Segmentation of the left ventricular endocardium from magnetic resonance images by using different statistical shape models.

We evaluate in this paper different strategies for the construction of a statistical shape model (SSM) of the left ventricle (LV) to be used for segmentation in cardiac magnetic resonance (CMR) images. From a large database of LV surfaces obtained throughout the cardiac cycle from 3D echocardiographic (3DE) LV images, different LV shape models were built by varying the considered phase in the cardiac cycle and the registration procedure employed for surface alignment. Principal component analysis was computed to describe the statistical variability of the SSMs, which were then deformed by applying an active shape model (ASM) approach to segment the LV endocardium in CMR images of 45 patients. Segmentation performance was evaluated by comparing LV volumes derived by ASM segmentation with different SSMs and those obtained by manual tracing, considered as a reference. A high correlation (r(2)>0.92) was found in all cases, with better results when using the SSM models comprising more than one frame of the cardiac cycle.

Three-dimensional left ventricular segmentation from magnetic resonance imaging for patient-specific modelling purposes.

AIMS: To propose a nearly automated left ventricular (LV) three-dimensional (3D) surface segmentation procedure, based on active shape modelling (ASM) and built on a database of 3D echocardiographic (3DE) LV surfaces, for cardiac magnetic resonance (CMR) images, and to test its accuracy for LV volumes computation compared with 'gold standard' manual tracings and discs-summation method. METHODS AND RESULTS: The ASM was created based on segmented LV surfaces (4D LV analysis, Tomtec) from 3DE datasets of 205 patients. Then, it was applied to the cardiac magnetic resonance imaging short-axis (SAX) images stack of 12 consecutive patients. After proper realignment using two- and four-chambers CMR long-axis views both as reference and for initializing LV apex and base (six points in total), the ASM was iteratively and automatically updated to match the information of all the SAX planes contemporaneously, resulting in an endocardial LV 3D mesh from which volume was directly derived. The same CMR images were analysed by an experienced cardiologist to derive end-diastolic and end-systolic volumes. Linear correlation and Bland-Altman analyses were applied vs. the manual 'gold standard'. Active shape modelling results showed high correlations with manual values both for LV volumes (r(2) > 0.98) and ejection fraction (EF) (r(2) > 0.90), non-significant biases and narrow limits of agreement. CONCLUSION: The proposed method resulted in accurate detection of 3D LV endocardial surfaces, which lead to fast and reliable measurements of LV volumes and EF when compared with manual tracing of CMR SAX images. The segmented 3D mesh, including a realistic LV apex and base, could constitute a novel starting point for more realistic patient-specific finite element modelling.

FIELDRT: an open-source platform for the assessment of target volume delineation in radiation therapy.

OBJECTIVES: Target volume delineation (TVD) has been identified as a weakness in the accuracy of radiotherapy, both within and outside of clinical trials due to the intra/interobserver variations affecting the TVD quality. Sources of variations such as poor compliance or protocol violation may have adverse effect on treatment outcomes. In this paper, we present and describe the FIELDRT software developed for the ARENA project to improve the quality of TVD through qualitative and quantitative feedbacks and individual and personalized summary of trainee"s performance. METHODS: For each site-specific clinical case included in the FIELDRT software, reference volumes, minimum and maximum "acceptable" volumes and organ at risk were derived by outlines of consultants and senior trainees. The software components currently developed include: (a) user-friendly importing interface (b) analysis toolbox to compute quantitative and qualitative (c) visualiser and (d) structured report generator for personalised feedback. The FIELDRT software was validated by comparing the performance of 63 trainees and by measuring performance over time. In addition, a trainee evaluation day was held in 2019 to collect feedback on FIELDRT. RESULTS: Results show the trainees' improvement when reoutlining a case after reviewing the feedback generated from the FIELDRT software. Comments and feedback received after evaluation day were positive and confirmed that FIELDRT can be a useful application for training purposes. CONCLUSION: We presented a new open-source software to support education in TVD and ongoing continuous professional development for clinical oncology trainees and consultants. ARENA in combination with FIELDRT implements site-specific modules with reference target and organs at risk volumes and automatically evaluates individual performance using several quantitative and qualitative feedbacks. Pilot results suggests this software could be used as an education tool to reduce variation in TVD so to guarantee high quality in radiotherapy. ADVANCES IN KNOWLEDGE: FIELDRT is a new easy and free to use software aiming at supporting education in TVD and ongoing continuous professional development. The software provides quantitative/qualitative feedback and an exportable report with an individual and personalised summary of trainee's performance.

Discovery of stable and prognostic CT-based radiomic features independent of contrast administration and dimensionality in oesophageal cancer.

The aim of this work was to investigate radiomic analysis of contrast and non-contrast enhanced planning CT images of oesophageal cancer (OC) patients in terms of stability, dimensionality and contrast agent dependency. The prognostic significance of CT-based radiomic features was also evaluated. Different 2D and 3D radiomic features were extracted from contrast and non-contrast enhanced CT images of 213 patients from the multi-centre SCOPE1 randomised controlled trial (RCT) in OC. Feature stability was evaluated by randomly dividing patients into three groups and identifying textures with similar distributions among groups with a Kruskal-Wallis analysis. A paired two-sided Wilcoxon signed rank test was used to assess for significant differences in the remaining corresponding 2D and 3D stable features. A prognostic model was constructed using clinical characteristics and remaining filtered features. The discriminative ability of significant variables was tested using Kaplan-Meier analysis. A total of 238 2D and 3D radiomic features were computed from oesophageal CT images. More than 75 features were stable if extracted from homogeneous cohort (contrast or non-contrast enhanced CT images) and inhomogeneous cohort (contrast and non-contrast enhanced CT images). Among the remaining corresponding stable features computed from both cohorts, only 4 features did not show a statistically significant difference if obtained in 2D or in 3D (p-value < 0.05). A Cox regression model constructed using 5 clinical variables (age, sex, tumour, node and metastasis (TNM) stage, WHO performance status and contrast administration) and 4 radiomic variables (inverse varianceGLCM, large distance emphasisGLDZM, zone distance non uniformity normGLDZM, zone distance varianceGLDZM), identified one radiomic feature (zone distance varianceGLDZM) that was significantly associated with overall survival (p-value = 0.032, HR = 1.25, 95% CI = 1.02-1.52). A significant difference in overall survival between groups was found when considering a threshold of zone distance varianceGLDZM equals to 1.70 (X2 = 7.692, df = 1, p-value = 0.006). Zone distance varianceGLDZM was identified as the only stable CT radiomic feature statistically correlated with overall survival, independent of dimensionality and contrast administration. This feature was able to identify high-risk patients and if validated, could be the subject of a future clinical trial aiming to improve clinical decision making and personalise OC treatment.

Transthoracic echocardiography in patients undergoing mitral valve repair: comparison of new transthoracic 3D techniques to 2D transoesophageal echocardiography in the localization of mitral valve prolapse.

Successful mitral valve (MV) repair for degenerative mitral regurgitation (DMR) is mainly related to surgical expertise and MV anatomy. Although 2D echocardiography, specifically transoesophageal (TOE), provides precise information regarding MV anatomy, recent advancements in matrix technology meant a decisive step forward to the point where segmental MV analysis can be accurately performed from a noninvasive 3D transthoracic (TTE) approach. The aims of this study were: (a) to evaluate the feasibility and time required for real-time 3D TTE in a large consecutive cohort of patients with severe DMR in the assessment of MV anatomy; (b) to compare the accuracy of 3D TTE and 2D TOE versus surgical inspection in the recognition and localization of all components of the MV leaflets; (c) to establish the added diagnostic value of 3D colourDoppler examination to pure 3D morphologic evaluation. 149 consecutive patients with severe DMR underwent complete 3D TTE before surgery and 2D TOE in the operating room. Echocardiographic data obtained by the different techniques were compared with surgical inspection. 3D TTE was feasible in a relatively short time (8 ± 4 min), with good (49%) and optimal (33%) imaging quality in the majority of cases. 3D TTE had significant better overall accuracy compared to 2D TOE (93 and 91%, p < 0.05, respectively). 2D TOE was significantly more specific than 3D TTE in the identification of A3 prolapse (99 vs. 96%). The colourDoppler mode did not improve significantly the accuracy of 3D TTE, albeit it determined a better sensitivity in the detection of A2 prolapse if compared to 2D TOE (95 vs. 85%). 3D TTE with or without colourDoppler is a feasible and useful method in the analysis of MV prolapse; it allows a preoperative and noninvasive description of the pathology as accurate as the 2D TOE.

Feasibility and Accuracy of Automated Software for Transthoracic Three-Dimensional Left Ventricular Volume and Function Analysis: Comparisons with Two-Dimensional Echocardiography, Three-Dimensional Transthoracic Manual Method, and Cardiac Magnetic Resonance Imaging.

BACKGROUND: Recently, a new automated software package (HeartModel) was developed to obtain three-dimensional (3D) left ventricular (LV) volumes using a model-based algorithm (MBA) with a "one-button" simple system and user-adjustable slider. The aims of this study were to verify the feasibility and accuracy of the MBA in comparison with other commonly used imaging techniques in a large unselected population, to evaluate possible accuracy improvements of free operator border adjustments or changes of the slider's default position, and to identify differences in method accuracy related to specific pathologies. METHODS: This prospective study included consecutive 200 patients. LV volumes and ejection fraction were obtained using the MBA and compared with the two-dimensional biplane method, the 3D full-volume (3DFV) modality, and, in 90 of 200 cases, cardiac magnetic resonance (CMR) measurements. To evaluate the optimal position of the slider with respect to the 3DFV and CMR modalities, a set of threefold cross-validation experiments was performed. Optimized and manually corrected LV volumes obtained using the MBA were also tested. Linear correlation and Bland-Altman analysis were used to assess intertechnique agreement. RESULTS: Automatic volumes were feasible in 194 patients (94.5%), with a mean processing time of 29 ± 10 sec. MBA-derived volumes correlated significantly with all evaluated methods, with slight overestimation of two-dimensional biplane and slight underestimation of CMR measurements. Higher correlations were found between MBA and 3DFV measurements, with negligible differences both in volumes (overestimation) and in LV ejection fraction (underestimation), respectively. Optimization of the user-adjustable slider position improved the correlation and markedly reduced the bias between the MBA and 3DFV or CMR. The accuracy of MBA volumes was lower in some pathologies for incorrect definition of LV endocardium. CONCLUSIONS: The MBA is highly feasible, reproducible, and rapid, and it correlates highly with the traditional 3DFV method. It may represent a valid alternative to 3DFV measurement for everyday clinical use.

Reconstruction of the descending thoracic aorta by multiview compounding of 3-D transesophageal echocardiographic aortic data sets for improved examination and quantification of atheroma burden.

A robust and efficient approach to reconstruction of the descending thoracic aorta from contiguous 3-D transesophageal echocardiographic (TEE) images is proposed. An ad hoc image acquisition protocol was designed to acquire ordered and partially overlapped 3-D TEE data sets, followed by dedicated image processing to align and fuse all acquired data sets. Alignment strategy implemented pairwise rigid registration guided by a priori knowledge, and it was validated using artificially misaligned images. Image fusion was finally performed to enable visualization and analysis of extended field-of-view of the acquired aorta. The application of different fusion techniques was also investigated. The method was applied to a population of 17 consecutive patients. Qualitative and quantitative results supported the feasibility and accuracy of the proposed approach. In a clinical scenario, its application could allow the quantitative assessment of aortic plaque burden in the descending thoracic aorta from 3-D TEE images.

Semiautomated detection and quantification of aortic plaques from three-dimensional transesophageal echocardiography.

BACKGROUND: Aortic atherosclerosis is a risk factor for cerebrovascular events. Two-dimensional transesophageal echocardiographic quantification of descending aortic plaques is time-consuming and underestimates plaque burden. The aim of this study was to assess the feasibility and accuracy of a novel semiautomated program that uses three-dimensional (3D) transesophageal echocardiography to identify and quantify aortic plaque severity as determined by plaque thickness, volume, and number. The relationship between maximum plaque thickness and volume was also examined. METHODS: Descending aortic 3D transesophageal echocardiographic images from 58 patients were analyzed for plaque thickness, volume, and number using semiautomated custom software. The reference standard was manual assessment by an expert reader using 3D multiplanar reconstructions. Agreement and κ values were calculated to determine the program's accuracy against the reference standard. Correlation and bias were examined using linear regression and Bland-Altman statistics. Pearson's correlation was used to examine the relationship between maximum plaque thickness and volume. RESULTS: Analysis was possible in all patients. Overall agreement for the absolute presence or absence of plaque per patient was 95%. Agreement regarding the number of plaques per patient and plaque severity was high at 95% and 85%, respectively. Plaque volume was slightly underestimated by the program compared with manual measurements. The correlation between plaque thickness and volume was 0.56. CONCLUSIONS: The results of this study demonstrate that semiautomated plaque analysis of 3D transesophageal echocardiographic descending aortic data sets is feasible and accurate in determining plaque severity as measured by plaque thickness, volume, and number. This methodology allows the standardization of plaque quantification, which will improve its utility in clinical trials. A greater understanding of the importance of plaque thickness versus volume is needed.