Fast 5-minute shoulder MRI protocol with accelerated TSE-sequences and deep learning image reconstruction for the assessment of shoulder pain at 1.5 and 3 Tesla

Purpose

The objective of this study was to implement a 5-minute MRI protocol for the shoulder in routine clinical practice consisting of accelerated 2D turbo spin echo (TSE) sequences with deep learning (DL) reconstruction at 1.5 and 3 Tesla, and to compare the image quality and diagnostic performance to that of a standard 2D TSE protocol.

Methods

Patients undergoing shoulder MRI between October 2020 and June 2021 were prospectively enrolled. Each patient underwent two MRI examinations: first a standard, fully sampled TSE (TSES) protocol reconstructed with a standard reconstruction followed by a second fast, prospectively undersampled TSE protocol with a conventional parallel imaging undersampling pattern reconstructed with a DL reconstruction (TSEDL). Image quality and visualization of anatomic structures as well as diagnostic performance with respect to shoulder lesions were assessed using a 5-point Likert-scale (5 = best). Interchangeability analysis, Wilcoxon signed-rank test and kappa statistics were performed to compare the two protocols.

Results

A total of 30 participants was included (mean age 50±15 years; 15 men). Overall image quality was evaluated to be superior in TSEDL versus TSES (p<0.001). Noise and edge sharpness were evaluated to be significantly superior in TSEDL versus TSES (noise: p<0.001, edge sharpness: p<0.05). No difference was found concerning qualitative diagnostic confidence, assessability of anatomical structures (p>0.05), and quantitative diagnostic performance for shoulder lesions when comparing the two sequences.

Conclusions

A fast 5-minute TSEDL MRI protocol of the shoulder is feasible in routine clinical practice at 1.5 and 3 T, with interchangeable results concerning the diagnostic performance, allowing a reduction in scan time of more than 50% compared to the standard TSES protocol.

Shortening Acquisition Time and Improving Image Quality for Pelvic MRI Using Deep Learning Reconstruction for Diffusion-Weighted Imaging at 1.5 T

RATIONALE AND OBJECTIVES

To determine the impact on acquisition time reduction and image quality of a deep learning (DL) reconstruction for accelerated diffusion-weighted imaging (DWI) of the pelvis at 1.5 T compared to standard DWI.

MATERIALS AND METHODS

A total of 55 patients (mean age, 61 ± 13 years; range, 27-89; 20 men, 35 women) were consecutively included in this retrospective, monocentric study between February and November 2022. Inclusion criteria were (1) standard DWI (DWIS) in clinically indicated magnetic resonance imaging (MRI) at 1.5 T and (2) DL-reconstructed DWI (DWIDL). All patients were examined using the institution's standard MRI protocol according to their diagnosis including DWI with two different b-values (0 and 800 s/mm2) and calculation of apparent diffusion coefficient (ADC) maps. Image quality was qualitatively assessed by four radiologists using a visual 5-point Likert scale (5 = best) for the following criteria: overall image quality, noise level, extent of artifacts, sharpness, and diagnostic confidence. The qualitative scores for DWIS and DWIDL were compared with the Wilcoxon signed-rank test.

RESULTS

The overall image quality was evaluated to be significantly superior in DWIDL compared to DWIS for b = 0 s/mm2, b = 800 s/mm2, and ADC maps by all readers (P < .05). The extent of noise was evaluated to be significantly less in DWIDL compared to DWIS for b = 0 s/mm2, b = 800 s/mm2, and ADC maps by all readers (P < .001). No significant differences were found regarding artifacts, lesion detectability, sharpness of organs, and diagnostic confidence (P > .05). Acquisition time for DWIS was 2:06 minutes, and simulated acquisition time for DWIDL was 1:12 minutes.

CONCLUSION

DL image reconstruction improves image quality, and simulation results suggest that a reduction in acquisition time for diffusion-weighted MRI of the pelvis at 1.5 T is possible.

Ultra-high resolution photon-counting CT with tin prefiltration for bone-metal interface visualization

PURPOSE

To investigate the metal artifact suppression potential of combining tin prefiltration and virtual monoenergetic imaging (VMI) for osseous microarchitecture depiction in ultra-high-resolution (UHR) photon-counting CT (PCCT) of the lower extremity.

METHOD

Derived from tin-filtered UHR scans at 140 kVp, polychromatic datasets (T3D) and VMI reconstructions at 70, 110, 150, and 190 keV were compared in 117 patients with lower extremity metal implants (53 female; 62.1 ± 18.0 years). Three implant groups were investigated (total arthroplasty [n = 48], osteosynthetic material [n = 43], and external fixation [n = 26]). Image quality was assessed with regions of interest placed in the most pronounced artifacts and adjacent soft tissue, measuring the respective attenuation. Additionally, artifact extent, bone-metal interface interpretability and overall image quality were independently evaluated by three radiologists.

RESULTS

Artifact reduction was superior with increasing keV level of VMI. While T3D was superior to VMI70keV (p ≥ 0.117), artifacts were more severe in T3D than in VMI ≥ 110 keV (all p ≤ 0.036). Image noise was highest for VMI70keV (all p < 0.001) and lowest for VMI110keV with comparable results for VMI110keV - VMI190keV. Subjective image quality regarding artifacts was superior for VMI ≥ 110 keV (all p ≤ 0.042) and comparable for VMI110keV - VMI190keV. Bone-metal interface interpretability was superior for VMI110keV (all p ≤ 0.001), while T3D, VMI150keV and VMI190keV were comparable. Overall image quality was deemed best for VMI110keV and VMI150keV. Interreader reliability was good in all cases (ICC ≥ 0.833).

CONCLUSIONS

Tin-filtered UHR-PCCT scans of the lower extremity combined with VMI reconstructions allow for efficient artifact reduction in the vicinity of bone-metal interfaces.

Deep Learning MRI Reconstruction for Accelerating Turbo Spin Echo Hand and Wrist Imaging: A Comparison of Image Quality, Visualization of Anatomy, and Detection of Common Pathologies with Standard Imaging

RATIONALE AND OBJECTIVES

Magnetic resonance imaging (MRI) of the hand and wrist is a routine MRI examination and takes about 15-20 minutes, which can lead to problems resulting from the relatively long scan time, such as decreased image quality due to motion artifacts and lower patient throughput. The objective of this study was to evaluate a deep learning (DL) reconstruction for turbo spin echo (TSE) sequences of the hand and wrist regarding image quality, visualization of anatomy, and diagnostic performance concerning common pathologies.

MATERIALS AND METHODS

Twenty-one patients (mean age: 43 ± 19 [19-85] years, 10 men, 11 female) were prospectively enrolled in this study between October 2020 and June 2021. Each participant underwent two MRI protocols: first, standard fully sampled TSE sequences reconstructed with a standard GRAPPA reconstruction (TSES) and second, prospectively undersampled TSE sequences using a conventional parallel imaging undersampling pattern reconstructed with a DL reconstruction (TSEDL). Both protocols were acquired consecutively in one examination. Two experienced MSK-imaging radiologists qualitatively evaluated the images concerning image quality, noise, edge sharpness, artifacts, and diagnostic confidence, as well as the delineation of anatomical structures (triangular fibrocartilage complex, tendon of the extensor carpi ulnaris muscle, extrinsic and intrinsic ligaments, median nerve, cartilage) using a five-point Likert scale and assessed common pathologies. Wilcoxon signed-rank test and kappa statistics were performed to compare the sequences.

RESULTS

Overall image quality, artifacts, delineation of anatomical structures, and diagnostic confidence of TSEDL were rated to be comparable to TSES (p > 0.05). Additionally, TSEDL showed decreased image noise (4.90, median 5, IQR 5-5) compared to TSES (4.52, median 5, IQR 4-5, p < 0.05) and improved edge sharpness (TSEDL: 4.10, median 4, IQR 3.5-5; TSES: 3.57, median 4, IQR 3-4; p < 0.05). Inter- and intrareader agreement was substantial to almost perfect (κ = 0.632-1.000) for the detection of common pathologies. Time of acquisition could be reduced by more than 60% with the protocol using TSEDL.

CONCLUSION

Compared to TSES, TSEDL provided decreased noise and increased edge sharpness, equal image quality, delineation of anatomical structures, detection of pathologies, and diagnostic confidence. Therefore, TSEDL may be clinically relevant for hand and wrist imaging, as it reduces examination time by more than 60%, thus increasing patient comfort and patient throughput.

Combining virtual monoenergetic imaging and iterative metal artifact reduction in first-generation photon-counting computed tomography of patients with dental implants

OBJECTIVES

While established for energy-integrating detector computed tomography (CT), the effect of virtual monoenergetic imaging (VMI) and iterative metal artifact reduction (iMAR) in photon-counting detector (PCD) CT lacks thorough investigation. This study evaluates VMI, iMAR, and combinations thereof in PCD-CT of patients with dental implants.

MATERIAL AND METHODS

In 50 patients (25 women; mean age 62.0 ± 9.9 years), polychromatic 120 kVp imaging (T3D), VMI, T3DiMAR, and VMIiMAR were compared. VMIs were reconstructed at 40, 70, 110, 150, and 190 keV. Artifact reduction was assessed by attenuation and noise measurements in the most hyper- and hypodense artifacts, as well as in artifact-impaired soft tissue of the mouth floor. Three readers subjectively evaluated artifact extent and soft tissue interpretability. Furthermore, new artifacts through overcorrection were assessed.

RESULTS

iMAR reduced hyper-/hypodense artifacts (T3D 1305.0/-1418.4 versus T3DiMAR 103.2/-46.9 HU), soft tissue impairment (106.7 versus 39.7 HU), and image noise (16.9 versus 5.2 HU) compared to non-iMAR datasets (p ≤ 0.001). VMIiMAR ≥ 110 keV subjectively enhanced artifact reduction over T3DiMAR (p ≤ 0.023). Without iMAR, VMI displayed no measurable artifact reduction (p ≥ 0.186) and facilitated no significant denoising over T3D (p ≥ 0.366). However, VMI ≥ 110 keV reduced soft tissue impairment (p ≤ 0.009). VMIiMAR ≥ 110 keV resulted in less overcorrection than T3DiMAR (p ≤ 0.001). Inter-reader reliability was moderate/good for hyperdense (0.707), hypodense (0.802), and soft tissue artifacts (0.804).

CONCLUSION

While VMI alone holds minimal metal artifact reduction potential, iMAR post-processing enabled substantial reduction of hyperdense and hypodense artifacts. The combination of VMI ≥ 110 keV and iMAR resulted in the least extensive metal artifacts.

CLINICAL RELEVANCE

Combining iMAR with VMI represents a potent tool for maxillofacial PCD-CT with dental implants achieving substantial artifact reduction and high image quality.

KEY POINTS

• Post-processing of photon-counting CT scans with an iterative metal artifact reduction algorithm substantially reduces hyperdense and hypodense artifacts arising from dental implants. • Virtual monoenergetic images presented only minimal metal artifact reduction potential. • The combination of both provided a considerable benefit in subjective analysis compared to iterative metal artifact reduction alone.

Image Quality and Diagnostic Performance of Accelerated 2D Hip MRI with Deep Learning Reconstruction Based on a Deep Iterative Hierarchical Network

OBJECTIVES

Hip MRI using standard multiplanar sequences requires long scan times. Accelerating MRI is accompanied by reduced image quality. This study aimed to compare standard two-dimensional (2D) turbo spin echo (TSE) sequences with accelerated 2D TSE sequences with deep learning (DL) reconstruction (TSEDL) for routine clinical hip MRI at 1.5 and 3 T in terms of feasibility, image quality, and diagnostic performance.

MATERIAL AND METHODS

In this prospective, monocentric study, TSEDL was implemented clinically and evaluated in 14 prospectively enrolled patients undergoing a clinically indicated hip MRI at 1.5 and 3T between October 2020 and May 2021. Each patient underwent two examinations: For the first exam, we used standard sequences with generalized autocalibrating partial parallel acquisition reconstruction (TSES). For the second exam, we implemented prospectively undersampled TSE sequences with DL reconstruction (TSEDL). Two radiologists assessed the TSEDL and TSES regarding image quality, artifacts, noise, edge sharpness, diagnostic confidence, and delineation of anatomical structures using an ordinal five-point Likert scale (1 = non-diagnostic; 2 = poor; 3 = moderate; 4 = good; 5 = excellent). Both sequences were compared regarding the detection of common pathologies of the hip. Comparative analyses were conducted to assess the differences between TSEDL and TSES.

RESULTS

Compared with TSES, TSEDL was rated to be significantly superior in terms of image quality (p ≤ 0.020) with significantly reduced noise (p ≤ 0.001) and significantly improved edge sharpness (p = 0.003). No difference was found between TSES and TSEDL concerning the extent of artifacts, diagnostic confidence, or the delineation of anatomical structures (p > 0.05). Example acquisition time reductions for the TSE sequences of 52% at 3 Tesla and 70% at 1.5 Tesla were achieved.

CONCLUSION

TSEDL of the hip is clinically feasible, showing excellent image quality and equivalent diagnostic performance compared with TSES, reducing the acquisition time significantly.

Comparison of endoscopic versus CT assessment of stone-free status after percutaneous nephrolithotomy (PCNL)

This study is aimed to determine whether postoperative low dose computed tomography (LDCT) imaging is necessary after percutaneous nephrolithotomy (PCNL), or the surgeon's intraoperative assessment of residual fragments (RF) is sufficient and avoidance of postoperative imaging with reduction of radiation exposure can be achieved. Data of all 610 patients who underwent PCNL in prone position in our institution from February 2009 to September 2020 was collected. Parameters such as age, gender, BMI, ASA-Classification, stone related parameters and the surgeon's assessment of stone-free status were analyzed. The LDCT performed postoperatively was compared to the intraoperative assessment of the surgeon regarding RF. The mean age of patients was 52.82 years; the mean BMI was 28.18 kg/m2. In 418 cases, the surgeon made a clear statement about the presence of RF and postoperative LDCT was carried out. The discrepancy between the two methods (surgeon´s assessment vs. LDCT) was significant at p < 0.0001. The sensitivity, specificity, positive and negative predictive value of the surgeon when assessing RF were 24.05%, 99.45%, 98.28% and 50%. Stone free rate (SFR) after primary PCNL was 45.57%. The overall SFR at discharge was 96.23%. Although the surgeon´s assessment of RF was reliable, postoperative LDCT imaging should still be performed if endoscopic stone clearance is suspected due to the high false negative rate and the low negative predictive value. The optimal timing of postoperative imaging following PCNL remains unclear.

Electrocardiogram with Artificial Intelligence Assessment as a Predictor of Cardiac Events and Overall Survival in Patients Receiving Radiotherapy for Esophageal Cancer

PURPOSE/OBJECTIVE(S)

Neoadjuvant (chemo)radiotherapy (RT) has demonstrated an overall survival (OS) benefit in esophageal cancer and constitutes part of the standard of care trimodality therapy. Unfortunately, subsequent cardiac toxicity can reduce the benefit of treatment. Our group aimed to study whether data from electrocardiograms (ECGs) could predict clinical outcomes and cardiac events after RT for esophageal cancer, allowing for identification of and early intervention for patients at high risk for cardiac toxicity.

MATERIALS/METHODS

Included patients received at least 41.4 Gy of pre-operative or definitive photon or proton RT for esophageal cancer from 2015 through July 2022. All ECGs were assessed using a previously validated artificial intelligence assessment for atrial fibrillation (AF) and reduced ejection fraction (rEF) (Noseworthy et al. Lancet 2022). The model determined propensities for the development of multiple cardiac events, including AF and heart failure (HF). Medical records were reviewed for cardiac events and conditions prior to and after RT.

RESULTS

A cohort of 491 patients was assembled, with 301, 121, and 364 patients having an ECG prior to, during, and after RT, respectively. Of these, 84% had malignancy in the lower third of the esophagus and 48% underwent esophagectomy. At last follow-up relative to baseline assessment, patients had increased propensity for rEF (median 0.013, interquartile range (IQR): 0.001-0.038 vs. median 0.022, IQR: 0.011-0.074, p < 0.0001) and AF (median 0.16, IQR: 0.04-0.40 vs. median 0.048, IQR: 0.01-0.19, p < 0.0001). Increases in AF propensity were associated with reduced OS (hazard ratio (HR) = 1.10 per 0.1 increase, 95% confidence interval (CI): 1.03-1.17, p = 0.0071). Baseline rEF propensity was predictive of future HF events (HR = 1.14, 95% CI: 1.07-1.22, p < 0.001) for all patients or after excluding the 172 (35%) patients with baseline HF (HR = 1.45, 95% CI: 1.19-1.76, p < 0.001). Among patients who did not have HF prior to radiotherapy, the development of HF was associated with reduced OS (HR = 1.60, 95% CI: 1.10-2.32, p = 0.014). Currently available cardiac dosimetric parameters, including heart mean/max doses, did not significantly correlate with cardiac outcomes. Patients who underwent esophagectomy had improved OS (HR = 0.62, 95% CI: 0.47-0.82, p = 0.0008) and were not more likely to develop cardiac toxicity.

CONCLUSION

This analysis suggests that chemoradiotherapy for esophageal cancer can have significant impacts on a patient's propensity for cardiac events, which are associated with reduced OS. ECGs carry the potential to identify patients at greater risk for such events, and baseline ECGs with artificial intelligence assessment could select patients for increased surveillance or early intervention to further optimize the therapeutic ratio of RT.

Faster Elbow MRI with Deep Learning Reconstruction-Assessment of Image Quality, Diagnostic Confidence, and Anatomy Visualization Compared to Standard Imaging

OBJECTIVE

The objective of this study was to evaluate a deep learning (DL) reconstruction for turbo spin echo (TSE) sequences of the elbow regarding image quality and visualization of anatomy.

MATERIALS AND METHODS

Between October 2020 and June 2021, seventeen participants (eight patients, nine healthy subjects; mean age: 43 ± 16 (20-70) years, eight men) were prospectively included in this study. Each patient underwent two examinations: standard MRI, including TSE sequences reconstructed with a generalized autocalibrating partial parallel acquisition reconstruction (TSESTD), and prospectively undersampled TSE sequences reconstructed with a DL reconstruction (TSEDL). Two radiologists evaluated the images concerning image quality, noise, edge sharpness, artifacts, diagnostic confidence, and delineation of anatomical structures using a 5-point Likert scale, and rated the images concerning the detection of common pathologies.

RESULTS

Image quality was significantly improved in TSEDL (mean 4.35, IQR 4-5) compared to TSESTD (mean 3.76, IQR 3-4, p = 0.008). Moreover, TSEDL showed decreased noise (mean 4.29, IQR 3.5-5) compared to TSESTD (mean 3.35, IQR 3-4, p = 0.004). Ratings for delineation of anatomical structures, artifacts, edge sharpness, and diagnostic confidence did not differ significantly between TSEDL and TSESTD (p > 0.05). Inter-reader agreement was substantial to almost perfect (κ = 0.628-0.904). No difference was found concerning the detection of pathologies between the readers and between TSEDL and TSESTD. Using DL, the acquisition time could be reduced by more than 35% compared to TSESTD.

CONCLUSION

TSEDL provided improved image quality and decreased noise while receiving equal ratings for edge sharpness, artifacts, delineation of anatomical structures, diagnostic confidence, and detection of pathologies compared to TSESTD. Providing more than a 35% reduction of acquisition time, TSEDL may be clinically relevant for elbow imaging due to increased patient comfort and higher patient throughput.

Accelerated diffusion-weighted imaging of the prostate using deep learning image reconstruction: A retrospective comparison with standard diffusion-weighted imaging

PURPOSE

Routine multiparametric MRI of the prostate reduces overtreatment and increases sensitivity in the diagnosis of the most common solid cancer in men. However, the capacity of MRI systems is limited. Here we investigate the ability of deep learning image reconstruction to accelerate time consuming diffusion-weighted imaging (DWI) acquisition while maintaining diagnostic image quality.

METHOD

In this retrospective study, raw data of DWI sequences of consecutive patients undergoing MRI of the prostate at a tertiary care hospital in Germany were reconstructed using standard and deep learning reconstruction. To simulate a shortening of acquisition times by 39 %, one instead of two and six instead of ten averages were used in the reconstruction of b = 0 and 1000 s/mm2 images, respectively. Image quality was assessed by three radiologists and objective image quality metrics.

RESULTS

After the application of exclusion criteria, 35 out of 147 patients examined between September 2022 and January 2023 were included in this study. The radiologists perceived less image noise on deep learning reconstructed images at b = 0 s/mm2 images and ADC maps with good inter-reader agreement. Signal-to-noise ratios were similar overall with discretely reduced values in the transitional zone after deep learning reconstruction.

CONCLUSIONS

An acquisition time reduction of 39 % without loss in image quality is feasible in DWI of the prostate when using deep learning image reconstruction.

Acquisition time reduction of diffusion-weighted liver imaging using deep learning image reconstruction

PURPOSE

The purpose of this study was to investigate the impact of deep learning accelerated diffusion-weighted imaging (DWIDL) in 1.5-T liver MRI on image quality, sharpness, and diagnostic confidence.

MATERIALS AND METHODS

One-hundred patients who underwent liver MRI at 1.5-T including DWI with two different b-values (50 and 800 s/mm²) between February and April 2022 were retrospectively included. There were 54 men and 46 women, with a mean age of 59 ± 14 (SD) years (range: 21-88 years). The single average raw data were retrospectively processed using a deep learning (DL) image reconstruction algorithm leading to a simulated acquisition time of 1 min 28 s for DWIDL as compared to 2 min 31 s for standard DWI (DWIStd) via reduction of signal averages. All DWI datasets were reviewed by four radiologists using a Likert scale ranging from 1-4 using the following criteria: noise level, extent of artifacts, sharpness, overall image quality, and diagnostic confidence. Furthermore, quantitative assessment of noise and signal-to-noise ratio (SNR) was performed via regions of interest.

RESULTS

No significant differences were found regarding artifacts and overall image quality (P > 0.05). Noise measurements for the spleen, liver, and erector spinae muscles revealed significantly lower noise for DWIDL versus DWIStd (P < 0.001). SNR measurements in the above-mentioned tissues also showed significantly superior results for DWIDL versus DWIStd for b = 50 s/mm² and ADC maps (all P < 0.001). For b = 800 s/mm², significantly superior results were found for the spleen, right hemiliver, and erector spinae muscles.

CONCLUSIONS

DL image reconstruction of liver DWI at 1.5-T is feasible including significant reduction of acquisition time without compromised image quality.

[Multiparametric MRI of the prostate: requirements and principles regarding diagnostic reporting]

Multiparametric MRI (mpMRI) is one of the primary diagnostic tools for detecting clinically relevant prostate cancer. It should be routinely used in addition to urological investigations owing to its higher diagnostic yield than systematic biopsies. However, combining targeted and systematic biopsies achieves the highest diagnostic rate. The Prostate Imaging Reporting and Data System (PI-RADS Version 2.1) standardizes the acquisition and interpretation of mpMRI of the prostate. It consists of high-resolution T2- and diffusion-weighted images, the corresponding apparent diffusion coefficient (ADC) maps, and a dynamic contrast-enhanced sequence. Reports describe the increasing likelihood of clinically significant prostate cancer with PI-RADS categories 1-5. The MRI sequence determining the PI-RADS category of a lesion depends on its location within the prostate: in the transitional zone, the T2-weighted sequence and, in the peripheral zone, the diffusion-weighted sequence are the primary determinants. The diffusion-weighted and contrast-enhanced sequences provide secondary classification for the transitional and peripheral zones, respectively. This review summarizes and illustrates the diagnostic criteria defined in PI-RADS 2.1. In addition, evidence for mpMRI of the prostate, its indication and implementation are described.

Prospective intraindividual comparison of a standard 2D TSE MRI protocol for ankle imaging and a deep learning-based 2D TSE MRI protocol with a scan time reduction of 48

PURPOSE

Magnetic resonance imaging (MRI) scan time remains a limited and valuable resource. This study evaluates the diagnostic performance of a deep learning (DL)-based accelerated TSE study protocol compared to a standard TSE study protocol in ankle MRI.

MATERIAL AND METHODS

Between October 2020 and July 2021 forty-seven patients were enrolled in this study for an intraindividual comparison of a standard TSE study protocol and a DL TSE study protocol either on a 1.5 T or a 3 T scanner. Two radiologists evaluated the examinations regarding structural pathologies and image quality categories (5-point-Likert-scale; 1 = "non diagnostic", 5 = "excellent").

RESULTS

Both readers showed almost perfect/perfect agreement of DL TSE with standard TSE in all analyzed structural pathologies (0.81-1.00) with a median "good" or "excellent" rating (4-5/5) in all image quality categories in both 1.5 T and 3 T MRI. The reduction of total acquisition time of DL TSE compared to standard TSE was 49% in 1.5 T and 48% in 3 T MRI to a total acquisition time of 5 min 41 s and 5 min 46 s.

CONCLUSION

In ankle MRI the new DL-based accelerated TSE study protocol delivers high agreement with standard TSE and high image quality, while reducing the acquisition time by 48%.

Deep Learning Reconstruction for Accelerated Spine MRI: Prospective Analysis of Interchangeability

Background Deep learning (DL)-based MRI reconstructions can reduce examination times for turbo spin-echo (TSE) acquisitions. Studies that prospectively employ DL-based reconstructions of rapidly acquired, undersampled spine MRI are needed. Purpose To investigate the diagnostic interchangeability of an unrolled DL-reconstructed TSE (hereafter, TSE_DL) T1- and T2-weighted acquisition method with standard TSE and to test their impact on acquisition time, image quality, and diagnostic confidence. Materials and Methods This prospective single-center study included participants with various spinal abnormalities who gave written consent from November 2020 to July 2021. Each participant underwent two MRI examinations: standard fully sampled T1- and T2-weighted TSE acquisitions (reference standard) and prospectively undersampled TSE_DL acquisitions with threefold and fourfold acceleration. Image evaluation was performed by five readers. Interchangeability analysis and an image quality-based analysis were used to compare the TSE and TSE_DL images. Acquisition time and diagnostic confidence were also compared. Interchangeability was tested using the individual equivalence index regarding various degenerative and nondegenerative entities, which were analyzed on each vertebra and defined as discordant clinical judgments of less than 5%. Interreader and intrareader agreement and concordance (κ and Kendall τ and W statistics) were computed and Wilcoxon and McNemar tests were used. Results Overall, 50 participants were evaluated (mean age, 46 years ± 18 [SD]; 26 men). The TSE_DL method enabled up to a 70% reduction in total acquisition time (100 seconds for TSE_DL vs 328 seconds for TSE, P < .001). All individual equivalence indexes were less than 4%. TSE_DL acquisition was rated as having superior image noise by all readers (P < .001). No evidence of a difference was found between standard TSE and TSE_DL regarding frequency of major findings, overall image quality, or diagnostic confidence. Conclusion The deep learning (DL)-reconstructed turbo spin-echo (TSE) method was found to be interchangeable with standard TSE for detecting various abnormalities of the spine at MRI. DL-reconstructed TSE acquisition provided excellent image quality, with a 70% reduction in examination time. German Clinical Trials Register no. DRKS00023278 © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Hallinan in this issue.

Deep learning-based super-resolution gradient echo imaging of the pancreas: Improvement of image quality and reduction of acquisition time

PURPOSE

The purpose of this study was to evaluate the impact of a deep learning-based super-resolution technique on T1-weighted gradient-echo acquisitions (volumetric interpolated breath-hold examination; VIBE) on the assessment of pancreatic MRI at 1.5 T compared to standard VIBE imaging (VIBESTD).

MATERIALS AND METHODS

This retrospective single-center study was conducted between April 2021 and October 2021. Fifty patients with a total of 50 detectable pancreatic lesion entities were included in this study. There were 27 men and 23 women, with a mean age of 69 ± 13 (standard deviation [SD]) years (age range: 33-89 years). VIBESTD (precontrast, dynamic, postcontrast) was retrospectively processed with a deep learning-based super-resolution algorithm including a more aggressive partial Fourier setting leading to a simulated acquisition time reduction (VIBESR). Image analysis was performed by two radiologists regarding lesion detectability, noise levels, sharpness and contrast of pancreatic edges, as well as regarding diagnostic confidence using a 5-point Likert-scale with 5 being the best.

RESULTS

VIBESR was rated better than VIBESTD by both readers regarding lesion detectability (5 [IQR: 5, 5] vs. 5 [IQR: 4, 5], for reader 1; 5 [IQR: 5, 5] vs. 4 [IQR: 4, 5]) for reader 2; both P <0.001), noise levels (5 [IQR: 5, 5] vs. 5 [IQR: 4, 5] for reader 1; 5 [IQR: 5, 5] vs. 4 [IQR: 4, 5] for reader 2; both P <0.001), sharpness and contrast of pancreatic edges (5 [IQR: 5, 5] vs. 5 [IQR: 4, 5] for reader 1; 5 [IQR: 5, 5] vs. 4 [IQR: 4, 5] for reader 2; both P <0.001), as well as regarding diagnostic confidence (5 [IQR: 5, 5] vs. 5 [IQR: 4, 5] for reader 1; 5 [IQR: 5, 5] vs. 4 [IQR: 4, 5] for reader 2; both P <0.001). There were no significant differences between lesion sizes as measured by the two readers on VIBESR and VIBESTD images (P > 0.05). The mean acquisition time for VIBESTD (15 ± 1 [SD] s; range: 11-16 s) was longer than that for VIBESR (13 ± 1 [SD] s; range: 11-14 s) (P < 0.001).

CONCLUSION

Our results indicate that the newly developed deep learning-based super-resolution algorithm adapted to partial Fourier acquisitions has a positive influence not only on shortening the examination time but also on improvement of image quality in pancreatic MRI.

Thin-Slice Prostate MRI Enabled by Deep Learning Image Reconstruction

OBJECTIVES

Thin-slice prostate MRI might be beneficial for prostate cancer diagnostics. However, prolongation of acquisition time is a major drawback of thin-slice imaging. Therefore, the purpose of this study was to investigate the impact of a thin-slice deep learning accelerated T2-weighted (w) TSE imaging sequence (T2_DLR) of the prostate as compared to conventional T2w TSE imaging (T2_S).

MATERIALS AND METHODS

Thirty patients were included in this prospective study at one university center after obtaining written informed consent. T2_S (3 mm slice thickness) was acquired first in three orthogonal planes followed by thin-slice T2_DLR (2 mm slice thickness) in axial plane. Acquisition time of axial conventional T2_S was 4:12 min compared to 4:37 min for T2_DLR. Imaging datasets were evaluated by two radiologists using a Likert-scale ranging from 1-4, with 4 being the best regarding the following parameters: sharpness, lesion detectability, artifacts, overall image quality, and diagnostic confidence. Furthermore, preference of T2_S versus T2_DLR was evaluated.

RESULTS

The mean patient age was 68 ± 8 years. Sharpness of images and lesion detectability were rated better in T2_DLR with a median of 4 versus a median of 3 in T2_S (p < 0.001 for both readers). Image noise was evaluated to be significantly worse in T2_DLR as compared to T2_S (p < 0.001 and p = 0.021, respectively). Overall image quality was also evaluated to be superior in T2_DLR versus T2_S with a median of 4 versus 3 (p < 0.001 for both readers). Both readers chose T2_DLR in 29 cases as their preference.

CONCLUSIONS

Thin-slice T2_DLR of the prostate provides a significant improvement of image quality without significant prolongation of acquisition time.

Comprehensive Clinical Evaluation of a Deep Learning-Accelerated, Single-Breath-Hold Abdominal HASTE at 1.5 T and 3 T

To evaluate the clinical performance of a deep learning-accelerated single-breath-hold half-Fourier acquisition single-shot turbo spin echo (HASTE_DL)-sequence for T2-weighted fat-suppressed MRI of the abdomen at 1.5 T and 3 T in comparison to standard T2-weighted fat-suppressed multi-shot turbo spin echo-sequence. A total of 320 patients who underwent a clinically indicated liver MRI at 1.5 T and 3 T between August 2020 and February 2021 were enrolled in this single-center, retrospective study. HASTE_DL and standard sequences were assessed regarding overall and organ-based image quality, noise, contrast, sharpness, artifacts, diagnostic confidence, as well as lesion detectability using a Likert scale ranging from 1 to 4 (4 = best). The number of visible lesions of each organ was counted and the largest diameter of the major lesion was measured. HASTE_DL showed excellent image quality (median 4, interquartile range 3-4), although BLADE (median 4, interquartile range 4-4) was rated significantly higher for overall and organ-based image quality of the adrenal gland (P < .001), contrast (P < 0.001), sharpness (P < 0.001), artifacts (P < 0.001), as well as diagnostic confidence (P < .001). No significant differences were found concerning noise (P = 0.886), organ-based image quality of the liver, pancreas, spleen, and kidneys (P = 0.120-0.366), number and measured diameter of the detected lesions (ICC = 0.972-1.0). Reduction of the aquisition time (TA) was at least 89% for 1.5 T images and 86% for 3 T images. HASTE_DL provided excellent image quality, good diagnostic confidence and lesion detection compared to a standard T2-sequences, allowing an eminent reduction of the acquisition time.

Fetal 4D flow MRI of the great thoracic vessels at 3 Tesla using Doppler-ultrasound gating: a feasibility study

OBJECTIVES

To evaluate the feasibility of Doppler-ultrasound (DUS)-gated 4D flow MRI of the fetal great thoracic vessels at 3T in a clinical setting.

METHODS

Sixteen consecutive fetuses (range 30⁺⁴-38⁺⁵ weeks) with (n = 11) and without (n = 5) cardiovascular anomalies underwent 4D flow MRI of the great thoracic vessels at 3T. Direct fetal cardiac gating was obtained using a MR-compatible DUS device. 4D flow MRI-based visualisation and quantification of four target regions (ascending aorta (AAo), descending aorta (DAo), main pulmonary artery (MPA), and ductus arteriosus (DA)) were performed using dedicated software.

RESULTS

Fetal 4D flow MRI of the great thoracic vessels was successful in 12/16 fetuses (75%) by adopting clinical 4D flow MR protocols in combination with direct fetal cardiac DUS-gating. Four datasets were excluded due to artefacts by fetal movement or maternal breathing. 4D flow MRI-derived time-velocity curves revealed typical arterial blood flow patterns in the aorta. 4D flow quantification was achieved for the pre-defined target regions. Average velocity and flow volume were 21.1 ± 5.2 cm/s and 6.0 ± 3.1 mL/s in the AAo, 24.3 ± 6.7 cm/s and 8.4 ± 3.7 mL/s in the DAo, 21.9 ± 6.4 cm/s and 7.8 ± 4.2 mL/s in the MPA, and 23.4 ± 4.7 cm/s and 5.9 ± 3.6 mL/s in the DA, respectively.

CONCLUSIONS

Combination of DUS-gating of the fetal heart and 4D flow MRI allows comprehensive visualisation and quantification of haemodynamics in the fetal great thoracic vessels. DUS-gated fetal 4D flow MRI may provide a new diagnostic approach for prenatal assessment of blood flow haemodynamics.

KEY POINTS

• Fetal cardiac Doppler-ultrasound (DUS) gating and 4D flow MRI can be successfully combined. • DUS-gated fetal 4D flow MRI allowed visualisation and evaluation of streamline directionality, illustration of blood flow variations, and pulsatile arterial waveforms in the target vessels. • 4D flow MRI-based visualisation and quantification of the fetal great thoracic vessels were successful and flow metrics agreed with echocardiographic reference values.

[Whole-body MRI in cancer predisposition syndromes]

BACKGROUND

In recent decades, whole-body magnetic resonance imaging (WB-MRI) has become established as the modality of choice for the diagnosis, staging, and follow-up of oncological diseases as well as for the screening of cancer predisposition syndromes, such as Li-Fraumeni syndrome.

METHODS

As a comprehensive imaging modality without ionizing radiation, WB-MRI can be used repetitively and because of its excellent soft tissue contrast and high resolution provides early and precise detection of pathologies. This article discusses the technical requirements, some examination strategies and the clinical significance of typical findings of WB-MRI in patients with cancer predisposition syndromes.

Accelerated Three-dimensional T2-Weighted Turbo-Spin-Echo Sequences with Inner-Volume Excitation and Iterative Denoising in the Setting of Pelvis MRI at 1.5T: Impact on Image Quality and Lesion Detection

RATIONALE AND OBJECTIVES

To investigate image quality and rate of lesion detection in a novel three-dimensional T2-weighted turbo-spin-echo sequence with inner-volume excitation (zoomed imaging) and iterative denoising processing in pelvic MRI at 1.5T. Two-dimensional T2-weighted turbo-spin-echo sequences were used as the clinical reference standard (2D-T2-TSE).

MATERIALS AND METHODS

This is a prospective study of patients with various pelvic pathologies. Each patient underwent standard 2D-T2-TSE in three planes with two-fold acceleration as well as a single three-dimensional T2-TSE in the sagittal plane with four-fold acceleration known as Sampling-Perfection-with-Application-optimized-Contrast-using-different-flip-angle-Evolutions (3D-T2-SPACE). The 3D-T2-SPACE images were reconstructed in three orthogonal planes at a slice thickness of 2 mm (vs. 2D-T2-TSE at 4 mm). Two radiologists conducted a qualitative image analysis on standard 2D-T2-TSE and multiplanar reconstructed 3D-T2-SPACE images. These parameters were compared and inter-reader agreement was computed. Furthermore, each reader documented the observed lesions of various pelvic organs. The rate of lesion detection was compared between readers and sequences. Inter-reader and inter-sequence agreement were computed.

RESULTS

Forty patients (25 females) were included. Mean patient age was 58 ± 13 years. 3D-T2-SPACE enabled an approximate 22% reduction of acquisition time and 50% of reconstructed slice thickness. 3D-T2-SPACE showed fewer artifacts than 2D-T2-TSE (p < 0.001). However, 2D-T2-TSE was rated to have significantly higher signal intensity than 3D-T2-SPACE (p < 0.001). There were no significant differences between the two sequences regarding all other parameters. Inter-reader agreement regarding image quality parameters was substantial (Kappa = 0.772). For all analyzed pelvic anatomic structures, inter-reader and inter-sequence agreement for lesion detection was excellent (Kappa > 0.80).

CONCLUSION

3D-T2-SPACE with the inner-volume excitation and iterative denoising is clinically feasible at 1.5 T, enabling faster imaging, thinner slices, and significant reduction of artifacts. Despite that signal intensity was inferior in the SPACE images, overall image quality, diagnostic confidence and lesion detection were not compromised. This prospective study sets the stage for further clinical implementation and future investigations tailored to specific indications in pelvis MRI.

Mortality and major adverse cardiac events in women with breast cancer receiving radiotherapy: a 10-year cohort study of patients and population controls

Background

Treatment for breast cancer (BC) frequently involves radiotherapy. Guidelines recommend screening for cardiac adverse events starting 10 years after radiotherapy. The rationale for recommending this interval is unclear and informed the objective of this study.

Objectives

Study cardiovascular event rates in the first decade following curative radiotherapy for breast cancer, the time frame before guidelines recommend screening.

Methods

We performed a monocentric, retrospective study enrolling all women with unilateral BC in 2007–2008, who received radiotherapy as part of their curative treatment. We compared event rates during 10 years follow-up with an age and risk factor-matched control population (FLEMENGHO population).

Results

We included 1095 BC patients (median age 55y, IQR: 47–66y). Two hundred and eighteen (19.9%) women died. Cancer and cardiovascular mortality accounted for 107 (49.1%) and 22 (10.1%) deaths, respectively. The incidence of coronary artery disease was similar compared to age and risk-matched women [risk ratio 0.75 (95% CI 0.48–1.18)], yet heart failure (HF) [risk ratio 1.97 (95% CI 1.19–3.25)] and atrial fibrillation or flutter (AF) (risk ratio 1.82 (95% CI 1.07–3.08) occurred more often. Age [HR 1.040 (95% CI 1.012–1.069)], tumor grade [HR 1.646 (95% CI 1.103–2.458)], and neo-adjuvant treatment setting [HR 3.079 (95% CI 1.432–6.620)] were risk factors for mortality; hormonal therapy [HR 0.007 (95% CI 0.001–0.042)] proved protective. Risk factors for MACE were mean heart dose [HR 1.079 (95% CI 1.012–1.151], hormonal therapy, history of cardiovascular disease [HR 2.771 (95% CI 1.253–6.126)], and Mayo Clinic Cardiotoxicity Risk Score [HR 2.547 (95% CI 1.538–4.217)]. While mean heart dose [HR 1.141 (95% CI 1.017–1.282)] and cardiovascular history [HR 3.374 (95% CI 1.259–9.043] clearly associated with new onset HF, only a trend towards higher AF burden with increasing mean heart dose could be observed.

Conclusions

Ten-year mortality following curative treatment for unilateral BC was mainly cancer-related. HF and AF constituted significantly increased risks in the first decade following irradiation. Mean heart dose, pre-existing cardiovascular diseases, and Mayo Clinic Cardiotoxicity Risk Score were risk factors for early cardiac mortality and adverse events and should guide early dedicated cardio-oncological follow-up.

Funding Acknowledgement

Type of funding sources: None.

Mitral annular plane systolic excursion and global longitudinal strain for the prediction of cardiotoxicity or heart failure in lymphoma patients treated with anthracycline-based chemotherapy

Background

Assessing cardiac performance of patients receiving chemotherapy is a cornerstone for adequate cardiovascular care. Mitral annular plane systolic excursion (MAPSE) has been considered as a surrogate for Ejection Fraction (EF). However, little is known about its role in predicting Cardiotoxicity or Heart Failure in Lymphoma patients, as its relationship with Global Longitudinal Strain (GLS) and EF.

Purpose

Our aims were: i) to evaluate if MAPSE and GLS can predict the development of CT and/or HF in lymphoma patients treated with anthracyclines and ii) to evaluate its correlation with GLS and EF.

Methods

For this prospective observational study, 325 Hodgkin (HL) & non-Hodgkin (NHL) lymphoma patients (n=325) treated with anthracyclines were recruited from 2013 to 2021 and followed for 1 year. MAPSE by M-mode and GLS by Speckle-Tracking (ST) were measured at baseline (T0), during treatment (T1), and up to 1 year after chemotherapy completion (T2). CT was defined as a decrease in EF by &gt;10% to a value &lt;50% and HF by a cardiologist as the first occurrence after the initiation of anthracyclines. Logistic regression analyses with Receiving operator characteristics (ROC) and Area under the curve (AUC) were performed. Pearson's correlation coefficient was also calculated. A p-value &lt;0.05 was considered statistically significant.

Results

Two hundred sixty-four patients (81.2%) had NHL and 61 (18.8%) HL. Of these, fifteen (4.6%) and 21 individuals (6.4%) developed CT at T1 and T2, respectively. Nine subjects (2.8%) developed HF at T1 and 14 (4.3%) at T2. MAPSE at T0 had the highest AUC to predict both HF at T1 (AUC=0.865, cut-off 14.9, sensitivity 100%, specificity 63%, p=0.008) and at T2 (AUC=0.757, cut-off 10.9, sensitivity 67%, specificity 93%, p=0.045). This same variable at T1 predicted HF at T2 with an AUC of 0.752 (cut-off 11.4, sensitivity 67%, specificity 94%, p=0.004). For CT prediction at T2, MAPSE at T1 had an AUC of 0.738 (cut-off 12.5, sensitivity 56%, specificity 85%, p&lt;0.0001). GLS at T0 predicted CT at T1 (AUC=0.657, cut-off −19, sensitivity 67%, specificity 63%, p=0.012) and when obtained at T1, it predicted CT at T2 (AUC=0.776, cut-off −17, sensitivity 74%, specificity 75%, p-value &lt;0.0001) (Table 1). Pearson's correlation between MAPSE and GLS at T0 (coefficient −0.25, p=0.023) at T1 (coefficient −0.38, p&lt;0.0001) at T2 (coefficient −0.037, p&lt;0.0001) and MAPSE with EF at T0 (coefficient 0.33, p=0.0002) at T1 (coefficient 0.28, p&lt;0.0001) and T2 (coefficient 0.29, p&lt;0.001).

Conclusions

To our best knowledge, this is the first time that MAPSE and GLS were compared to predict CT and HF in lymphoma patients receiving anthracycline-based chemotherapy; we have demonstrated that MAPSE measured at T0 was a very good predictor of HF at T1. Either MAPSE or GLS assessment at T0 and T1 were able to predict CT or HF. Future studies could explore the combination of these two variables to predict either CT or HF.

Funding Acknowledgement

Type of funding sources: Private hospital(s). Main funding source(s): Department of Cardiovascular Medicine. Mayo Clinic, Rochester-MN

Basic or comprehensive strain analyses, which variable is better to predict hard endpoints as clinical heart failure in lymphoma patients receiving anthracyclines

Background

Speckle tracking echocardiography (STE) has shown to be a good tool to foresee early myocardial dysfunction in lymphoma patients who receive anthracycline based chemotherapy. Conventional STE such as global longitudinal strain (GLS) is a good predictor of cardiotoxicity in these patients, however, a more in-depth characterization of conventional and comprehensive STE parameters to predict a hard end-point as chemotherapeutic related heart failure (HF) has not been evaluated.

Purpose

The aim of this prospective study was to evaluate predictability of cancer therapeutic-related clinical HF by conventional and comprehensive STE.

Methods

We enrolled 269 Hodgkin & non-Hodgkin lymphoma patients who underwent chemotherapy at Mayo Clinic from 2013 through 2021. All patients had an echocardiogram performed at baseline (T0), during chemotherapy (T1) and after (T2). HF was diagnosed by a cardiologist and defined as the first occurrence after the initiation of chemotherapy. Conventional (GLS) and comprehensive strain analyses that included: global circumferential strain (GCS), global radial strain (GRS), global longitudinal early diastolic strain rate (GLSRe), global longitudinal systolic strain rate (GLSRs), global circumferential early diastolic strain rate (GCSRe), global circumferential systolic strain rate (GCSRs), global radial early diastolic strain rate (GRSRe), and global radial systolic strain rate (GRSRs), were performed offline. Logistic regression analyses were used to evaluate the association of 2D and 3D STE measurements with the development of clinical HF.

Results

Overall, 215 (79.9%) patients had non-Hodgkin lymphoma while 54 (20.1%) had Hodgkin lymphoma. Mean age was 58.4±16.1 years and 64.7% of the patients were males. The most prevalent comorbidities were hypertension (101/37.5%), dyslipidemia (87/32.3%) and diabetes (28/10.4%). HF occurred in 21 (7.8%) patients, including 9 (3.3%) during chemotherapy and 12 (4.5%) after chemotherapy. The best predictors of HF were: i) GLSRe and GCSRs performed at baseline (T0) to predict HF at T1 with an AUC of 0.85 each and p values of 0.0006 and 0.0005 respectively (Table 1); ii) GCSRs and GCS at baseline (T0) to predict HF at T1 or T2 with AUCs of 0.82 (p, &lt;0.0001) and 0.81 (p, 0.0004), respectively. Basic strain (GLS) was able to predict HF when measured at T0 but not when measured at T1. All the AUCs for GLS were below 0.75 (Figure 1).

Conclusions

To our knowledge this is the first study to evaluate the use of conventional and comprehensive STE to predict a hard end-point as heart failure in patients with lymphoma who received anthracyclines. Comprehensive STE measurements as GLSRs, GLSRe, GCS, GCSRs and GCSRe are better than GLS to predict HF in patients with lymphoma who received anthracycline based chemotherapy. These findings can be crucial for the management of these patients by guiding when to start cardioprotection and/or avoid interruptions of cancer treatment.

Funding Acknowledgement

Type of funding sources: Private hospital(s). Main funding source(s): Department of cardiovascular diseases, Mayo Clinic, Rochester, MN

Reduction in Acquisition Time and Improvement in Image Quality in T2-Weighted MR Imaging of Musculoskeletal Tumors of the Extremities Using a Novel Deep Learning-Based Reconstruction Technique in a Turbo Spin Echo (TSE) Sequence

Background: The aim of this study was to assess the technical feasibility and the impact on image quality and acquisition time of a deep learning-accelerated fat-saturated T2-weighted turbo spin echo sequence in musculoskeletal imaging of the extremities. Methods: Twenty-three patients who underwent MRI of the extremities were prospectively included. Standard T2w turbo inversion recovery magnitude (TIRMStd) imaging was compared to a deep learning-accelerated T2w TSE (TSEDL) sequence. Image analysis of 23 patients with a mean age of 60 years (range 30−86) was performed regarding image quality, noise, sharpness, contrast, artifacts, lesion detectability and diagnostic confidence. Pathological findings were documented measuring the maximum diameter. Results: The analysis showed a significant improvement for the T2 TSEDL with regard to image quality, noise, contrast, sharpness, lesion detectability, and diagnostic confidence, as compared to T2 TIRMStd (each p < 0.001). There were no differences in the number of detected lesions. The time of acquisition (TA) could be reduced by 52−59%. Interrater agreement was almost perfect (κ = 0.886). Conclusion: Accelerated T2 TSEDL was technically feasible and superior to conventionally applied T2 TIRMStd. Concurrently, TA could be reduced by 52−59%. Therefore, deep learning-accelerated MR imaging is a promising and applicable method in musculoskeletal imaging.

Combined Deep Learning-based Super-Resolution and Partial Fourier Reconstruction for Gradient Echo Sequences in Abdominal MRI at 3 Tesla: Shortening Breath-Hold Time and Improving Image Sharpness and Lesion Conspicuity

RATIONALE AND OBJECTIVES

To investigate the impact of a prototypical deep learning-based super-resolution reconstruction algorithm tailored to partial Fourier acquisitions on acquisition time and image quality for abdominal T1-weighted volume-interpolated breath-hold examination (VIBE_SR) at 3 Tesla. The standard T1-weighted images were used as the reference standard (VIBE_SD).

MATERIALS AND METHODS

Patients with diverse abdominal pathologies, who underwent a clinically indicated contrast-enhanced abdominal VIBE magnetic resonance imaging at 3T between March and June 2021 were retrospectively included. Following the acquisition of the standard VIBE_SD sequences, additional images for the non-contrast, dynamic contrast-enhanced and post-contrast T1-weighted VIBE acquisition were retrospectively reconstructed using the same raw data and employing a prototypical deep learning-based super-resolution reconstruction algorithm. The algorithm was designed to enhance edge sharpness by avoiding conventional k-space filtering and to perform a partial Fourier reconstruction in the slice phase-encoding direction for a predefined asymmetric sampling ratio. In the retrospective reconstruction, the asymmetric sampling was realized by omitting acquired samples at the end of the acquisition and therefore corresponding to a shorter acquisition. Four radiologists independently analyzed the image datasets (VIBE_SR and VIBE_SD) in a blinded manner. Outcome measures were: sharpness of abdominal organs, sharpness of vessels, image contrast, noise, hepatic lesion conspicuity and size, overall image quality and diagnostic confidence. These parameters were statistically compared and interrater reliability was computed using Fleiss' Kappa and intraclass correlation coefficient (ICC). Finally, the rate of detection of hepatic lesions was documented and was statistically compared using the paired Wilcoxon test.

RESULTS

A total of 32 patients aged 59 ± 16 years (23 men (72%), 9 women (28%)) were included. For VIBE_SR, breath-hold time was significantly reduced by approximately 13.6% (VIBE_SR 11.9 ± 1.2 seconds vs. VIBE_SD: 13.9 ± 1.4 seconds, p < 0.001). All readers rated sharpness of abdominal organs, sharpness of vessels to be superior in images with VIBE_SR (p values ranged between p = 0.005 and p < 0.001). Despite reduction of acquisition time, image contrast, noise, overall image quality and diagnostic confidence were not compromised, as there was no evidence of a difference between VIBE_SR and VIBE_SD (p > 0.05). The inter-reader agreement was substantial with a Fleiss' Kappa of >0.7 in all contrast phases. A total of 13 hepatic lesions were analyzed. The four readers observed a superior lesion conspicuity in VIBE_SR than in VIBE_SD (p values ranged between p = 0.046 and p < 0.001). In terms of lesion size, there was no significant difference between VIBE_SD and VIBE_SR for all readers. Finally, there was an excellent inter-reader agreement regarding lesion size (ICC > 0.9). For all readers, no statistically significant difference was observed regarding detection of hepatic lesions between VIBE_SD and VIBE_SR.

CONCLUSION

The deep learning-based super-resolution reconstruction with partial Fourier in the slice phase-encoding direction enabled a reduction of breath-hold time and improved image sharpness and lesion conspicuity in T1-weighted gradient echo sequences in abdominal magnetic resonance imaging at 3 Tesla. Faster acquisition time without compromising image quality or diagnostic confidence was possible by using this deep learning-based reconstruction technique.

O-187 An analysis of the outcome of 11,712 men applying to be sperm donors at Cryos International in Denmark and the USA

Study question

Is the outcome of donor recruitment influenced by the country in which recruitment took place or the initial ID-release choice of applicants?

Summary answer

More applicants are accepted as donors in Denmark than the USA and those who choose ID release are more frequently accepted than those who don’t.

What is known already

The successful recruitment of sperm donors is essential to provide a range of Assisted Reproductive Technologies (ART) which rely upon donor sperm. However, while much has been written about the medical screening and assessment of sperm donors from a safety perspective, relatively little has been written about the process of recruiting donors and how it works in practice. There are differences in attitudes between donors who choose to allow their identity to be released to any donor conceived people (ID-release) compared to those who don’t (non ID-release). Therefore, we reasoned this may also influence the likelihood of them being recruited.

Study design, size, duration

A total of 11,712 men applied to be sperm donors at Cryos International in Denmark and the USA during 2018 and 2019.

Participants/materials, setting, methods

Anonymised records of all donor applicants were examined to assess the number passing through (or lost) at each stage of the recruitment process. Statistical analysis was carried out by Chi Squared test, using Graphpad Prism (San Diego, USA) to examine differences between location (Denmark or USA) and/or donor type (ID-release vs non-ID release).

Main results and the role of chance

Few applicants (3.79%) were accepted as donors and had samples released for use. This was higher in Denmark (6.53%) than the USA (1.03%) (χ2 = 243.2; 1df; z = 15.60; p &lt; 0.0001) and was higher in donors who opted at the outset to be ID-release (4.70%) compared to those who didn’t (3.15%) (χ2 = 18.51; 1df; z = 4.303; p &lt; 0.0001). Most potential donors were lost during recruitment because they: (i) withdrew, failed to respond, did not attend an appointment, or return a questionnaire (54.91%); (ii) reported a disqualifying health issue or failed a screening test (17.41%); (iii) did not meet the eligibility criteria at the outset (11.71%); or (iv) had semen quality which was not adequate (11.20%). In each case, there were statistically significant differences between countries and the donor’s initial ID choice. During recruitment, some donors decided to change ID-type. There were no country differences in the frequency in which this occurred (χ2 = 0.2852; 1df; z = 0.5340; p = 0.5933), but it was more common for donors to change from non-ID release to ID release (27.19%) than the other way around (11.45%) (χ2 = 17.75; 1df; z = 4.213; p &lt; 0.0001) although movements in both directions did occur in both countries.

Limitations, reasons for caution

No information was available about the demographic characteristics of the applicants which may also have influenced their chances of being accepted as a donor (e.g., ethnicity, age etc). Donor recruitment procedures may differ in other locations according to local laws or guidelines.

Wider implications of the findings

A better understanding of when and why potential donors are lost in the recruitment process may help develop leaner and efficient pathways for interested donors and sperm banks. This could ultimately increase the number of donors recruited through enhanced information, support and reassurance during the recruitment process.

Trial registration number

not applicable

[Multiparametric MRI of the prostate]

Multiparametric magnetic resonance imaging (mpMRI) is an integral component of prostate cancer diagnostics. According to the S3 guidelines on prostate cancer, mpMRI should be used for the primary diagnostics of prostate cancer as well as in active surveillance (AS). Basically, mpMRI consists of high-resolution T2-weighted (T2w) sequences, diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) sequences, which in turn are the basis for structured reporting according to the prostate imaging reporting and data system (PI-RADS) classification.

Analysis of a Deep Learning-Based Superresolution Algorithm Tailored to Partial Fourier Gradient Echo Sequences of the Abdomen at 1.5 T: Reduction of Breath-Hold Time and Improvement of Image Quality

OBJECTIVES

The aim of this study was to investigate the feasibility and impact of a novel deep learning superresolution algorithm tailored to partial Fourier allowing retrospectively theoretical acquisition time reduction in 1.5 T T1-weighted gradient echo imaging of the abdomen.

MATERIALS AND METHODS

Fifty consecutive patients who underwent a 1.5 T contrast-enhanced magnetic resonance imaging examination of the abdomen between April and May 2021 were included in this retrospective study. After acquisition of a conventional T1-weighted volumetric interpolated breath-hold examination using Dixon for water-fat separation (VIBEStd), the acquired data were reprocessed including a superresolution algorithm that was optimized for partial Fourier acquisitions (VIBESR). To accelerate theoretically the acquisition process, a more aggressive partial Fourier setting was applied in VIBESR reconstructions practically corresponding to a shorter acquisition for the data included in the retrospective reconstruction. Precontrast, dynamic contrast-enhanced, and postcontrast data sets were processed. Image analysis was performed by 2 radiologists independently in a blinded random order without access to clinical data regarding the following criteria using a Likert scale ranging from 1 to 4 with 4 being the best: noise levels, sharpness and contrast of vessels, sharpness and contrast of organs and lymph nodes, overall image quality, diagnostic confidence, and lesion conspicuity.Wilcoxon signed rank test for paired data was applied to test for significance.

RESULTS

Mean patient age was 61 ± 14 years. Mean acquisition time for the conventional VIBEStd sequence was 15 ± 1 seconds versus theoretical 13 ± 1 seconds of acquired data used for the VIBESR reconstruction. Noise levels were evaluated to be better in VIBESR with a median of 4 (4-4) versus a median of 3 (3-3) in VIBEStd by both readers (P < 0.001). Sharpness and contrast of vessels as well as organs and lymph nodes were also evaluated to be superior in VIBESR compared with VIBEStd with a median of 4 (4-4) versus a median of 3 (3-3) (P < 0.001). Diagnostic confidence was also rated superior in VIBESR with a median of 4 (4-4) versus a median of 3.5 (3-4) in VIBEStd by reader 1 and with a median of 4 (4-4) for VIBESR and a median of 4 (4-4) for VIBEStd by reader 2 (both P < 0.001).

CONCLUSIONS

Image enhancement using deep learning-based superresolution tailored to partial Fourier acquisitions of T1-weighted gradient echo imaging of the abdomen provides improved image quality and diagnostic confidence in combination with more aggressive partial Fourier settings leading to shorter scan time.

Deep Learning Applications in Magnetic Resonance Imaging: Has the Future Become Present?

Deep learning technologies and applications demonstrate one of the most important upcoming developments in radiology. The impact and influence of these technologies on image acquisition and reporting might change daily clinical practice. The aim of this review was to present current deep learning technologies, with a focus on magnetic resonance image reconstruction. The first part of this manuscript concentrates on the basic technical principles that are necessary for deep learning image reconstruction. The second part highlights the translation of these techniques into clinical practice. The third part outlines the different aspects of image reconstruction techniques, and presents a review of the current literature regarding image reconstruction and image post-processing in MRI. The promising results of the most recent studies indicate that deep learning will be a major player in radiology in the upcoming years. Apart from decision and diagnosis support, the major advantages of deep learning magnetic resonance imaging reconstruction techniques are related to acquisition time reduction and the improvement of image quality. The implementation of these techniques may be the solution for the alleviation of limited scanner availability via workflow acceleration. It can be assumed that this disruptive technology will change daily routines and workflows permanently.

1.5 vs 3 Tesla Magnetic Resonance Imaging: A Review of Favorite Clinical Applications for Both Field Strengths-Part 2

ABSTRACT

The second part of this review deals with experiences in neuroradiological and pediatric examinations using modern magnetic resonance imaging systems with 1.5 T and 3 T, with special attention paid to experiences in pediatric cardiac imaging. In addition, whole-body examinations, which are widely used for diagnostic purposes in systemic diseases, are compared with respect to the image quality obtained in different body parts at both field strengths. A systematic overview of the technical differences at 1.5 T and 3 T has been presented in part 1 of this review, as well as several organ-based magnetic resonance imaging applications including musculoskeletal imaging, abdominal imaging, and prostate diagnostics.

1.5 vs 3 Tesla Magnetic Resonance Imaging: A Review of Favorite Clinical Applications for Both Field Strengths-Part 1

ABSTRACT

Whole-body magnetic resonance imaging (MRI) systems with a field strength of 3 T have been offered by all leading manufacturers for approximately 2 decades and are increasingly used in clinical diagnostics despite higher costs. Technologically, MRI systems operating at 3 T have reached a high standard in recent years, as well as the 1.5-T devices that have been in use for a longer time. For modern MRI systems with 3 T, more complexity is required, especially for the magnet and the radiofrequency (RF) system (with multichannel transmission). Many clinical applications benefit greatly from the higher field strength due to the higher signal yield (eg, imaging of the brain or extremities), but there are also applications where the disadvantages of 3 T might outweigh the advantages (eg, lung imaging or examinations in the presence of implants). This review describes some technical features of modern 1.5-T and 3-T whole-body MRI systems, and reports on the experience of using both types of devices in different clinical settings, with all sections written by specialist radiologists in the respective fields.This first part of the review includes an overview of the general physicotechnical aspects of both field strengths and elaborates the special conditions of diffusion imaging. Many relevant aspects in the application areas of musculoskeletal imaging, abdominal imaging, and prostate diagnostics are discussed.

Comprehensive strain analysis in oncological patients undergoing thoracic radiotherapy: 1-year follow-up of a prospective study comparing proton vs. photon beam therapy

Background

Proton beam therapy (PBT) is a promising radiotherapeutic method by which the proton Bragg peak may be exploited to reduce the dose to non-target normal tissues, when compared with the conventional photon treatment (PhT).

Purpose

To evaluate the mechanical function of the left ventricle by endocardial longitudinal (GLS-basic strain), circumferential (GCS) and radial strain (GRS) and systolic (SRs) and early diastolic (SRe) strain rate following thoracic radiotherapy.

Methods

Between March 2016 and March 2017, 58 patients with breast or thoracic cancer scheduled to receive radiotherapy were enrolled prospectively and, underwent 2D-STE echocardiography with basic (GLS) and comprehensive (GCS, GRS,GLSRs, GCSRs, GRSRs, GLSRe, GCSRe, GRSRe parameters) analysis at pre-treatment, mid-treatment, end of treatment, 3 month and 1 year follow-up. LVEF was calculated by the biplane Simpson technique. Shapiro-Wilk's test was performed to evaluate the normal distribution of the data. Comparison between groups was performed with Student's t-test or Wilcoxon test for quantitative variables and with Chi-Square test or Fisher's exact test for qualitative variables. Tukey-Kramer method was used to compare means during follow up. A p-value &lt;0.05 was assumed as the level of statistical significance.

Results

Mean age was 53.3±10.9 years and 91.3% were women. PBT was used to treat 38 patients; PhT in 20. The median of the mean heart dose was lower with PBT than PhT (79±92 vs 829±1121 cGy, respectively [P&lt;.001]). No significant changes in LVEF or GLS for PBT or PhT were seen. Comprehensive strain analysis showed changes in endocardial longitudinal, radial, and circumferential early diastolic strain rate (SRe) in patients undergoing photon beam (PhT) up to one year of follow up (Table 1). No changes were detected in the PBT group. All other variables were non-significant (Not shown).

Conclusion

This is the first longitudinal study, with a one-year follow-up, that shows the relaxation properties of LV are compromised during PhT but not PBT. These findings should be followed in time to evaluate their influence on overall heart function.

Funding Acknowledgement

Type of funding sources: None. Table 1

Development and Evaluation of Deep Learning-Accelerated Single-Breath-Hold Abdominal HASTE at 3 T Using Variable Refocusing Flip Angles

OBJECTIVE

Deep learning (DL) reconstruction enables substantial acceleration of image acquisition while maintaining diagnostic image quality. The aims of this study were to overcome the drawback of specific absorption rate (SAR)-related limitations at 3 T and to develop a DL-accelerated single-breath-hold half-Fourier acquisition single-shot turbo spin echo (HASTE) sequence for 2-dimesional T2-weighted fat-suppressed magnetic resonance imaging of the abdomen at 3 T using a variable flip angle (FA) evolution for the refocusing radiofrequency pulses, as well as to evaluate its feasibility and image quality in comparison to state-of-the-art T2-weighted fat-suppressed imaging technique (BLADE).

MATERIALS AND METHODS

First, a suitable FA evolution with low cardiac motion-related signal loss (CRSL) and low SAR was determined through a prospective volunteer study with 11 participants. Image quality and diagnostic confidence with 5 different FA evolutions of a HASTEDL were assessed to identify the most suitable FA evolution. Second, the identified FA evolution was implemented clinically and evaluated in 51 patients undergoing a clinically indicated liver magnetic resonance imaging at 3 T. Two radiologists assessed the HASTEDL and standard sequences regarding overall image quality, noise, contrast, sharpness, artifacts, CRSL, and diagnostic confidence using a Likert scale ranging from 1 to 4, with 4 being the best. Comparative analyses were conducted to assess the differences between HASTEDL (acquisition time, 21 seconds; single breath-hold) and the routinely used T2-weighted BLADE sequence (acquisition time, 4 minutes; respiratory triggering).

RESULTS

From the volunteer study, the FA evolution characterized by the control points 130-90-110-130 degrees (HASTEDL) was identified as optimal among the 5 evolutions evaluated and was implemented in our clinical protocol. In all 51 patients, HASTEDL was successfully acquired at 3 T and showed excellent image quality (median, 4; interquartile range, 3-4). Although BLADE was rated significantly higher for overall image quality, noise, contrast, sharpness, artifacts, CRSL, and diagnostic confidence than HASTEDL, no differences were found concerning the number (n = 102) and measured diameter of the detected hepatic lesions between the 2 sequences BLADE and HASTEDL.

CONCLUSIONS

The proposed single-breath-hold abdominal HASTEDL with variable refocusing FAs is feasible at 3 T within SAR limits and yields high image quality and diagnostic confidence as compared with a standard T2-weighted acquisition technique, at a 10th of the acquisition time.

Feasibility and Implementation of a Deep Learning MR Reconstruction for TSE Sequences in Musculoskeletal Imaging

Magnetic Resonance Imaging (MRI) of the musculoskeletal system is one of the most common examinations in clinical routine. The application of Deep Learning (DL) reconstruction for MRI is increasingly gaining attention due to its potential to improve the image quality and reduce the acquisition time simultaneously. However, the technology has not yet been implemented in clinical routine for turbo spin echo (TSE) sequences in musculoskeletal imaging. The aim of this study was therefore to assess the technical feasibility and evaluate the image quality. Sixty examinations of knee, hip, ankle, shoulder, hand, and lumbar spine in healthy volunteers at 3 T were included in this prospective, internal-review-board-approved study. Conventional (TSE_S) and DL-based TSE sequences (TSE_DL) were compared regarding image quality, anatomical structures, and diagnostic confidence. Overall image quality was rated to be excellent, with a significant improvement in edge sharpness and reduced noise compared to TSE_S (p < 0.001). No difference was found concerning the extent of artifacts, the delineation of anatomical structures, and the diagnostic confidence comparing TSE_S and TSE_DL (p > 0.05). Therefore, DL image reconstruction for TSE sequences in MSK imaging is feasible, enabling a remarkable time saving (up to 75%), whilst maintaining excellent image quality and diagnostic confidence.

Accelerated T2-Weighted TSE Imaging of the Prostate Using Deep Learning Image Reconstruction: A Prospective Comparison with Standard T2-Weighted TSE Imaging

Multiparametric MRI (mpMRI) of the prostate has become the standard of care in prostate cancer evaluation. Recently, deep learning image reconstruction (DLR) methods have been introduced with promising results regarding scan acceleration. Therefore, the aim of this study was to investigate the impact of deep learning image reconstruction (DLR) in a shortened acquisition process of T2-weighted TSE imaging, regarding the image quality and diagnostic confidence, as well as PI-RADS and T2 scoring, as compared to standard T2 TSE imaging. Sixty patients undergoing 3T mpMRI for the evaluation of prostate cancer were prospectively enrolled in this institutional review board-approved study between October 2020 and March 2021. After the acquisition of standard T2 TSE imaging (T2_S), the novel T2 TSE sequence with DLR (T2_DLR) was applied in three planes. Overall, the acquisition time for T2_S resulted in 10:21 min versus 3:50 min for T2_DLR. The image evaluation was performed by two radiologists independently using a Likert scale ranging from 1-4 (4 best) applying the following criteria: noise levels, artifacts, overall image quality, diagnostic confidence, and lesion conspicuity. Additionally, T2 and PI-RADS scoring were performed. The mean patient age was 69 ± 9 years (range, 49-85 years). The noise levels and the extent of the artifacts were evaluated to be significantly improved in T2_DLR versus T2_S by both readers (p < 0.05). Overall image quality was also evaluated to be superior in T2_DLR versus T2_S in all three acquisition planes (p = 0.005-<0.001). Both readers evaluated the item lesion conspicuity to be superior in T2_DLR with a median of 4 versus a median of 3 in T2_S (p = 0.001 and <0.001, respectively). T2-weighted TSE imaging of the prostate in three planes with an acquisition time reduction of more than 60% including DLR is feasible with a significant improvement of image quality.

Image Quality Improvement of Dynamic Contrast-Enhanced Gradient Echo Magnetic Resonance Imaging by Iterative Denoising and Edge Enhancement

OBJECTIVES

The aim of this study was to investigate the impact of a novel edge enhancement and iterative denoising algorithm in 1.5-T T1-weighted dynamic contrast-enhanced (DCE) gradient echo (GRE) magnetic resonance imaging of the abdomen on image quality, noise levels, diagnostic confidence, and lesion detectability.

MATERIALS AND METHODS

Fifty patients who underwent a clinically indicated magnetic resonance imaging with DCE imaging of the abdomen between June and August 2020 were included in this retrospective, monocentric, institutional review board-approved study. For DCE imaging, a series of 3 volume interpolated breath-hold examinations (VIBEs) was performed. The raw data of all DCE imaging studies were processed twice, once using standard reconstruction (DCES) and again using an edge enhancement and iterative denoising approach (DCEDE). All imaging studies were randomly reviewed by 2 radiologists independently regarding noise levels, arterial contrast, sharpness of vessels, overall image quality, and diagnostic confidence using a Likert scale ranging from 1 to 4, with 4 being the best. Furthermore, lesion detectability was evaluated using the same ranking system.

RESULTS

All 50 imaging studies were successfully reconstructed with both methods. Interreader agreement (Cohen κ) was substantial to perfect for both readers. Arterial contrast and sharpness of vessels were rated superior by both readers with a median of 4 in DCEDE versus a median of 3 in DCES (P < 0.001). Furthermore, noise levels as well as overall image quality were rated higher with a median of 4 in DCEDE compared with a median of 3 in DCES (P < 0.001). Lesion detectability was evaluated to be superior in DCEDE with a median of 4 versus DCES with a median of 3 (P < 0.001). Consequently, diagnostic confidence was also rated to be superior in DCEDE with a median of 4 versus DCES with a median of 3 (P < 0.001).

CONCLUSIONS

Iterative denoising and edge enhancement are feasible in DCE imaging of the abdomen providing superior arterial contrast, noise levels, and overall image quality. Furthermore, lesion detectability and diagnostic confidence were significantly improved using this novel reconstruction method. Further reduction of acquisition time might be possible via reduction of increased noise levels using this presented method.

Nutritional support during the hospital stay reduces mortality in patients with different types of cancers: secondary analysis of a prospective randomized trial

BACKGROUND

Nutritional support in patients with cancer aims at improving quality of life. Whether use of nutritional support is also effective in improving clinical outcomes requires further study.

PATIENTS AND METHODS

In this preplanned secondary analysis of patients with cancer included in a prospective, randomized-controlled, Swiss, multicenter trial (EFFORT), we compared protocol-guided individualized nutritional support (intervention group) to standard hospital food (control group) regarding mortality at 30-day (primary endpoint) and other clinical outcomes.

RESULTS

We analyzed 506 patients with a main admission diagnosis of cancer, including lung cancer (n = 113), gastrointestinal tumors (n = 84), hematological malignancies (n = 108) and other types of cancer (n = 201). Nutritional risk based on Nutritional Risk Screening (NRS 2002) was an independent predictor for mortality over 180 days with an (age-, sex-, center-, type of cancer-, tumor activity- and treatment-) adjusted hazard ratio of 1.29 (95% CI 1.09-1.54; P = 0.004) per point increase in NRS. In the 30-day follow-up period, 50 patients (19.9%) died in the control group compared to 36 (14.1%) in the intervention group resulting in an adjusted odds ratio of 0.57 (95% CI 0.35-0.94; P = 0.027). Interaction tests did not show significant differences in mortality across the cancer type subgroups. Nutritional support also significantly improved functional outcomes and quality of life measures.

CONCLUSIONS

Compared to usual hospital nutrition without nutrition support, individualized nutritional support reduced the risk of mortality and improved functional and quality of life outcomes in cancer patients with increased nutritional risk. These data further support the inclusion of nutritional care in cancer management guidelines.

Application of a Novel Iterative Denoising and Image Enhancement Technique in T1-Weighted Precontrast and Postcontrast Gradient Echo Imaging of the Abdomen: Improvement of Image Quality and Diagnostic Confidence

OBJECTIVES

The aim of this study was to investigate the impact of a novel iterative denoising and image enhancement technique in T1-weighted precontrast and postcontrast volume-interpolated breath-hold examination (VIBE) of the abdomen on image quality, noise levels, and diagnostic confidence without change of acquisition parameters.

MATERIALS AND METHODS

Fifty patients were included in this retrospective, monocentric, institutional review board-approved study after clinically indicated magnetic resonance imaging of the abdomen including T1-weighted precontrast and postcontrast imaging. After acquisition of the standard VIBE (VIBES), images were processed with a novel reconstruction algorithm using the same raw data as for VIBES, resulting in a denoised and enhanced dataset (VIBEDE). Two different radiologists evaluated both datasets in a randomized order regarding sharpness of organs as well as vessels, noise levels, artifacts, overall image quality, and diagnostic confidence using a Likert scale ranging from 1 to 4 with 4 being the best. Furthermore, in the presence of focal liver lesions, the largest lesion was measured in the postcontrast dataset, and lesion detectability was analyzed using a Likert scale (1-4).

RESULTS

Precontrast and postcontrast sharpness of organs and sharpness of vessels were rated significantly superior by both readers in VIBEDE with a median of 4 (interquartile range, 0) compared with VIBES with a median of 3 (1) (all P's < 0.0001). Precontrast and postcontrast noise levels were also rated superior by both readers in VIBEDE with a median of 4 (0) compared with VIBES with a median of 3 (1) for precontrast and a median of 3 (0) (median of 3 [1] for reader 2) for postcontrast imaging (all P's < 0.0001).Overall image quality was also rated higher with a median of 4 (0) in VIBEDE versus 3 (1) in VIBES (P < 0.0001). Twenty-seven imaging studies contained liver lesions. There was no difference regarding the number and localization between the readers and between VIBES and VIBEDE. Lesion detectability was rated by both readers significantly better in VIBEDE with a median of 4 (0) compared with a median of 4 (1) for reader 1 and a median of 3 (1) for reader 2 (P = 0.001 for reader 1; P < 0.001 for reader 2). Consequently, diagnostic confidence was also significantly superior in VIBEDE versus VIBES with a median of 4 (0) for both (P = 0.001). Interreader agreement resulted in a Cohen κ of 0.76 for precontrast analysis as well as of 0.76 for postcontrast analysis.

CONCLUSIONS

Application of a novel iterative denoising and image enhancement technique in T1-weighted VIBE precontrast and postcontrast imaging of the abdomen is feasible, providing superior image quality, noise levels, and diagnostic confidence.

Diagnostic Confidence and Feasibility of a Deep Learning Accelerated HASTE Sequence of the Abdomen in a Single Breath-Hold

OBJECTIVE

The aim of this study was to evaluate the feasibility of a single breath-hold fast half-Fourier single-shot turbo spin echo (HASTE) sequence using a deep learning reconstruction (HASTEDL) for T2-weighted magnetic resonance imaging of the abdomen as compared with 2 standard T2-weighted imaging sequences (HASTE and BLADE).

MATERIALS AND METHODS

Sixty-six patients who underwent 1.5-T liver magnetic resonance imaging were included in this monocentric, retrospective study. The following T2-weighted sequences in axial orientation and using spectral fat suppression were compared: a conventional respiratory-triggered BLADE sequence (time of acquisition [TA] = 4:00 minutes), a conventional multiple breath-hold HASTE sequence (HASTES) (TA = 1:30 minutes), as well as a single breath-hold HASTE with deep learning reconstruction (HASTEDL) (TA = 0:16 minutes). Two radiologists assessed the 3 sequences regarding overall image quality, noise, sharpness, diagnostic confidence, and lesion detectability as well as lesion characterization using a Likert scale ranging from 1 to 4 with 4 being the best. Comparative analyses were conducted to assess the differences between the 3 sequences.

RESULTS

HASTEDL was successfully acquired in all patients. Overall image quality for HASTEDL was rated as good (median, 3; interquartile range, 3-4) and was significantly superior to HASTEs (P < 0.001) and inferior to BLADE (P = 0.001). Noise, sharpness, and artifacts for HASTEDL reached similar levels to BLADE (P ≤ 0.176) and were significantly superior to HASTEs (P < 0.001). Diagnostic confidence for HASTEDL was rated excellent by both readers and significantly superior to HASTEs (P < 0.001) and inferior to BLADE (P = 0.044). Lesion detectability and lesion characterization for HASTEDL reached similar levels to those of BLADE (P ≤ 0.523) and were significantly superior to HASTEs (P < 0.001). Concerning the number of detected lesions and the measured diameter of the largest lesion, no significant differences were found comparing BLADE, HASTES, and HASTEDL (P ≤ 0.912).

CONCLUSIONS

The single breath-hold HASTEDL is feasible and yields comparable image quality and diagnostic confidence to standard T2-weighted TSE BLADE and may therefore allow for a remarkable time saving in abdominal imaging.

Deep learning-accelerated T2-weighted imaging of the prostate: Reduction of acquisition time and improvement of image quality

PURPOSE

To introduce a novel deep learning (DL) T2-weighted TSE imaging (T2_DL) sequence in prostate MRI and investigate its impact on examination time, image quality, diagnostic confidence, and PI-RADS classification compared to standard T2-weighted TSE imaging (T2_S).

METHOD

Thirty patients who underwent multiparametric MRI (mpMRI) of the prostate due to suspicion of prostatic cancer were included in this retrospective study. Standard sequences were acquired consisting of T1- and T2-weighted imaging and diffusion-weighted imaging as well as the novel T2_DL. Axial acquisition time of T2_S was 4:37 min compared to 1:38 min of T2_DL. Two radiologists independently evaluated all imaging datasets in a blinded reading regarding image quality, lesion detectability, and diagnostic confidence using a Likert-scale ranging from 1 to 4 with 4 being the best. T2 score as well as PI-RADS score were obtained for the most malignant lesion.

RESULTS

Mean patient age was 65 ± 11 years. Noise levels and overall image quality were rated significantly superior by both readers with a median of 4 in T2_DL compared to a median of 3 in T2_S (all p < 0.001). Lesion detectability was also rated higher in T2_DL by both readers with a median of 4 versus a median of 3 in T2_S (p = 0.005 and <0.001, respectively). There was no difference regarding PI-RADS scoring between T2_DL and T2_S affecting patient management.

CONCLUSIONS

Deep learning axial T2w TSE imaging of the prostate is feasible with reduction of examination time of 65 % compared to standard imaging and improvement of image quality and lesion detectability.

Management of cardiac disease in cancer patients throughout oncological treatment: ESMO consensus recommendations

Cancer and cardiovascular (CV) disease are the most prevalent diseases in the developed world. Evidence increasingly shows that these conditions are interlinked through common risk factors, coincident in an ageing population, and are connected biologically through some deleterious effects of anticancer treatment on CV health. Anticancer therapies can cause a wide spectrum of short- and long-term cardiotoxic effects. An explosion of novel cancer therapies has revolutionised this field and dramatically altered cancer prognosis. Nevertheless, these new therapies have introduced unexpected CV complications beyond heart failure. Common CV toxicities related to cancer therapy are defined, along with suggested strategies for prevention, detection and treatment. This ESMO consensus article proposes to define CV toxicities related to cancer or its therapies and provide guidance regarding prevention, screening, monitoring and treatment of CV toxicity. The majority of anticancer therapies are associated with some CV toxicity, ranging from asymptomatic and transient to more clinically significant and long-lasting cardiac events. It is critical however, that concerns about potential CV damage resulting from anticancer therapies should be weighed against the potential benefits of cancer therapy, including benefits in overall survival. CV disease in patients with cancer is complex and treatment needs to be individualised. The scope of cardio-oncology is wide and includes prevention, detection, monitoring and treatment of CV toxicity related to cancer therapy, and also ensuring the safe development of future novel cancer treatments that minimise the impact on CV health. It is anticipated that the management strategies discussed herein will be suitable for the majority of patients. Nonetheless, the clinical judgment of physicians remains extremely important; hence, when using these best clinical practices to inform treatment options and decisions, practitioners should also consider the individual circumstances of their patients on a case-by-case basis.

P674Behavior of 2D and 3D derived ejection fraction and strain in patients with Hodgkin and non-Hodgkin lymphoma undergoing anthracycline-based chemotherapy, a prospective study

Background

Anthracyclines are one of the most effective chemotherapeutic agents but can lead to a decline in cardiac function. Two-dimensional (2D) speckle tracking echocardiography derived strain can predict cancer therapeutics-related cardiac dysfunction (CTRCD). However, little is known about the role of three-dimensional (3D) strain imaging in this setting.

Purpose

To evaluate different methods of Left Ventricular Ejection Fraction (LVEF) and strain, and to identify the best strain parameter for the prediction of CTRCD in this group of patients during treatment with anthracycline based chemotherapy.

Methods

Patients with Hodgkin's or non-Hodgkin's lymphoma receiving anthracycline based chemotherapy were enrolled. 2D-and 3D echocardiography was performed at 3 time points: baseline, at the completion of chemotherapy and at 1 year. 2D- and 3D LVEF (2D Modified Quinones, M-mode, 2D Biplane, 3D Philips, 3D GE and 3D TomTec), peak systolic left and right ventricular longitudinal, radial and circumferential strain and strain rate were measured. CTRCD was defined as a decrease in LVEF >10% to an absolute value of <53%. Lin's Concordance Correlation Coefficient (CCC) was calculated to compare LVEF methods. ANOVA, uni and multivariate analysis was performed.

Results

A total of 130 patients (79 males, mean age 57±16 years) were enrolled; 104 non-Hodgkin.3D Philips and GE (CCC 0.88 [0.84, 0.92]), 3D Philips and biplane (CCC 0.84 [0.79, 0.89]), 3D Philips and Modified Quinones (CCC 0.86 [0.82, 091]) as well as 3D Philips and M-mode (CCC 0.77 [0.70, 0.85]) showed strong correlation for LVEF. 15 patients (12%) developed CTRCD. Mean cumulative anthracycline dose was 263±65 mg/m2. 2D and 3D global longitudinal and circumferential peak systolic strain, 2D global longitudinal systolic and early diastolic strain rate, 2D global early diastolic strain rate, 2D right ventricular longitudinal peak systolic strain and systolic strain rate, 2D global radial peak systolic strain and systolic strain rate measured at the completion of chemotherapy were independent predictors of the development of CTRCD at 1 year post-chemotherapy. The strongest predictors of CTRCD were 3D global longitudinal and circumferential strain either individually (area under the curve, 0.90 and 0.95 respectively) or combined (area under the curve, 0.95) at the completion of chemotherapy; a cutoff value of <-18% in 3D global longitudinal strain had a sensitivity of 82% and specificity of 99%, while for 3D global circumferential peak systolic strain of <-24% had a sensitivity of 82% and specificity of 95%.

Conclusions

To our knowledge this is the first prospective trial that shows that 3D EF correlates well with other EF methods and 3D strain predicts cardiac toxicity in this group of patients with a very good sensitivity and specificity.

Acknowledgement/Funding

Department of Cardiovascular Medicine-Mayo Clinic Rochester MN

P2447Defining the values of left ventricular ejection fraction, volumes and strain by 2-dimensional echocardiography in subjects with normal cardiac geometry - a single center study

Background

Left ventricular ejection fraction (LVEF), end diastolic, end systolic volumes (EDV, ESV) and global longitudinal strain (GLS) are very important parameters that are frequently reported in cardiology. Normal cardiac geometry was not considered in articles that published normal values. It is important to know normal parameters for population studies. Our hypothesis is to analyze how EF, volumes and GLS may vary by age groups, gender and BMI in a population with normal cardiac geometry.

Purpose

To define the values in EF, volumes and GLS measurements in a healthy population with normal cardiac geometry stratified by age groups, gender and body mass index (BMI).

Methods

This is a single center retrospective study conducted from 2008 to 2018. We selected 4557 subjects (2605 females, 1952 males) >18 years with ≤ mild valvular heart disease, who underwent 2D-echocardiography (2DE) at Mayo clinic, Rochester. All selected subjects had normal LV geometry (i.e., LV mass index≤88g/m2 in females and ≤102g/m2 in males and relative wall thickness ≤0.42 measured by 2DE) and without any cardiovascular risk factors or structural or functional abnormality determined by 2DE. Based on age groups, gender and BMI, we assessed the variability in volumes indexed to body surface area, EF and GLS by Mean ± SD and two sample t-test.

Results

Mean age was 54±15 years (females = 53±15, males = 56±16), body surface area was 1.9 m2±0.2 (females = 1.8±0.2, males = 2.1±0.2), LV GLS −20.7% ±2 SD (females = −21.2±2, males= −20.2±1.9) ranging −16.1 to −27.6 in both genders (Figure); LVEF by Biplane volume method 62.6% ± 4 SD (females = 63±4.3, males=62±4.5). The end diastolic volume 63.6±11.7 cc/m2 (female = 59.9±10.3, males = 68.1±11.8) and end systolic volume 23.9 cc/m2±5.4 (female = 22.3±4.8, males = 25.9±5.5). LV GLS, Biplane EF values were higher in females and EDV and ESV values were higher in males. LV GLS values decreased with age in females (P<0.0001). While EF increased with age in both genders (P<0.0001), EDV and ESV values decreased with age (P<0.0001). When each gender is sub-divided based on their BMI (<25 and ≥25), GLS, EDV and ESV values were higher in population with BMI <25 (P<0.0001).

Normal geometry variables

Conclusion

To our knowledge, this is the biggest single center study to evaluate LV GLS values, LV EF, ED, ES volumes. These results can be used as reference values in a normal population.

Acknowledgement/Funding

None

P1942A trait of inflammation pathogenesis in human atherosclerosis: inflammasome driven interleukin-1 signaling in complex atherosclerotic plaques via hyperlipidemia trained innate immunity

Objectives

We aimed to investigate interleukin (IL)-1 generation and the regulatory role of inflammasome in human advanced atherosclerosis.

Background

IL-1β is key contributor to the inflammatory process associated with atherosclerosis and its complications. Recent studies suggested that IL-1β blockade reduces the burden of inflammation and recurrence of cardiovascular events. Yet, other cytokines in IL-1 family and the regulation of IL-1 generation in patients with atherosclerosis remains poorly understood.

Methods and results

A focused transcriptomic analysis in human atherosclerotic specimens discovered that human atherosclerotic plaques host a broad reservoir of inflammasome components, characterised by expression of canonical inflammasome gene NLRP6, NLRP12, NLRC4, NLRP3 and non-canonical inflammasome gene caspase 4 significantly elevated in the symptomatic plaques versus the asymptomatic plaques. Upregulation of NLRP3 inflammasome expression in plaque validated by immunohistochemistry staining suggested it as a distinctive characteristic of plaque vulnerability and complexity. Functional studies on atherosclerotic explants obtained from patients undergoing carotid endarterectomy revealed constitutive generation of IL-1β accompanied by secretion of comparable levels of IL-1α from the majority of the plaques, while IL-18 and IL-33 generation from some of the plaques. Stimulation of the plaques with inflammasome activators showed an inducible generation of both IL-1α and IL-1β, not IL-18 or IL-33, mediated by specific canonical and non-canonical inflammasome pathways. Analysis on the medication records of these patients indicated that plaques from patients with suboptimally controlled hyperlipidemia, imaging signs for plaque instability and inadequate statins therapy possessed higher recruitable production of IL-1β, suggesting the conventional atherogenic factor in regulation of inflammasome immunity and disease activity. Mechanistic studies on tissue and cells isolated from atheromatous plaques demonstrate that generation of mature IL-1β is via a mechanism controlled by NLRP3 and the effector caspase-1.

Conclusions

The study supports a profound canonical and non-canonical inflammasomes mediated plaque IL-1α/β generation, via a key mechanism by NLRP3 and caspase-1. The results provide biological insights into the clinical merit of high-intensity cholesterol lowering and anti-IL-1 signalling-directed therapies in high-risk patients with atherosclerosis.

Acknowledgement/Funding

KI-Mayo collaboration project, the Swedish Research Council, the Swedish Heart-Lung Foundation, European Union FP7 projects, the NIH