Radiomics features of the cardiac blood pool to indicate hemodynamic changes in pulmonary hypertension (PH) due to heart failure with preserved ejection fraction (PH-HFpEF).

To test the hypothesis that cine MRI-derived radiomics features of the cardiac blood pool can represent hemodynamic characteristics of pulmonary hypertension-heart failure with preserved ejection fraction (PH-HFpEF). Nineteen PH-HFpEF patients (9 male, 57.8 ± 14.7 years) and 19 healthy controls (13 male, 50.3 ± 13.6 years) were enrolled. All participants underwent a cardiac MRI scan. One hundred and seven radiomics features (7 classes) of the blood pool in the left and right ventricles/atrium (LV/RV/LA/RA) were extracted from 4-chamber cine (2D images) at the stages of systole, rapid filling, diastasis, and atrial contraction within a cardiac cycle. For PH-HFpEF patients, features acquired from LV/LA were related to the pulmonary capillary wedge pressure (PCWP); features acquired from RV/RA were related to the mean pulmonary artery pressure (mPAP) using the Pearson correlation coefficient (r). Logistic regression, receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used to test the capability of radiomics features in discriminating 2 subject groups. Features acquired from different chambers at various periods present diverse properties in representing hemodynamic indices of PH-HFpEF. Multiple radiomics features blood pool were significantly related to PCWP and/or mPAP (r: 0.4-0.679, p < 0.05). In addition, multiple features of blood pools acquired at various time points within a cardiac cycle can efficiently discriminate PH-HFpEF from controls (individual AUC: 0.7-0.864). Cine MRI-derived radiomics features of the cardiac blood pool have the potential to characterize hemodynamic abnormalities in the context of PH-HFpEF.

Inter-scanner super-resolution of 3D cine MRI using a transfer-learning network for MRgRT.

Objective. Deep-learning networks for super-resolution (SR) reconstruction enhance the spatial-resolution of 3D magnetic resonance imaging (MRI) for MR-guided radiotherapy (MRgRT). However, variations between MRI scanners and patients impact the quality of SR for real-time 3D low-resolution (LR) cine MRI. In this study, we present a personalized super-resolution (psSR) network that incorporates transfer-learning to overcome the challenges in inter-scanner SR of 3D cine MRI.Approach: Development of the proposed psSR network comprises two-stages: (1) a cohort-specific SR (csSR) network using clinical patient datasets, and (2) a psSR network using transfer-learning to target datasets. The csSR network was developed by training on breath-hold and respiratory-gated high-resolution (HR) 3D MRIs and their k-space down-sampled LR MRIs from 53 thoracoabdominal patients scanned at 1.5 T. The psSR network was developed through transfer-learning to retrain the csSR network using a single breath-hold HR MRI and a corresponding 3D cine MRI from 5 healthy volunteers scanned at 0.55 T. Image quality was evaluated using the peak-signal-noise-ratio (PSNR) and the structure-similarity-index-measure (SSIM). The clinical feasibility was assessed by liver contouring on the psSR MRI using an auto-segmentation network and quantified using the dice-similarity-coefficient (DSC).Results. Mean PSNR and SSIM values of psSR MRIs were increased by 57.2% (13.8-21.7) and 94.7% (0.38-0.74) compared to cine MRIs, with the reference 0.55 T breath-hold HR MRI. In the contour evaluation, DSC was increased by 15% (0.79-0.91). Average time consumed for transfer-learning was 90 s, psSR was 4.51 ms per volume, and auto-segmentation was 210 ms, respectively.Significance. The proposed psSR reconstruction substantially increased image and segmentation quality of cine MRI in an average of 215 ms across the scanners and patients with less than 2 min of prerequisite transfer-learning. This approach would be effective in overcoming cohort- and scanner-dependency of deep-learning for MRgRT.

Advanced Diagnostic Techniques in Obstructive Sleep Apnea.

Optimal surgical and medical management of obstructive sleep apnea requires clinically reliable identification of patterns and sites of upper airway obstruction. A wide variety of modalities have been used to evaluate upper airway obstruction. Drug-induced sleep endoscopy (DISE) and cine MRI are increasingly used to identify upper airway obstruction sites, to characterize airway obstruction patterns, to determine optimum medical and surgical treatment, and to plan individualized surgical management. Here, we provide an overview of the applications of DISE and cine MRI in assessing upper airway obstruction in children and adults with obstructive sleep apnea.

Ferumoxytol-Enhanced Cardiac Cine MRI Reconstruction Using a Variable-Splitting Spatiotemporal Network.

BACKGROUND: Balanced steady-state free precession (bSSFP) imaging is commonly used in cardiac cine MRI but prone to image artifacts. Ferumoxytol-enhanced (FE) gradient echo (GRE) has been proposed as an alternative. Utilizing the abundance of bSSFP images to develop a computationally efficient network that is applicable to FE GRE cine would benefit future network development. PURPOSE: To develop a variable-splitting spatiotemporal network (VSNet) for image reconstruction, trained on bSSFP cine images and applicable to FE GRE cine images. STUDY TYPE: Retrospective and prospective. SUBJECTS: 41 patients (26 female, 53 ± 19 y/o) for network training, 31 patients (19 female, 49 ± 17 y/o) and 5 healthy subjects (5 female, 30 ± 7 y/o) for testing. FIELD STRENGTH/SEQUENCE: 1.5T and 3T, bSSFP and GRE. ASSESSMENT: VSNet was compared to VSNet with total variation loss, compressed sensing and low rank methods for 14× accelerated data. The GRAPPA×2/×3 images served as the reference. Peak signal-to-noise-ratio (PSNR), structural similarity index (SSIM), left ventricular (LV) and right ventricular (RV) end-diastolic volume (EDV), end-systolic volume (ESV), and ejection fraction (EF) were measured. Qualitative image ranking and scoring were independently performed by three readers. Latent scores were calculated based on scores of each method relative to the reference. STATISTICS: Linear mixed-effects regression, Tukey method, Fleiss' Kappa, Bland-Altman analysis, and Bayesian categorical cumulative probit model. A P-value <0.05 was considered statistically significant. RESULTS: VSNet achieved significantly higher PSNR (32.7 ± 0.2), SSIM (0.880 ± 0.004), rank (2.14 ± 0.06), and latent scores (-1.72 ± 0.22) compared to other methods (rank >2.90, latent score < -2.63). Fleiss' Kappa was 0.52 for scoring and 0.61 for ranking. VSNet showed no significantly different LV and RV ESV (P = 0.938) and EF (P = 0.143) measurements, but statistically significant different (2.62 mL) EDV measurements compared to the reference. CONCLUSION: VSNet produced the highest image quality and the most accurate functional measurements for FE GRE cine images among the tested 14× accelerated reconstruction methods. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 1.

Advanced Diagnostic Techniques in Obstructive Sleep Apnea.

Optimal surgical and medical management of obstructive sleep apnea (OSA) requires clinically reliable identification of patterns and sites of upper airway obstruction. A wide variety of modalities has been used to evaluate upper airway obstruction. Drug-induced sleep endoscopy (DISE) and cine MRI are increasingly used to identify upper airway obstruction sites, to characterize airway obstruction patterns, to determine optimum medical and surgical treatment, and to plan individualized surgical management. Here, the authors provide an overview of the applications of DISE and cine MRI in assessing upper airway obstruction in children and adults with OSA.

3D cine-magnetic resonance imaging using spatial and temporal implicit neural representation learning (STINR-MR).

Objective. 3D cine-magnetic resonance imaging (cine-MRI) can capture images of the human body volume with high spatial and temporal resolutions to study anatomical dynamics. However, the reconstruction of 3D cine-MRI is challenged by highly under-sampled k-space data in each dynamic (cine) frame, due to the slow speed of MR signal acquisition. We proposed a machine learning-based framework, spatial and temporal implicit neural representation learning (STINR-MR), for accurate 3D cine-MRI reconstruction from highly under-sampled data.Approach. STINR-MR used a joint reconstruction and deformable registration approach to achieve a high acceleration factor for cine volumetric imaging. It addressed the ill-posed spatiotemporal reconstruction problem by solving a reference-frame 3D MR image and a corresponding motion model that deforms the reference frame to each cine frame. The reference-frame 3D MR image was reconstructed as a spatial implicit neural representation (INR) network, which learns the mapping from input 3D spatial coordinates to corresponding MR values. The dynamic motion model was constructed via a temporal INR, as well as basis deformation vector fields (DVFs) extracted from prior/onboard 4D-MRIs using principal component analysis. The learned temporal INR encodes input time points and outputs corresponding weighting factors to combine the basis DVFs into time-resolved motion fields that represent cine-frame-specific dynamics. STINR-MR was evaluated using MR data simulated from the 4D extended cardiac-torso (XCAT) digital phantom, as well as two MR datasets acquired clinically from human subjects. Its reconstruction accuracy was also compared with that of the model-based non-rigid motion estimation method (MR-MOTUS) and a deep learning-based method (TEMPEST).Main results. STINR-MR can reconstruct 3D cine-MR images with high temporal (<100 ms) and spatial (3 mm) resolutions. Compared with MR-MOTUS and TEMPEST, STINR-MR consistently reconstructed images with better image quality and fewer artifacts and achieved superior tumor localization accuracy via the solved dynamic DVFs. For the XCAT study, STINR reconstructed the tumors to a mean ± SD center-of-mass error of 0.9 ± 0.4 mm, compared to 3.4 ± 1.0 mm of the MR-MOTUS method. The high-frame-rate reconstruction capability of STINR-MR allows different irregular motion patterns to be accurately captured.Significance. STINR-MR provides a lightweight and efficient framework for accurate 3D cine-MRI reconstruction. It is a 'one-shot' method that does not require external data for pre-training, allowing it to avoid generalizability issues typically encountered in deep learning-based methods.

Prospective Comparison of Free-Breathing Accelerated Cine Deep Learning Reconstruction Versus Standard Breath-Hold Cardiac MRI Sequences in Patients With Ischemic Heart Disease.

BACKGROUND. Cine cardiac MRI sequences require repeated breath-holds, which can be difficult for patients with ischemic heart disease (IHD). OBJECTIVE. The purpose of the study was to compare a free-breathing accelerated cine sequence using deep learning (DL) reconstruction and a standard breath-hold cine sequence in terms of image quality and left ventricular (LV) measurements in patients with IHD undergoing cardiac MRI. METHODS. This prospective study included patients undergoing 1.5- or 3-T cardiac MRI for evaluation of IHD between March 15, 2023, and June 21, 2023. Examinations included an investigational free-breathing cine short-axis sequence with DL reconstruction (hereafter, cine-DL sequence). Two radiologists (reader 1 [R1] and reader 2 [R2]), in blinded fashion, independently assessed left ventricular ejection fraction (LVEF), left ventricular end-diastolic volume (LVEDV), left ventricular end-systolic volume (LVESV), and subjective image quality for the cine-DL sequence and a standard breath-hold balanced SSFP sequence; R1 assessed artifacts. RESULTS. The analysis included 26 patients (mean age, 64.3 ± 11.7 [SD] years; 14 men, 12 women). Acquisition was shorter for the cine-DL sequence than the standard sequence (mean ± SD, 0.6 ± 0.1 vs 2.4 ± 0.6 minutes; p < .001). The cine-DL sequence, in comparison with the standard sequence, showed no significant difference for LVEF for R1 (mean ± SD, 51.7% ± 14.3% vs 51.3% ± 14.7%; p = .56) or R2 (53.4% ± 14.9% vs 52.8% ± 14.6%; p = .53); significantly greater LVEDV for R2 (mean ± SD, 171.9 ± 51.9 vs 160.6 ± 49.4 mL; p = .01) but not R1 (171.8 ± 53.7 vs 165.5 ± 52.4 mL; p = .16); and no significant difference in LVESV for R1 (mean ± SD, 88.1 ± 49.3 vs 86.0 ± 50.5 mL; p = .45) or R2 (85.2 ± 48.1 vs 81.3 ± 48.2 mL; p = .10). The mean bias between the cine-DL and standard sequences by LV measurement was as follows: LVEF, 0.4% for R1 and 0.7% for R2; LVEDV, 6.3 mL for R1 and 11.3 mL for R2; and LVESV, 2.1 mL for R1 and 3.9 mL for R2. Subjective image quality was better for cine-DL sequence than the standard sequence for R1 (mean ± SD, 2.3 ± 0.5 vs 1.9 ± 0.8; p = .02) and R2 (2.2 ± 0.4 vs 1.9 ± 0.7; p = .02). R1 reported no significant difference between the cine-DL and standard sequences for off-resonance artifacts (3.8% vs 23.1% examinations; p = .10) and parallel imaging artifacts (3.8% vs 19.2%; p = .19); blurring artifacts were more frequent for the cine-DL sequence than the standard sequence (42.3% vs 7.7% examinations; p = .008). CONCLUSION. A free-breathing cine-DL sequence, in comparison with a standard breath-hold cine sequence, showed very small bias for LVEF measurements and better subjective quality. The cine-DL sequence yielded greater LV volumes than the standard sequence. CLINICAL IMPACT. A free-breathing cine-DL sequence may yield reliable LVEF measurements in patients with IHD unable to repeatedly breath-hold. TRIAL REGISTRATION. ClinicalTrials.gov NCT05105984.

Precision assessment of bowel motion quantification using 3D cine-MRI for radiotherapy.

Objective. The bowel is an important organ at risk for toxicity during pelvic and abdominal radiotherapy. Identifying regions of high and low bowel motion with MRI during radiotherapy may help to understand the development of bowel toxicity, but the acquisition time of MRI is rather long. The aim of this study is to retrospectively evaluate the precision of bowel motion quantification and to estimate the minimum MRI acquisition time.Approach. We included 22 gynaecologic cancer patients receiving definitive radiotherapy with curative intent. The 10 min pre-treatment 3D cine-MRI scan consisted of 160 dynamics with an acquisition time of 3.7 s per volume. Deformable registration of consecutive images generated 159 deformation vector fields (DVFs). We defined two motion metrics, the 50th percentile vector lengths (VL50) of the complete set of DVFs was used to measure median bowel motion. The 95th percentile vector lengths (VL95) was used to quantify high motion of the bowel. The precision of these metrics was assessed by calculating their variation (interquartile range) in three different time frames, defined as subsets of 40, 80, and 120 consecutive images, corresponding to acquisition times of 2.5, 5.0, and 7.5 min, respectively.Main results. For the full 10 min scan, the minimum motion per frame of 50% of the bowel volume (M50%) ranged from 0.6-3.5 mm for the VL50 motion metric and 2.3-9.0 mm for the VL95 motion metric, across all patients. At 7.5 min scan time, the variation in M50% was less than 0.5 mm in 100% (VL50) and 95% (VL95) of the subsets. A scan time of 5.0 and 2.5 min achieved a variation within 0.5 mm in 95.2%/81% and 85.7%/57.1% of the subsets, respectively.Significance. Our 3D cine-MRI technique quantifies bowel loop motion with 95%-100% confidence with a precision of 0.5 mm variation or less, using a 7.5 min scan time.

Cine magnetic resonance imaging in evaluating retroperitoneal leiomyosarcoma arising from the inferior vena cava.

Introduction: Leiomyosarcoma of the inferior vena cava is associated with poor prognosis. Complete resection is the only curative treatment. We present a patient with this disease in whom cine magnetic resonance imaging was valuable in selecting the surgical strategy and mitigating invasiveness. Case presentation: A 68-year-old woman presented with right-sided abdominal pain. Computed tomography revealed an 86 mm tumor in the right retroperitoneal space that extended into the inferior vena cava and reached superiorly to the right atrium. Percutaneous needle biopsy confirmed leiomyosarcoma. Cine magnetic resonance imaging demonstrated no adhesions between the tumor and the upper segment of inferior vena cava wall, nor with the right atrial wall, indicating resectability. Radical tumor resection was successfully performed without requiring thoracotomy. Conclusion: Cine magnetic resonance imaging appears to be useful in inferior vena cava leiomyosarcoma for evaluating adhesions between the tumor and vessel wall.

Cine magnetic resonance imaging predicts thrombus adhesion in metastatic renal cell carcinoma with an inferior vena cava tumor thrombus: A case of pathological complete response with pembrolizumab plus lenvatinib.

Introduction: Renal cell carcinoma with an inferior vena cava tumor thrombus is a challenging disease that requires a multimodal treatment approach. Pembrolizumab plus lenvatinib has displayed promising efficacy in metastatic renal cell carcinoma. Case presentation: A 61-year-old man was diagnosed with metastatic renal cell carcinoma and a tumor thrombus adhering to the inferior vena cava wall by cine magnetic resonance imaging. After 6 months of pembrolizumab and lenvatinib therapy, tumor shrinkage was detected, excluding the advanced portion of the inferior vena cava thrombus, and nephrectomy and thrombectomy were performed. Adhesion of the tumor thrombus to the inferior vena cava wall was observed during surgery. Resection produced a remarkable pathological complete response with no viable cells in the resected specimens, including the thrombus site. Conclusion: This case highlights the potential of pembrolizumab plus lenvatinib for treating advanced renal cell carcinoma with an inferior vena cava thrombus and the utility of cine magnetic resonance imaging for evaluating thrombus adhesion to the inferior vena cava.

ECG-free cine MRI with data-driven clustering of cardiac motion for quantification of ventricular function.

BACKGROUND: Despite the widespread use of cine MRI for evaluation of cardiac function, existing real-time methods do not easily enable quantification of ventricular function. Moreover, segmented cine MRI assumes periodicity of cardiac motion. We aim to develop a self-gated, cine MRI acquisition scheme with data-driven cluster-based binning of cardiac motion. METHODS: A Cartesian golden-step balanced steady-state free precession sequence with sorted k-space ordering was designed. Image data were acquired with breath-holding. Principal component analysis and k-means clustering were used for binning of cardiac phases. Cluster compactness in the time dimension was assessed using temporal variability, and dispersion in the spatial dimension was assessed using the Calinski-Harabasz index. The proposed and the reference electrocardiogram (ECG)-gated cine methods were compared using a four-point image quality score, SNR and CNR values, and Bland-Altman analyses of ventricular function. RESULTS: A total of 10 subjects with sinus rhythm and 8 subjects with arrhythmias underwent cardiac MRI at 3.0 T. The temporal variability was 45.6 ms (cluster) versus 24.6 ms (ECG-based) (p < 0.001), and the Calinski-Harabasz index was 59.1 ± 9.1 (cluster) versus 22.0 ± 7.1 (ECG based) (p < 0.001). In subjects with sinus rhythm, 100% of the end-systolic and end-diastolic images from both the cluster and reference approach received the highest image quality score of 4. Relative to the reference cine images, the cluster-based multiphase (cine) image quality consistently received a one-point lower score (p < 0.05), whereas the SNR and CNR values were not significantly different (p = 0.20). In cases with arrhythmias, 97.9% of the end-systolic and end-diastolic images from the cluster approach received an image quality score of 3 or more. The mean bias values for biventricular ejection fraction and volumes derived from the cluster approach versus reference cine were negligible. CONCLUSION: ECG-free cine cardiac MRI with data-driven clustering for binning of cardiac motion is feasible and enables quantification of cardiac function.

Cine MRI-derived radiomics features indicate hemodynamic changes in the pulmonary artery.

Although cine MRI-derived radiomics features in the cardiac blood pool have been used to represent cardiac function and motion, the clinical relevance of radiomics features in the great vessels is still unknown. The aim of the present study was to test the hypothesis that cine MRI-derived radiomics features of the pulmonary artery (PA) can represent hemodynamic abnormalities in pulmonary hypertension (PH). With the approval of the institutional review board (IRB), 50 PH patients (21 males, 36-89 years old, diagnosed with right heart catheterization [RHC]) and 23 healthy volunteers (14 males, 26-80 years old) were retrospectively enrolled in this study. All participants underwent cardiac 4D flow and cine MRI (25 retrospective phases) at the right ventricular (RV) outflow tract (RVOT). A total of 93 radiomics features were extracted from RVOT cine images through a fixed size region of interest (ROI) at the proximal part of the PA. The peak values of the 6 first order features were different between the PH patients and controls. 4D flow-derived mean velocity in PA was related to 'Kurtosis' (r = 0.452,), 'Range' (r = 0.426), 'Autocorrelation' (r = 0.407), 'Joint Average' (r = 0.459), 'Sum Average' (r = 0.459), 'High Gray Level Emphasis' (r = 0.41), 'Large Dependence High Gray Level Emphasis' (r = 0.44), 'High Gray Level Run Emphasis' (r = 0.422), 'Gray Level Variance' (r = 0.419), 'High Gray Level Zone Emphasis' (r = 0.451), and 'Small Area High Gray Level Emphasis' (r = 0.415). Mean RV pressure was related to 'Inverse Variance' (r = 0.43) and 'Run Percentage' (r = 0.403). All p values < 0.05. Cine MRI-derived PA radiomics features have the potential to serve as novel imaging biomarkers for representing hemodynamic changes in pulmonary circulation.

Quantitative metrics of the LV trabeculated layer by cardiac CT and cardiac MRI in patients with suspected noncompaction cardiomyopathy.

OBJECTIVES: To compare cardiac computed tomography (CCT) and cardiac magnetic resonance (CMR) for the quantitative assessment of the left ventricular (LV) trabeculated layer in patients with suspected noncompaction cardiomyopathy (NCCM). MATERIALS AND METHODS: Subjects with LV excessive trabeculation who underwent both CMR and CCT imaging as part of the prospective international multicenter NONCOMPACT clinical study were included. For each subject, short-axis CCT and CMR slices were matched. Four quantitative metrics were estimated: 1D noncompacted-to-compacted ratio (NCC), trabecular-to-myocardial area ratio (TMA), trabecular-to-endocardial cavity area ratio (TCA), and trabecular-to-myocardial volume ratio (TMV). In 20 subjects, end-diastolic and mid-diastolic CCT images were compared for the quantification of the trabeculated layer. Relationships between the metrics were investigated using linear regression models and Bland-Altman analyses. RESULTS: Forty-eight subjects (49.9 ± 12.8 years; 28 female) were included in this study. NCC was moderately correlated (r = 0.62), TMA and TMV were strongly correlated (r = 0.78 and 0.78), and TCA had excellent correlation (r = 0.92) between CMR and CCT, with an underestimation bias from CCT of 0.3 units, and 5.1, 4.8, and 5.4 percent-points for the 4 metrics, respectively. TMA, TCA, and TMV had excellent correlations (r = 0.93, 0.96, 0.94) and low biases (- 3.8, 0.8, - 3.8 percent-points) between the end-diastolic and mid-diastolic CCT images. CONCLUSIONS: TMA, TCA, and TMV metrics of the LV trabeculated layer in patients with suspected NCCM demonstrated high concordance between CCT and CMR images. TMA and TCA were highly reproducible and demonstrated minimal differences between mid-diastolic and end-diastolic CCT images. CLINICAL RELEVANCE STATEMENT: The results indicate similarity of CCT to CMR for quantifying the LV trabeculated layer, and the small differences in quantification between end-diastole and mid-diastole demonstrate the potential for quantifying the LV trabeculated layer from clinically performed coronary CT angiograms. KEY POINTS: • Data on cardiac CT for quantifying the left ventricular trabeculated layer are limited. • Cardiac CT yielded highly reproducible metrics of the left ventricular trabeculated layer that correlated well with metrics defined by cardiac MR. • Cardiac CT appears to be equivalent to cardiac MR for the quantification of the left ventricular trabeculated layer.

Determination of internal target volume with Cine-MRI sequence for prostate MRI-Guided radiotherapy.

BACKGROUND: In prostate radiotherapy, the intrafractional target motion negatively affects treatment accuracy. Generating internal target volume (ITV) using four-dimensional (4D) images may resolve the issue of intrafractional target motion induced by bladder filling and bowel movement. However, no 4D imaging techniques suitable for the prostate are currently available in clinical practice. PURPOSE: This study aimed to determine the ITV based on cine magnetic resonance imaging (MRI) sequence for intrafractional target motion management in prostate MRI-guided radiotherapy. MATERIALS AND METHODS: A reference ITV was generated in simulation process. Then, the reference ITV was adapted with cine MRI sequence before online planning in each fraction. Finally, the reference ITV was updated with the cine MRI sequence acquired during beam delivery after each fraction. Cine MRI sequences and positioning three-dimensional (3D) MRI from 35 patients were retrospectively collected. Clinical target volume (CTV) coverage was computed according to the two-dimensional contour of CTV and ITV on cine MRI images. Relative target size was calculated as the ratio of the volume of ITV and CTV. Isotropic planning target volume (PTV; 5 mm margin) and anisotropic PTV (3 mm margin in the posterior direction and 5 mm margin in other directions) were generated for comparison. RESULTS: The CTV coverage rate of the proposed ITV had a mean value of 98.61% ± 0.51%, whereas the CTV coverage rates of the isotropic and anisotropic PTVs were 97.43% ± 0.41% and 96.58% ± 0.73%, respectively. The proposed ITV had a relative target size of 1.79 ± 0.17, whereas the anisotropic and isotropic PTVs had relative target sizes of 1.92 ± 0.12 and 2.21 ± 0.19, respectively. For both the CTV coverage rate and target relative size, significant differences were observed between the proposed ITV and the other two PTVs (p < 0.05). CONCLUSION: The ITV achieved higher CTV coverage with smaller size than conventional isotropic and anisotropic PTVs, indicating that it can effectively deal with the intrafractional movement of the prostate.

Recent advances in the treatment of gastrointestinal motility disorders in children.

INTRODUCTION: Pediatric gastrointestinal motility disorders represent some of the most challenging clinical conditions with largely undefined pathogenetic pathways and therefore limited therapeutic options. Herein, we provide an overview of the recent advances in treatment options for these disorders and their clinical impact. AREAS COVERED: PubMed and Medline databases were searched for relevant articles related to the treatment of achalasia, esophageal atresia, gastroparesis, PIPO and constipation published between 2017 and 2022. In this article, we review and summarize recent advances in management of gastrointestinal motility disorders in children with a particular focus on emerging therapies as well as novel diagnostic modalities that help guide their application or develop new, more targeted treatments. EXPERT OPINION: Gastrointestinal motility disorders represent one of the most challenging conundrums in pediatric age and despite significant advances in investigative tools, the palette of treatment options remain limited. Overall, while pharmacological options have failed to bring a curative solution, recent advances in minimal invasive therapeutic and diagnostic techniques have emerged as potential keys to symptom and quality of life improvement, such as ENDOFLIP, POEM, cine-MRI, fecal microbiota transplantation.

Improvement of 2D cine image quality using 3D priors and cycle generative adversarial network for low field MRI-guided radiation therapy.

BACKGROUND: Cine magnetic resonance (MR) images have been used for real-time MR guided radiation therapy (MRgRT). However, the onboard MR systems with low-field strength face the problem of limited image quality. PURPOSE: To improve the quality of cine MR images in MRgRT using prior image information provided by the patient planning and positioning MR images. METHODS: This study employed MR images from 18 pancreatic cancer patients who received MR-guided stereotactic body radiation therapy. Planning 3D MR images were acquired during the patient simulation, and positioning 3D MR images and 2D sagittal cine MR images were acquired before and during the beam delivery, respectively. A deep learning-based framework consisting of two cycle generative adversarial networks (CycleGAN), Denoising CycleGAN and Enhancement CycleGAN, was developed to establish the mapping between the 3D and 2D MR images. The Denoising CycleGAN was trained to first denoise the cine images using the time domain cine image series, and the Enhancement CycleGAN was trained to enhance the spatial resolution and contrast by taking advantage of the prior image information from the planning and positioning images. The denoising performance was assessed by signal-to-noise ratio (SNR), structural similarity index measure, peak SNR, blind/reference-less image spatial quality evaluator (BRISQUE), natural image quality evaluator, and perception-based image quality evaluator scores. The quality enhancement performance was assessed by the BRISQUE and physician visual scores. In addition, the target contouring was evaluated on the original and processed images. RESULTS: Significant differences were found for all evaluation metrics after Denoising CycleGAN processing. The BRISQUE and visual scores were also significantly improved after sequential Denoising and Enhancement CycleGAN processing. In target contouring evaluation, Dice similarity coefficient, centroid distance, Hausdorff distance, and average surface distance values were significantly improved on the enhanced images. The whole processing time was within 20 ms for a typical input image size of 512 × 512. CONCLUSION: Taking advantage of the prior high-quality positioning and planning MR images, the deep learning-based framework enhanced the cine MR image quality significantly, leading to improved accuracy in automatic target contouring. With the merits of both high computational efficiency and considerable image quality enhancement, the proposed method may hold important clinical implication for real-time MRgRT.

Preliminary study of cine-MRI compression in MR-guided radiotherapy.

Background: Cine-magnetic resonance imaging (MRI) is currently used in real-time tumor tracking during magnetic resonance (MR)-guided radiotherapy. As a type of MRI specified for motion tracking, a few minutes' acquisition results in thousands of 2-dimensional (2D) images. For MR-guided radiotherapy consisting of multiple treatment fractions, the large number of cine-MRI images would be disproportionate to the tight clinical data storage available. To alleviate this issue, the feasibility of compression of cine-MRI via video encoders was investigated in this study. Methods: The cine-MRI images were first sorted into 3 sequences according to their plane orientations. Then, each sequence was reordered according to their acquisition times [time-based (TB)] or content similarities [similarity-based (SB)]. As a result, 3 sequences were obtained for 3 plan orientations. Next, the obtained sequences were processed by a video encoder and the corresponding 3 video files were achieved. We employed 3 popular video encoders: Motion JPEG (M-JPEG), Advanced Video Coding (AVC), and High Efficiency Video Coding (HEVC). The performances of the sequence reordering methods and video encoders were evaluated based on a total of 150 image sets. Results: The mean correlation quantities for SB sequences were higher than those for TB sequences by 3% (sagittal), 2% (coronal), and 1% (transverse), respectively. The average compression ratio (CR) yielded by the SB sequences was higher than that achieved by the TB sequences. Comparing with M-JPEG, the CRs obtained by AVC and HEVC were increased by 58% and 62% (sagittal), 16% and 23% (coronal), and 48% and 56% (transverse), respectively. Among the 3 video encoders, the highest CRs and restoration accuracy were achieved by HEVC. Conclusions: HEVC with inter-frame coding is more effective in reducing the redundant information in consecutive images. It is feasible to implement the video encoder for high-performance cine-MRI compression.

AI approach to biventricular function assessment in cine-MRI: an ultra-small training dataset and multivendor study.

Objective. It was a great challenge to train an excellent and generalized model on an ultra-small data set composed of multi-orientation cardiac cine magnetic resonance imaging (MRI) images. We try to develop a 3D deep learning method based on an ultra-small training data set from muti-orientation cine MRI images and assess its performance of automated biventricular structure segmentation and function assessment in multivendor.Approach. We completed the training and testing of our deep learning networks using only heart datasets of 150 cases (90 cases for training and 60 cases for testing). This datasets were obtained from three different MRI vendors and each subject included two phases of the cardiac cycle and three cine sequences. A 3D deep learning algorithm combining Transformers and U-Net was trained. The performance of the segmentation was evaluated using the Dice metric and Hausdorff distance (HD). Based on this, the manual and automatic results of cardiac function parameters were compared with Pearson correlation, intraclass correlation coefficient (ICC) and Bland-Altman analysis in multivendor.Main results. The results show that the average Dice of 0.92, 0.92, 0.94 and HD95 of 2.50, 1.36, 1.37 for three sequences. The automatic and manual results of seven parameters were excellently correlated with the lowestr2 value of 0.824 and the highest of 0.983. The ICC (0.908-0.989,P< 0.001) showed that the results were highly consistent. Bland-Altman with a 95% limit of agreement showed there was no significant difference except for the difference in RVESV (P= 0.005) and LVM (P< 0.001).Significance. The model had high accuracy in segmentation and excellent correlation and consistency in function assessment. It provides a fast and effective method for studying cardiac MRI and heart disease.

Hydrodynamic and Hemodynamic Interactions in Chronic Hydrocephalus.

BACKGROUND: During a cardiac cycle, intracranial pressure is related to arterial entry into the cranium and its interaction with intracranial compliance. The arterial inflow is compensated by intracranial compliance and, initially, the flushing of cerebrospinal fluid (CSF) into the cervical subarachnoid spaces. Our objective is to analyze the interactions between intracranial arteriovenous exchange and cerebrospinal fluid oscillations. METHOD: A total of 23 patients (73 ± 8 years) with suspected chronic hydrocephalus (CH) underwent an infusion test and phase-contrast MRI. Rout is an important factor in the diagnosis of CH. Patients were divided into 2 populations: probableCH (Rout: resistance to CSF outflow) (Rout > 12 mmHg/mL/min, 13 patients) and unlikelyCH (Rout < 12 mmHg/mL/min, 10 patients). We measured the intracranial vascular volume (arteriovenous stroke volume: SVvasc) and CSF (CSF stroke volume at upper cervical level: SVCSF) volume variations during the cardiac cycle. RESULTS: In the whole population, we observed a significant correlation between SVvasc and SVCSF (R2 = 0.43; p = 0.0007). In the population unlikelyCH, this correlation was significant (R2 = 0.76; p = 0.001). In the population probableCH, this correlation was not significant (R2 = 0.17, p = 0.16). CONCLUSIONS: These results show that the link between the compliance of the oscillating CSF and the abrupt arterial inflow seems to be altered in CH. CSF oscillations between intracranial and cervical fluid spaces limit the impact of the abrupt arterial inflow.

Comparative Study of 2D-Cine and 3D-wh Volumetry: Revealing Systemic Error of 2D-Cine Volumetry.

This study investigates the crucial factors influencing the end-systolic and end-diastolic volumes in MRI volumetry and their direct effects on the derived functional parameters. Through the simultaneous acquisition of 2D-cine and 3D whole-heart slices in end-diastole and end-systole, we present a novel direct comparison of the volumetric measurements from both methods. A prospective study was conducted with 18 healthy participants. Both 2D-cine and 3D whole-heart sequences were obtained. Despite the differences in the creation of 3D volumes and trigger points, the impact on the LV volume was minimal (134.9 mL ± 16.9 mL vs. 136.6 mL ± 16.6 mL, p < 0.01 for end-diastole; 50.6 mL ± 11.0 mL vs. 51.6 mL ± 11.2 mL, p = 0.03 for end-systole). In our healthy patient cohort, a systematic underestimation of the end-systolic volume resulted in a significant overestimation of the SV (5.6 mL ± 2.6 mL, p < 0.01). The functional calculations from the 3D whole-heart method proved to be highly accurate and correlated well with function measurements from the phase-contrast sequences. Our study is the first to demonstrate the superiority of 3D whole-heart volumetry over 2D-cine volumetry and sheds light on the systematic error inherent in 2D-cine measurements.