon-Counting Detector CT Virtual Monoenergetic Images for Coronary Artery Stenosis Quantification: Phantom and In Vivo Evaluation

BACKGROUND. Calcium blooming causes stenosis overestimation on coronary CTA. OBJECTIVE. The purpose of this article was to evaluate the impact of virtual monoenergetic imaging (VMI) reconstruction level on coronary artery stenosis quantification using photon-counting detector (PCD) CT. METHODS. A phantom containing two custom-made vessels (representing 25% and 50% stenosis) underwent PCD CT acquisitions without and with simulated cardiac motion. A retrospective analysis was performed of 33 patients (seven women, 26 men; mean age, 71.3 ± 9.0 [SD] years; 64 coronary artery stenoses) who underwent coronary CTA by PCD CT followed by invasive coronary angiography (ICA). Scans were reconstructed at nine VMI energy levels (40-140 keV). Percentage diameter stenosis (PDS) was measured, and bias was determined from the ground-truth stenosis percentage in the phantom and ICA-derived quantitative coronary angiography measurements in patients. Extent of blooming artifact was measured in the phantom and in calcified and mixed plaques in patients. RESULTS. In the phantom, PDS decreased for 25% stenosis from 59.9% (40 keV) to 13.4% (140 keV) and for 50% stenosis from 81.6% (40 keV) to 42.3% (140 keV). PDS showed lowest bias for 25% stenosis at 90 keV (bias, 1.4%) and for 50% stenosis at 100 keV (bias, -0.4%). Blooming artifacts decreased for 25% stenosis from 61.5% (40 keV) to 35.4% (140 keV) and for 50% stenosis from 82.7% (40 keV) to 52.1% (140 keV). In patients, PDS for calcified plaque decreased from 70.8% (40 keV) to 57.3% (140 keV), for mixed plaque decreased from 69.8% (40 keV) to 56.3% (140 keV), and for noncalcified plaque was 46.6% at 40 keV and 54.6% at 140 keV. PDS showed lowest bias for calcified plaque at 100 keV (bias, 17.2%), for mixed plaque at 140 keV (bias, 5.0%), and for noncalcified plaque at 40 keV (bias, -0.5%). Blooming artifacts decreased for calcified plaque from 78.4% (40 keV) to 48.6% (140 keV) and for mixed plaque from 73.1% (40 keV) to 44.7% (140 keV). CONCLUSION. For calcified and mixed plaque, stenosis severity measurements and blooming artifacts decreased at increasing VMI reconstruction levels. CLINICAL IMPACT. PCD CT with VMI reconstruction helps overcome current limitations in stenosis quantification on coronary CTA.

Ultrahigh-Spatial-Resolution Photon-counting Detector CT Angiography of Coronary Artery Disease for Stenosis Assessment

Background Coronary CT angiography is a first-line test in coronary artery disease but is limited by severe calcifications. Photon-counting-detector (PCD) CT improves spatial resolution. Purpose To investigate the effect of improved spatial resolution on coronary stenosis assessment and reclassification. Materials and Methods Coronary stenoses were evaluated prospectively in a vessel phantom (in vitro) containing two stenoses (25%, 50%), and retrospectively in patients (in vivo) who underwent ultrahigh-spatial-resolution cardiac PCD CT (from July 2022 to April 2023). Images were reconstructed at standard resolution (section thickness, 0.6 mm; increment, 0.4 mm; Bv44 kernel), high spatial resolution (section thickness, 0.4 mm; increment, 0.2 mm; Bv44 kernel), and ultrahigh spatial resolution (section thickness, 0.2; increment, 0.1 mm; Bv64 kernel). Percentages of diameter stenosis (DS) were compared between reconstructions. In vitro values were compared with the manufacturer specifications of the phantom and patient results were assessed regarding effects on Coronary Artery Disease Reporting and Data System (CAD-RADS) reclassification. Results The in vivo sample included 114 patients (mean age, 68 years ± 9 [SD]; 71 male patients). In vitro percentage DS measurements were more accurate with increasing spatial resolution for both 25% and 50% stenoses (mean bias for standard resolution, high spatial resolution, and ultrahigh spatial resolution, respectively: 10.1%, 8.0%, and 2.3%; P < .001). In vivo results confirmed decreasing median percentage DS with increasing spatial resolution for calcified stenoses (n = 161) (standard resolution, high spatial resolution, and ultrahigh spatial resolution, respectively: 41.5% [IQR, 27.3%-58.2%], 34.8% [IQR, 23.7%-55.1%], and 26.7% [IQR, 18.6%-44.3%]; P < .001), whereas noncalcified (n = 13) and mixed plaques (n = 19) did not show evidence of a difference (P ≥ .88). Ultrahigh-spatial-resolution reconstructions led to reclassification of 62 of 114 (54.4%) patients to lower CAD-RADS category than that assigned using standard resolution. Conclusion In vivo and in vitro coronary stenosis assessment improved for calcified stenoses by using ultrahigh-spatial-resolution PCD CT reconstructions, leading to lower percentage DS compared with standard resolution and clinically relevant rates of reclassification. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by McCollough in this issue.

Medical Imaging Decision And Support (MIDAS): Study protocol for a multi-centre cluster randomized trial evaluating the ESR iGuide

OBJECTIVES

Medical imaging plays an essential role in healthcare. As a diagnostic test, imaging is prone to substantial overuse and potential overdiagnosis, with dire consequences to patient outcomes and health care costs. Clinical decision support systems (CDSSs) were developed to guide referring physicians in making appropriate imaging decisions. This study will evaluate the effect of implementing a CDSS (ESR iGuide) with versus without active decision support in a physician order entry on the appropriate use of imaging tests and ordering behaviour.

METHODS

A protocol for a multi-center cluster-randomized trial with departments acting as clusters, combined with a before-after-revert design. Four university hospitals with eight participating departments each for a total of thirty-two clusters will be included in the study. All departments start in control condition with structured data entry of the clinical indication and tracking of the imaging exams requested. Initially, the CDSS is implemented and all physicians remain blinded to appropriateness scores based on the ESR imaging referral guidelines. After randomization, half of the clusters switch to the active intervention of decision support. Physicians in the active condition are made aware of the categorization of their requests as appropriate, under certain conditions appropriate, or inappropriate, and appropriate exams are suggested. Physicians may change their requests in response to feedback. In the revert condition, active decision support is removed to study the educational effect.

RESULTS/CONCLUSIONS

The main outcome is the proportion of inappropriate diagnostic imaging exams requested per cluster. Secondary outcomes are the absolute number of imaging exams, radiation from diagnostic imaging, and medical costs.

TRIAL REGISTRATION NUMBER

Approval from the Medical Ethics Review Committee was obtained under protocol numbers 20-069 (Augsburg), B 238/21 (Kiel), 20-318 (Lübeck) and 2020-15,125 (Mainz). The trial is registered in the ClinicalTrials.gov register under registration number NCT05490290.

Convolutional neural network-based kidney volume estimation from low-dose unenhanced computed tomography scans

PURPOSE

Kidney volume is important in the management of renal diseases. Unfortunately, the currently available, semi-automated kidney volume determination is time-consuming and prone to errors. Recent advances in its automation are promising but mostly require contrast-enhanced computed tomography (CT) scans. This study aimed at establishing an automated estimation of kidney volume in non-contrast, low-dose CT scans of patients with suspected urolithiasis.

METHODS

The kidney segmentation process was automated with 2D Convolutional Neural Network (CNN) models trained on manually segmented 2D transverse images extracted from low-dose, unenhanced CT scans of 210 patients. The models' segmentation accuracy was assessed using Dice Similarity Coefficient (DSC), for the overlap with manually-generated masks on a set of images not used in the training. Next, the models were applied to 22 previously unseen cases to segment kidney regions. The volume of each kidney was calculated from the product of voxel number and their volume in each segmented mask. Kidney volume results were then validated against results semi-automatically obtained by radiologists.

RESULTS

The CNN-enabled kidney volume estimation took a mean of 32 s for both kidneys in a CT scan with an average of 1026 slices. The DSC was 0.91 and 0.86 and for left and right kidneys, respectively. Inter-rater variability had consistencies of ICC = 0.89 (right), 0.92 (left), and absolute agreements of ICC = 0.89 (right), 0.93 (left) between the CNN-enabled and semi-automated volume estimations.

CONCLUSION

In our work, we demonstrated that CNN-enabled kidney volume estimation is feasible and highly reproducible in low-dose, non-enhanced CT scans. Automatic segmentation can thereby quantitatively enhance radiological reports.

Structured reporting in radiology enables epidemiological analysis through data mining: urolithiasis as a use case

PURPOSE

To investigate the epidemiology and distribution of disease characteristics of urolithiasis by data mining structured radiology reports.

METHODS

The content of structured radiology reports of 2028 urolithiasis CTs was extracted from the department's structured reporting (SR) platform. The investigated cohort represented the full spectrum of a tertiary care center, including mostly symptomatic outpatients as well as inpatients. The prevalences of urolithiasis in general and of nephro- and ureterolithasis were calculated. The distributions of age, sex, calculus size, density and location, and the number of ureteral and renal calculi were calculated. For ureterolithiasis, the impact of calculus characteristics on the degree of possible obstructive uropathy was calculated.

RESULTS

The prevalence of urolithiasis in the investigated cohort was 72%. Of those patients, 25% had nephrolithiasis, 40% ureterolithiasis, and 35% combined nephro- and ureterolithiasis. The sex distribution was 2.3:1 (M:F). The median patient age was 50 years (IQR 36-62). The median number of calculi per patient was 1. The median size of calculi was 4 mm, and the median density was 734 HU. Of the patients who suffered from ureterolithiasis, 81% showed obstructive uropathy, with 2nd-degree uropathy being the most common. Calculus characteristics showed no impact on the degree of obstructive uropathy.

CONCLUSION

SR-based data mining is a simple method by which to obtain epidemiologic data and distributions of disease characteristics, for the investigated cohort of urolithiasis patients. The added information can be useful for multiple purposes, such as clinical quality assurance, radiation protection, and scientific or economic investigations. To benefit from these, the consistent use of SR is mandatory. However, in clinical routine SR usage can be elaborate and requires radiologists to adapt.

Photon-counting detector CT-based virtual monoenergetic reconstructions: repeatability and reproducibility of radiomics features of an organic phantom and human myocardium

BACKGROUND

Photon-counting detector computed tomography (PCD-CT) may influence imaging characteristics for various clinical conditions due to higher signal and contrast-to-noise ratio in virtual monoenergetic images (VMI). Radiomics analysis relies on quantification of image characteristics. We evaluated the impact of different VMI reconstructions on radiomic features in in vitro and in vivo PCD-CT datasets.

METHODS

An organic phantom consisting of twelve samples (four oranges, four onions, and four apples) was scanned five times. Twenty-three patients who had undergone coronary computed tomography angiography on a first generation PCD-CT system with the same image acquisitions were analyzed. VMIs were reconstructed at 6 keV levels (40, 55, 70, 90, 120, and 190 keV). The phantoms and the patients' left ventricular myocardium (LVM) were segmented for all reconstructions. Ninety-three original radiomic features were extracted. Repeatability and reproducibility were evaluated through intraclass correlations coefficient (ICC) and post hoc paired samples ANOVA t test.

RESULTS

There was excellent repeatability for radiomic features in phantom scans (all ICC = 1.00). Among all VMIs, 36/93 radiomic features (38.7%) in apples, 28/93 (30.1%) in oranges, and 33/93 (35.5%) in onions were not significantly different. For LVM, the percentage of stable features was high between VMIs ≥ 90 keV (90 versus 120 keV, 77.4%; 90 versus 190 keV, 83.9%; 120 versus 190 keV, 89.3%), while comparison to lower VMI levels led to fewer reproducible features (40 versus 55 keV, 8.6%).

CONCLUSIONS

VMI levels influence the stability of radiomic features in an organic phantom and patients' LVM; stability decreases considerably below 90 keV.

RELEVANCE STATEMENT

Spectral reconstructions significantly influence radiomic features in vitro and in vivo, necessitating standardization and careful attention to these reconstruction parameters before clinical implementation.

KEY POINTS

• Radiomic features have an excellent repeatability within the same PCD-CT acquisition and reconstruction. • Differences in VMI lead to decreased reproducibility for radiomic features. • VMI ≥ 90 keV increased the reproducibility of the radiomic features.

Impact of Cardiac Motion on coronary artery calcium scoring using a virtual non-iodine algorithm on photon-counting detector CT: a dynamic phantom study

This study assessed the impact of cardiac motion and in-vessel attenuation on coronary artery calcium (CAC) scoring using virtual non-iodine (VNI) against virtual non-contrast (VNC) reconstructions on photon-counting detector CT. Two artificial vessels containing calcifications and different in-vessel attenuations (500, 800HU) were scanned without (static) and with cardiac motion (60, 80, 100 beats per minute [bpm]). Images were post-processed using a VNC and VNI algorithm at 70 keV and quantum iterative reconstruction (QIR) strength 2. Calcium mass, Agatston scores, cardiac motion susceptibility (CMS)-indices were compared to physical mass, static scores as well as between reconstructions, heart rates and in-vessel attenuations. VNI scores decreased with rising heart rate (p < 0.01) and showed less underestimation than VNC scores (p < 0.001). Only VNI scores were similar to the physical mass at static measurements, and to static scores at 60 bpm. Agatston scores using VNI were similar to static scores at 60 and 80 bpm. Standard deviation of CMS-indices was lower for VNI-based than for VNC-based CAC scoring. VNI scores were higher at 500 than 800HU (p < 0.001) and higher than VNC scores (p < 0.001) with VNI scores at 500 HU showing the lowest deviation from the physical reference. VNI-based CAC quantification is influenced by cardiac motion and in-vessel attenuation, but least when measuring Agatston scores, where it outperforms VNC-based CAC scoring.

Soft Reconstruction Kernels Improve HCC Imaging on a Photon-Counting Detector CT

RATIONALE AND OBJECTIVES

Hepatocellular carcinoma (HCC) is the only tumor entity that allows non-invasive diagnosis based on imaging without further histological proof. Therefore, excellent image quality is of utmost importance for HCC diagnosis. Novel photon-counting detector (PCD) CT improves image quality via noise reduction and higher spatial resolution, inherently providing spectral information. The aim of this study was to investigate these improvements for HCC imaging with triple-phase liver PCD-CT in a phantom and patient population study focusing on identification of the optimal reconstruction kernel.

MATERIALS AND METHODS

Phantom experiments were performed to analyze objective quality characteristics of the regular body and quantitative reconstruction kernels, each with four sharpness levels (36-40-44-48). For 24 patients with viable HCC lesions on PCD-CT, virtual monoenergetic images at 50 keV were reconstructed using these kernels. Quantitative image analysis included contrast-to-noise ratio (CNR) and edge sharpness. Three raters performed qualitative analyses evaluating noise, contrast, lesion conspicuity, and overall image quality.

RESULTS

In all contrast phases, the CNR was highest using the kernels with a sharpness level of 36 (all p < 0.05), with no significant influence on lesion sharpness. Softer reconstruction kernels were also rated better regarding noise and image quality (all p < 0.05). No significant differences were found in image contrast and lesion conspicuity. Comparing body and quantitative kernels with equal sharpness levels, there was no difference in image quality criteria, neither regarding in vitro nor in vivo analysis.

CONCLUSION

Soft reconstruction kernels yield the best overall quality for the evaluation of HCC in PCD-CT. As the image quality of quantitative kernels with potential for spectral post-processing is not restricted compared to regular body kernels, they should be preferred.

Quantum iterative reconstruction on a photon-counting detector CT improves the quality of hepatocellular carcinoma imaging

BACKGROUND

Excellent image quality is crucial for workup of hepatocellular carcinoma (HCC) in patients with liver cirrhosis because a signature tumor signal allows for non-invasive diagnosis without histologic proof. Photon-counting detector computed tomography (PCD-CT) can enhance abdominal image quality, especially in combination with a novel iterative reconstruction algorithm, quantum iterative reconstruction (QIR). The purpose of this study was to analyze the impact of different QIR levels on PCD-CT imaging of HCC in both phantom and patient scans.

METHODS

Virtual monoenergetic images at 50 keV were reconstructed using filtered back projection and all available QIR levels (QIR 1-4). Objective image quality properties were investigated in phantom experiments. The study also included 44 patients with triple-phase liver PCD-CT scans of viable HCC lesions. Quantitative image analysis involved assessing the noise, contrast, and contrast-to-noise ratio of the lesions. Qualitative image analysis was performed by three raters evaluating noise, artifacts, lesion conspicuity, and overall image quality using a 5-point Likert scale.

RESULTS

Noise power spectra in the phantom experiments showed increasing noise suppression with higher QIR levels without affecting the modulation transfer function. This pattern was confirmed in the in vivo scans, in which the lowest noise levels were found in QIR-4 reconstructions, with around a 50% reduction in median noise level compared with the filtered back projection images. As contrast does not change with QIR, QIR-4 also yielded the highest contrast-to-noise ratios. With increasing QIR levels, rater scores were significantly better for all qualitative image criteria (all p < .05).

CONCLUSIONS

Without compromising image sharpness, the best image quality of iodine contrast optimized low-keV virtual monoenergetic images can be achieved using the highest QIR level to suppress noise. Using these settings as standard reconstruction for HCC in PCD-CT imaging might improve diagnostic accuracy and confidence.

Cardiac MRI Findings in Patients Clinically Referred for Evaluation of Post-Acute Sequelae of SARS-CoV-2 Infection

Persistent or recurrent cardiovascular symptoms have been identified as one of the hallmarks of long-COVID or post-acute sequelae of SARS-CoV-2 infection (PASC). The purpose of this study was to determine the prevalence and extent of cardiac abnormalities in patients referred for cardiac MRI due to clinical evidence of PASC. To investigate this, two tertiary care hospitals identified all patients who were referred for cardiac MRI under the suspicion of PASC in a 2-year period and retrospectively included them in this study. Patients with previously known cardiac diseases were excluded. This resulted in a total cohort of 129 patients (63, 51% female; age 41 ± 16 years). The majority of patients (57%) showed normal cardiac results. No patient had active myocarditis or an acute myocardial infarction. However, 30% of patients had evidence of non-ischemic myocardial fibrosis, which exceeds the prevalence in the normal adult population and suggests that a possible history of myocarditis might explain persistent symptoms in the PASC setting.

Cardiac MRI-based right-to-left ventricular blood pool T2 relaxation times ratio correlates with exercise capacity in patients with chronic heart failure

BACKGROUND

MRI T2 mapping has been proven to be sensitive to the level of blood oxygenation. We hypothesized that impaired exercise capacity in chronic heart failure is associated with a greater difference between right (RV) to left ventricular (LV) blood pool T2 relaxation times due to a higher level of peripheral blood desaturation, compared to patients with preserved exercise capacity and to healthy controls.

METHODS

Patients with chronic heart failure (n = 70) who had undergone both cardiac MRI (CMR) and a 6-min walk test (6MWT) were retrospectively identified. Propensity score matched healthy individuals (n = 35) served as control group. CMR analyses included cine acquisitions and T2 mapping to obtain blood pool T2 relaxation times of the RV and LV. Following common practice, age- and gender-adjusted nominal distances and respective percentiles were calculated for the 6MWT. The relationship between the RV/LV T2 blood pool ratio and the results from 6MWT were evaluated by Spearman's correlation coefficients and regression analyses. Inter-group differences were assessed by independent t-tests and univariate analysis of variance.

RESULTS

The RV/LV T2 ratio moderately correlated with the percentiles of nominal distances in the 6MWT (r = 0.66) while ejection fraction, end-diastolic and end-systolic volumes showed no correlation (r = 0.09, 0.07 and - 0.01, respectively). In addition, there were significant differences in the RV/LV T2 ratio between patients with and without significant post-exercise dyspnea (p = 0.001). Regression analyses showed that RV/LV T2 ratio was an independent predictor of the distance walked and the presence of post-exercise dyspnea (p < 0.001).

CONCLUSION

The proposed RV/LV T2 ratio, obtained by two simple measurements on a routinely acquired four-chamber T2 map, was superior to established parameters of cardiac function to predict exercise capacity and the presence of post-exercise dyspnea in patients with chronic heart failure.

Optimization of Kernel Type and Sharpness Level Improves Objective and Subjective Image Quality for High-Pitch Photon Counting Coronary CT Angiography

(1) Background: Photon-counting detector (PCD) CT offers a wide variety of kernels and sharpness levels for image reconstruction. The aim of this retrospective study was to determine optimal settings for coronary CT angiography (CCTA). (2) Methods: Thirty patients (eight female, mean age 63 ± 13 years) underwent PCD-CCTA in a high-pitch mode. Images were reconstructed using three different kernels and four sharpness levels (Br36/40/44/48, Bv36/40/44/48, and Qr36/40/44/48). To analyze objective image quality, the attenuation, image noise, contrast-to-noise ratio (CNR), and vessel sharpness were quantified in proximal and distal coronaries. For subjective image quality, two blinded readers assessed image noise, visually sharp reproduction of coronaries, and the overall image quality using a five-point Likert scale. (3) Results: Attenuation, image noise, CNR, and vessel sharpness significantly differed across kernels (all p < 0.001), with the Br-kernel reaching the highest attenuation. With increasing kernel sharpness, image noise and vessel sharpness increased, whereas CNR continuously decreased. Reconstruction with Br-kernel generally had the highest CNR (Br > Bv > Qr), except Bv-kernel had a superior CNR at sharpness level 40. Bv-kernel had significantly higher vessel sharpness than Br- and Qr-kernel (p < 0.001). Subjective image quality was rated best for kernels Bv40 and Bv36, followed by Br36 and Qr36. (4) Conclusion: Reconstructions with kernel Bv40 are beneficial to achieve optimal image quality in spectral high-pitch CCTA using PCD-CT.

Implementation of structured reporting in clinical routine: a review of 7 years of institutional experience

BACKGROUND

To evaluate the implementation process of structured reporting (SR) in a tertiary care institution over a period of 7 years.

METHODS

We analysed the content of our image database from January 2016 to December 2022 and compared the numbers of structured reports and free-text reports. For the ten most common SR templates, usage proportions were calculated on a quarterly basis. Annual modality-specific SR usage was calculated for ultrasound, CT, and MRI. During the implementation process, we surveyed radiologists and clinical referring physicians concerning their views on reporting in radiology.

RESULTS

As of December 2022, our reporting platform contained more than 22,000 structured reports. Use of the ten most common SR templates increased markedly since their implementation, leading to a mean SR usage of 77% in Q4 2022. The highest percentages of SR usage were shown for trauma CT, focussed assessment with ultrasound for trauma (FAST), and prostate MRI: 97%, 95%, and 92%, respectively, in 2022. Overall modality-specific SR usage was 17% for ultrasound, 13% for CT, and 6% for MRI in 2022. Both radiologists and referring physicians were more satisfied with structured reports and rated SR better than free-text reporting (FTR) on various attributes.

CONCLUSIONS

The increasing SR usage during the period under review and the positive attitude towards SR among both radiologists and clinical referrers show that SR can be successfully implemented. We therefore encourage others to take this step in order to benefit from the advantages of SR.

KEY POINTS

1. Structured reporting usage increased markedly since its implementation at our institution in 2016. 2. Mean usage for the ten most popular structured reporting templates was 77% in 2022. 3. Both radiologists and referring physicians preferred structured reports over free-text reports. 4. Our data shows that structured reporting can be successfully implemented. 5. We strongly encourage others to implement structured reporting at their institutions.

Intra-individual comparison of coronary calcium scoring between photon counting detector- and energy integrating detector-CT: Effects on risk reclassification

Purpose

To compare coronary artery calcium volume and score (CACS) between photon-counting detector (PCD) and conventional energy integrating detector (EID) computed tomography (CT) in a phantom and prospective patient study.

Methods

A commercially available CACS phantom was scanned with a standard CACS protocol (120 kVp, slice thickness/increment 3/1.5 mm, and a quantitative Qr36 kernel), with filtered back projection on the EID-CT, and with monoenergetic reconstruction at 70 keV and quantum iterative reconstruction off on the PCD-CT. The same settings were used to prospectively acquire data in patients (n = 23, 65 ± 12.1 years), who underwent PCD- and EID-CT scans with a median of 5.5 (3.0-12.5) days between the two scans in the period from August 2021 to March 2022. CACS was quantified using a commercially available software solution. A regression formula was obtained from the aforementioned comparison and applied to simulate risk reclassification in a pre-existing cohort of 514 patients who underwent a cardiac EID-CT between January and December 2021.

Results

Based on the phantom experiment, CACS _PCD-CT showed a more accurate measurement of the reference CAC volumes (overestimation of physical volumes: PCD-CT 66.1 ± 1.6% vs. EID-CT: 77.2 ± 0.5%). CACS _EID-CT and CACS _PCD-CT were strongly correlated, however, the latter measured significantly lower values in the phantom (CACS _PCD-CT : 60.5 (30.2-170.3) vs CACS _EID-CT 74.7 (34.6-180.8), p = 0.0015, r = 0.99, mean bias -9.7, Limits of Agreement (LoA) -36.6/17.3) and in patients (non-significant) (CACS _PCD-CT : 174.3 (11.1-872.7) vs CACS _EID-CT 218.2 (18.5-876.4), p = 0.10, r = 0.94, mean bias -41.1, LoA -315.3/232.5). The systematic lower measurements of Agatston score on PCD-CT system led to reclassification of 5.25% of our simulated patient cohort to a lower classification class.

Conclusion

CACS _PCD-CT is feasible and correlates strongly with CACS _EID-CT , however, leads to lower CACS values. PCD-CT may provide results that are more accurate for CACS than EID-CT.

Biventricular strain assessment indicates progressive impairment of myocardial contractility in phenotypically negative patients with Fabry's disease

PURPOSE

The accumulation of sphingolipids in Fabry's disease (FD) leads to left ventricular (LV) hypertrophy and shortened T1 in cardiac magnetic resonance (CMR). Early detection of myocardial involvement is essential for the timely initiation and efficacy of enzyme replacement therapy. However, there is a diagnostic gap between the onset of accumulation and detectable myocardial changes. This study aimed to evaluate the diagnostic value of biventricular strain assessment in early FD.

METHODS

Genetically proven FD patients (n = 58) and healthy volunteers (HV, n = 62) who had undergone 3 T CMR were retrospectively identified and stratified into 3 groups according to disease severity. Biventricular volumetry, global longitudinal strains (GLS), indexed biventricular masses (RVMi/LVMi), and T1 were evaluated. Group comparisons were performed by ANOVA and diagnostic accuracy was evaluated by ROC-analysis.

RESULTS

The study population included 19 group I, 20 group II and 19 group III patients. LV volumetry and T1 showed no significant difference between early FD patients and HV (all p > 0.760). However, RVMi was increased, while RV-GLS and LV-GLS were significantly impaired (p = 0.024 and < 0.001, respectively). Biventricular strains accurately discriminated early FD patients and HV with RV-GLS being non-inferior to LV-GLS (AUC for both 0.83, p > 0.05). Adding strains to the established approach using T1 and LVMi further increased diagnostic accuracy (AUC 0.99, p < 0.05).

CONCLUSIONS

Biventricular strains may help detect altered myocardial deformation patterns in phenotypically negative FD patients. These findings may lead to an earlier initiation of therapy, which in turn may slow hypertrophy and the associated long-term risks.

Myocardial Mass Corrected CMR Feature Tracking-Based Strain Ratios are Different in Pathologies With Increased Myocardial Mass

RATIONALE AND OBJECTIVES

Acute myocarditis (AM) and hypertensive heart disease (HHD) have different pathophysiological backgrounds, thus potentially showing distinct patterns of altered myocardial deformation. Therefore, CMR left ventricular (LV) feature tracking (FT)- based strain parameters were indexed to myocardial mass index (LVMi) in order to evaluate potential additional value in the differentiation among AM, HHD, and healthy volunteers (HV) compared to non-indexed conventional strain.

MATERIALS AND METHODS

Patients with AM (n = 43) and HHD (n = 28) underwent CMR at 3T. 61 HV served as controls. Cine imaging-based FT-strain analysis was performed and natural strain (nStrain) values were evaluated for gender and age specific differences in HV. Strain parameters were indexed to LVMi yielding ratio Strain (rStrain). These were evaluated for their discriminatory accuracy compared to nStrain values.

RESULTS

There were significant differences in nStrain between genders (p < 0.05), but not between age groups in HV. Circumferential strains differentiated best between HV and AM, reaching an area under the curve (AUC) of 0.86 (female) and 0.81 (male), yielding 93 (72) % sensitivity and 55 (75) % specificity. In discriminating between HV and HHD as well as AM and HHD, longitudinal strains outperformed all other parameters with AUCs of 1.00 (female)/ 0.92 (male) and 0.90 (female)/ 0.74 (male), respectively. Sensitivity and specificity levels of 100 %/ 100 % (female) and 91 %/ 72 % (male) for HV versus AM as well as 82 %/ 71 % (female) and 91%/ 57 % (male) for AM versus HHD could be demonstrated. The usage of rStrains significantly increased the AUC for circumferential and radial strains in male patients.

CONCLUSION

rStrain provided additional value in the differentiation of diseases with increased LVM. As rStrain is derived from standard native cine imaging, such parameters can be time efficiently and reliably calculated, giving them the potential to be a powerful addition to the currently developing multiparametric native diagnostic approaches.

Quantitative washout in patients with hepatocellular carcinoma undergoing TACE: an imaging biomarker for predicting prognosis?

BACKGROUND

The delayed percentage attenuation ratio (DPAR) was recently identified as a novel predictor of an early complete response in patients with hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE). In this study, we aimed to validate the role of DPAR as a predictive biomarker for short-, mid-, and long-term outcomes after TACE.

METHODS

We retrospectively reviewed laboratory and imaging data for 103 treatment-naïve patients undergoing initial TACE treatment at our tertiary care center between January 2016 and November 2020. DPAR and other washin and washout indices were quantified in the triphasic computed tomography performed before the initial TACE. The correlation of DPAR and radiologic response was investigated. Furthermore, the influence of DPAR on the 6-, 12-, 18-, and 24-month survival rates and the median overall survival (OS) was compared to other established washout indices and estimates of tumor burden and remnant liver function.

RESULTS

The DPAR was significantly of the target lesions (TLs) with objective response to TACE after the initial TACE session was significantly higher compared to patients with stable disease (SD) or progressive disease (PD) (125 (IQR 118-134) vs 110 (IQR 103-116), p < 0.001). Furthermore, the DPAR was significantly higher in patients who survived the first 6 months after TACE (122 vs. 115, p = 0.04). In addition, the number of patients with a DPAR > 120 was significantly higher in this group (n = 38 vs. n = 8; p = 0.03). However, no significant differences were observed in the 12-, 18-, and 24-month survival rates after the initial TACE. Regarding the median OS, no significant difference was observed for patients with a high DPAR compared to those with a low DPAR (18.7 months vs. 12.7 months, p = 0.260).

CONCLUSIONS

Our results confirm DPAR as the most relevant washout index for predicting the short-term outcome of patients with HCC undergoing TACE. However, DPAR and the other washout indices were not predictive of mid- and long-term outcomes.

Compressed sensing acceleration of cardiac cine imaging allows reliable and reproducible assessment of volumetric and functional parameters of the left and right atrium

Objectives

To compare volumetric and functional parameters of the atria derived from highly accelerated compressed sensing (CS)–based cine sequences in comparison to conventional (Conv) cine imaging.

Methods

CS and Conv cine sequences were acquired in 101 subjects (82 healthy volunteers (HV) and 19 patients with heart failure with reduced ejection fraction (HFrEF)) using a 3T MR scanner in this single-center study. Time-volume analysis of the left (LA) and right atria (RA) were performed in both sequences to evaluate atrial volumes and function (total, passive, and active emptying fraction). Inter-sequence and inter- and intra-reader agreement were analyzed using correlation, intraclass correlation (ICC), and Bland-Altman analysis.

Results

CS-based cine imaging led to a 69% reduction of acquisition time. There was significant difference in atrial parameters between CS and Conv cine, e.g., LA minimal volume (LAVmin) (Conv 24.0 ml (16.7–32.7), CS 25.7 ml (19.2–35.2), p < 0.0001) or passive emptying fraction (PEF) (Conv 53.9% (46.7–58.4), CS 49.0% (42.0–54.1), p < 0.0001). However, there was high correlation between the techniques, yielding good to excellent ICC (0.76–0.99) and small mean of differences in Bland-Altman analysis (e.g. LAVmin − 2.0 ml, PEF 3.3%). Measurements showed high inter- (ICC > 0.958) and intra-rater (ICC > 0.934) agreement for both techniques. CS-based parameters (PEF AUC = 0.965, LAVmin AUC = 0.864) showed equivalent diagnostic ability compared to Conv cine imaging (PEF AUC = 0.989, LAVmin AUC = 0.859) to differentiate between HV and HFrEF.

Conclusion

Atrial volumetric and functional evaluation using CS cine imaging is feasible with relevant reduction of acquisition time, therefore strengthening the role of CS in clinical CMR for atrial imaging.

Key Points

• Reliable assessment of atrial volumes and function based on compressed sensing cine imaging is feasible.

• Compressed sensing reduces scan time and has the potential to overcome obstacles of conventional cine imaging.

• No significant differences for subjective image quality, inter- and intra-rater agreement, and ability to differentiate healthy volunteers and heart failure patients were detected between conventional and compressed sensing cine imaging.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-021-07830-z.

T1 and T2 mapping to detect chronic inflammation in cardiac magnetic resonance imaging in heart failure with reduced ejection fraction

Aims

The purpose of this retrospective single‐centre study was to evaluate the non‐invasive detection of endomyocardial biopsy (EMB)‐established chronic myocardial inflammation in patients with heart failure with reduced ejection fraction (HFrEF) using T1 and T2 mapping.

Methods and results

The study population consisted of 52 retrospectively identified HFrEF patients who underwent EMB and cardiac magnetic resonance imaging at 3 Tesla. EMB was defined according to the position statement of the European Society of Cardiology and served as reference to identify inflammation in all patients. A control group of healthy volunteers with prior cardiac magnetic resonance imaging studies (n = 58) was also identified. Global and segmental T1 and T2 values as well as septal measurements and tissue heterogeneity parameters were calculated.

Out of the 52 patients with HFrEF, 33 patients had myocardial inflammation detected by EMB, while 19 patients were EMB negative for inflammation. Mean left ventricular ejection fraction was 31% in both groups (P = 0.97). Global T1 and T2 values in HFrEF patients were significantly higher compared with healthy controls (T1 1275 ± 69 ms vs. 1,175 ± 44 ms, P < 0.001; T2 40.0 ± 3.4 ms vs. 37.9 ± 1.6 ms, P < 0.001). The distribution of T1 and T2 values between patients with and without EMB‐proven chronic myocardial inflammation was not statistically different when regarding global (T1 1292 ± 71 ms vs. 1266 ± 67 ms, P = 0.26; T2 40.0 ± 2.6 ms vs. 40.0 ± 3.9 ms, P = 1.0), septal (T1 1299 ± 63 ms vs. 1289 ± 76 ms, P = 0.76; T2 40.1 ± 3.5 ms vs 40.0 ± 6.4 ms, P = 0.49) or maximum segmental values (T1 1414 ± 111 ms vs. 1363 ± 88 ms, P = 0.15; T2 47.3 ± 5.2 ms vs. 48.8 ± 11.8 ms, P = 0.53). Mean absolute deviation of segmental T1 and T2 values and log‐transformed pixel‐wise standard deviation as parameters of tissue heterogeneity did not reveal statistical significant differences between inflammation‐positive and inflammation‐negative HFrEF patients (all P > 0.4).

Conclusions

Conventionally performed quantitative T1 and T2 mapping values significantly correlated with prevalence of HFrEF but did not discriminate HFrEF patients with or without chronic myocardial inflammation in our cohort. This suggests that EMB is the preferred method to detect chronic myocardial inflammation in HFrEF.