Cardiovascular magnetic resonance semi-automated threshold-based post-processing of right ventricular volumes in repaired tetralogy of Fallot.

Cardiovascular magnetic resonance (CMR) is the gold-standard to estimate right ventricular (RV) volumes, which are key for clinical management of patients with repaired tetralogy of Fallot (rTOF). Semi-automated threshold-based methods (SAT) have been proposed for CMR post-processing as alternatives to fully manual standard tracing. We investigated the impact of SAT on RV analysis using different thresholds in rTOF patients. RV volumes and mass were estimated using SAT and standard fully manual tracing methods in rTOF patients. Two threshold levels were set for SAT, i.e., default 50 (SAT-50) and 30 (SAT-30). RV stroke volumes (SV) were compared to main pulmonary artery forward flow (MPA-FF). Post-processing time, intra- and interobserver variabilities were compared across methods. Sixty-two CMRs of rTOF patients were analyzed. Compared to the standard fully manual tracing, no significant differences in RV mass, volumes and ejection fraction were observed using SAT-30, whereas SAT-50 significantly underestimated RV end-diastolic-volume index (EDVi) by 10.4% (mean difference of - 11.8 ± 6.2 ml/m2, p 0.03) and overestimated RV mass index by 21.8% (mean difference of 14.2 ± 11.9 g/m2, p 0.002). Compared to MPA-FF, RVSV by standard fully manual method and SAT-30 showed minor biases, respectively, 0.03 ml/m2 and 0.7 ml/m2, while SAT-50 underestimated RVSV by 6.86 ml/m2 (p < 0.001). In six patients, the degree of RV EDVi underestimation by SAT-50 determined a change of category from dilated to non-dilated RV. Intra- and interobserver variabilities were good to excellent for all methods. Post-processing duration was shorter for SAT compared to standard manual segmentation (5.5 ± 1.7 min vs. 19.5 ± 4.4 min, p < 0.001). CMR SAT-30 post-processing is a precise, accurate and time-saving method for biventricular assessment of volumes, ejection fraction and mass in rTOF.

Tondi L ，Figliozzi S ，Boveri S ，Sturla F ，Pasqualin G ，Camporeale A ，Disabato G ，Attanasio A ，Carrafiello G ，Spagnolo P ，Lombardi M ... -  《-》

Automated biventricular quantification in patients with repaired tetralogy of Fallot using a three-dimensional deep learning segmentation model.

Deep learning is the state-of-the-art approach for automated segmentation of the left ventricle (LV) and right ventricle (RV) in cardiovascular magnetic resonance (CMR) images. However, these models have been mostly trained and validated using CMR datasets of structurally normal hearts or cases with acquired cardiac disease, and are therefore not well-suited to handle cases with congenital cardiac disease such as tetralogy of Fallot (TOF). We aimed to develop and validate a dedicated model with improved performance for LV and RV cavity and myocardium quantification in patients with repaired TOF. We trained a three-dimensional (3D) convolutional neural network (CNN) with 5-fold cross-validation using manually delineated end-diastolic (ED) and end-systolic (ES) short-axis image stacks obtained from either a public dataset containing patients with no or acquired cardiac pathology (n = 100), an institutional dataset of TOF patients (n = 96), or both datasets mixed. Our method allows for missing labels in the training images to accommodate for different ED and ES phases for LV and RV as is commonly the case in TOF. The best performing model was applied to all frames of a separate test set of TOF cases (n = 36) and ED and ES phases were automatically determined for LV and RV separately. The model was evaluated against the performance of a commercial software (suiteHEART®, NeoSoft, Pewaukee, Wisconsin, US). Training on the mixture of both datasets yielded the best agreement with the manual ground truth for the TOF cases, achieving a median Dice similarity coefficient of (93.8%, 89.8%) for LV cavity and of (92.9%, 90.9%) for RV cavity at (ED, ES) respectively, and of 80.9% and 61.8% for LV and RV myocardium at ED. The offset in automated ED and ES frame selection was 0.56 and 0.89 frames on average for LV and RV respectively. No statistically significant differences were found between our model and the commercial software for LV quantification (two-sided Wilcoxon signed rank test, p<5%), while RV quantification was significantly improved with our model achieving a mean absolute error of 12 ml for RV cavity compared to 36 ml for the commercial software. We developed and validated a fully automatic segmentation and quantification approach for LV and RV, including RV mass, in patients with repaired TOF. Compared to a commercial software, our approach is superior for RV quantification indicating its potential in clinical practice.

Tilborghs S ，Liang T ，Raptis S ，Ishikita A ，Budts W ，Dresselaers T ，Bogaert J ，Maes F ，Wald RM ，Van De Bruaene A ... -  《-》

Myocardial strain analysis by cardiac magnetic resonance associated with arrhythmias in repaired tetralogy of Fallot patients.

Evaluating myocardial function using cardiac magnetic resonance (CMR) feature tracking provides a comprehensive cardiac assessment, particularly a detailed evaluation for patients with repaired tetralogy of Fallot (rTOF). This study aimed to identify factors associated with arrhythmias in rTOF patients utilizing conventional CMR techniques, including myocardial strain measurements. This single-center, retrospective study included 245 rTOF patients who underwent CMR between 2017 and 2023. Patients were stratified based on the presence or absence of arrhythmias during follow-up. The biventricular strain was assessed using CMR-derived feature tracking. Demographic, clinical, and imaging data were collected, and statistical analyses were performed to identify factors associated with arrhythmic events. The median age at surgery was 5.6 years (range 1-44 years), with the median age at CMR was 27.5 years (range 15-69 years). Over the follow-up period, 25 patients (10.2%) experienced atrial or ventricular arrhythmias. Univariate analysis revealed significant associations between arrhythmic events and older age at surgery and CMR, lower functional class, larger heart size on chest radiograph, and prolonged QRS duration (QRSd). Additionally, arrhythmias were associated with increased right ventricular (RV) volume, reduced RV and left ventricular (LV) ejection fraction (EF), and impaired strain values. Multivariate binary logistic regression, adjusting for age at surgery, NYHA class, QRSd, and cardiothoracic ratio, identified that a lower RV EF (adjusted odds ratio [aOR] 6.97), RV global radial strain (GRS) (aOR 6.68), RV global circumferential strain (GCS) (aOR 6.36), RV global longitudinal strain (GLS) (aOR 3.14), and LV GRS (aOR 3.02) were all significantly associated with arrhythmias. This study highlights the significant contribution of CMR-derived myocardial strain measurements in predicting arrhythmic events in patients with rTOF. In addition to conventional RV EF, strain metrics-particularly those of the right ventricle- emerged as strong, independent predictors of arrhythmias, offering valuable prognostic information for clinical management in this patient population. These findings underscore the importance of myocardial strain analysis as a complementary tool to conventional imaging in evaluating arrhythmic risk in rTOF patients. Not applicable.

Kangvanskol W ，Chungsomprasong P ，Sanwong Y ，Nakyen S ，Vijarnsorn C ，Patharateeranart K ，Chanthong P ，Kanjanauthai S ，Pacharapakornpong T ，Thammasate P ，Durongpisitkul K ，Soongswang J ... -  《BMC MEDICAL IMAGING》

Prognostic value of myocardial deformation parameters for outcome prediction in tetralogy of Fallot.

The prognostic value of myocardial deformation parameters in adults with repaired tetralogy of Fallot (rTOF) has not been well-elucidated. We therefore aimed to explore myocardial deformation parameters for outcome prediction in adults with rTOF using cardiovascular magnetic resonance imaging (CMR). Adults with rTOF and at least moderate pulmonary regurgitation were identified from an institutional prospective CMR registry. Left ventricular (LV) and right ventricular (RV) global strains were recorded in longitudinal (GLS), circumferential (GCS), and radial (GRS) directions. Major adverse cardiovascular events (MACE) were defined as a composite of mortality, resuscitated sudden death, sustained ventricular tachycardia (>30 seconds), or heart failure (hospital admission >24 hours). In patients with pulmonary valve replacement (PVR), pre- and post-PVR CMR studies were analyzed to assess for predictors of complete RV reverse remodeling, defined as indexed RV end-diastolic volume (RVEDVi) <110 mL/m2. Logistic regression models were used to estimate the odds ratio (OR) per unit change in absolute strain value associated with clinical outcomes and receiver operator characteristic curves were constructed with area under the curve (AUC) for select CMR variables. We included 307 patients (age 35 ± 13 years, 59% (180/307) male). During 6.1 years (3.3-8.8) of follow-up, PVR was performed in 142 (46%) and MACE occurred in 31 (10%). On univariate analysis, baseline biventricular ejection fraction (EF), mass, and all strain parameters were associated with MACE. After adjustment for LVEF, only LV-GLS remained independently predictive of MACE (OR 0.822 [0.693-0.976] p = 0.025). Receiver operator curves identified an absolute LV-GLS value less than 15 and LVEF less than 51% as thresholds for MACE prediction (AUC 0.759 [0.655-0.840] and 0.720 [0.608-0.810]). After adjusting for baseline RVEDVi, RV-GCS (OR 1.323 [1.094-1.600] p = 0.004), LV-GCS (OR 1.276 [1.029-1.582] p = 0.027) and LV-GRS (OR 1.101 [1.0210-1.200], p = 0.028) were independent predictors of complete remodeling post-PVR remodeling. Biventricular strain parameters predict clinical outcomes and post-PVR remodeling in rTOF. Further study will be necessary to establish the role of myocardial deformation parameters in clinical practice.

Thomas SK ，DSouza R ，Hanneman K ，Karur GR ，Houbois C ，Ishikita A ，D'Errico L ，Begun I ，Ng MY ，Wald RM ... -  《-》

Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.

Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided. (1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS? Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses. Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS. Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments. Level III, diagnostic study.

Lee CC ，Chen CW ，Yen HK ，Lin YP ，Lai CY ，Wang JL ，Groot OQ ，Janssen SJ ，Schwab JH ，Hsu FM ，Lin WH ... -  《-》