Computer-Assisted Transcatheter Mitral Valve Implantation for Valve-in-Valve Procedures.

Transcatheter mitral valve-in-valve is an alternative to high-risk reoperation on a failing bioprosthesis. It entails specific challenges such as left ventricular outflow tract obstruction. We propose a patient-specific augmented imaging based on preoperative planning to assist the procedure. Valve-in-valve simulation was performed to represent the optimal level of implantation and the neo-left ventricular outflow tract. These data were combined with intraoperative images through a real-time 3D/2D registration tool. All data were collected retrospectively on one case (pre and per-procedure imaging). We present for the first time an intraoperative guidance tool in transcatheter mitral valve-in-valve procedure.

Catheter navigation support for mechanical thrombectomy guidance: 3D/2D multimodal catheter-based registration with no contrast dye fluoroscopy.

PURPOSE: The fusion of pre-operative imaging and intra-operative fluoroscopy may support physicians during mechanical thrombectomy for catheter navigation from the aortic arch to carotids. Nevertheless, the aortic arch volume is too important for intra-operative contrast dye injection leading to a lack of common anatomical structure of interest that results in a challenging 3D/2D registration. The objective of this work is to propose a registration method between pre-operative 3D image and no contrast dye intra-operative fluoroscopy. METHODS: The registration method exploits successive 2D fluoroscopic images of the catheter navigating in the aortic arch. The similarity measure is defined as the normalized cross-correlation between a binary combination of catheter images and a pseudo-DRR resulting from the 2D binary projection of the pre-operative 3D image (MRA or CTA). The 3D/2D transformation is decomposed in out-plane and in-plane transformations to reduce computational complexity. The 3D/2D transformation is then obtained by maximizing the similarity measure through multiresolution exhaustive search. RESULTS: We evaluated the registration performance through dice score and mean landmark error. We evaluated the influence of parameters setting, aortic arch type and 2D navigation sequence duration. Results on a physical phantom and data from a patient who underwent a mechanical thrombectomy showed good registration accuracy with a dice score higher than 92% and a mean landmark error lower than the quarter of a carotid diameter (8-10 mm). CONCLUSION: A new registration method compatible with no contrast dye fluoroscopy has been proposed to guide the crossing from aortic arch to a carotid in mechanical thrombectomy. First evaluation showed the feasibility and accuracy of the method as well as its compatibility with clinical routine practice.

Computer-aided shape features extraction and regression models for predicting the ascending aortic aneurysm growth rate.

OBJECTIVE: ascending aortic aneurysm growth prediction is still challenging in clinics. In this study, we evaluate and compare the ability of local and global shape features to predict the ascending aortic aneurysm growth. MATERIAL AND METHODS: 70 patients with aneurysm, for which two 3D acquisitions were available, are included. Following segmentation, three local shape features are computed: (1) the ratio between maximum diameter and length of the ascending aorta centerline, (2) the ratio between the length of external and internal lines on the ascending aorta and (3) the tortuosity of the ascending tract. By exploiting longitudinal data, the aneurysm growth rate is derived. Using radial basis function mesh morphing, iso-topological surface meshes are created. Statistical shape analysis is performed through unsupervised principal component analysis (PCA) and supervised partial least squares (PLS). Two types of global shape features are identified: three PCA-derived and three PLS-based shape modes. Three regression models are set for growth prediction: two based on gaussian support vector machine using local and PCA-derived global shape features; the third is a PLS linear regression model based on the related global shape features. The prediction results are assessed and the aortic shapes most prone to growth are identified. RESULTS: the prediction root mean square error from leave-one-out cross-validation is: 0.112 mm/month, 0.083 mm/month and 0.066 mm/month for local, PCA-based and PLS-derived shape features, respectively. Aneurysms close to the root with a large initial diameter report faster growth. CONCLUSION: global shape features might provide an important contribution for predicting the aneurysm growth.

Deep-learning approach to automate the segmentation of aorta in non-contrast CTs.

Purpose: Segmentation of vascular structures in preoperative computed tomography (CT) is a preliminary step for computer-assisted endovascular navigation. It is a challenging issue when contrast medium enhancement is reduced or impossible, as in the case of endovascular abdominal aneurysm repair for patients with severe renal impairment. In non-contrast-enhanced CTs, the segmentation tasks are currently hampered by the problems of low contrast, similar topological form, and size imbalance. To tackle these problems, we propose a novel fully automatic approach based on convolutional neural network. Approach: The proposed method is implemented by fusing the features from different dimensions by three kinds of mechanisms, i.e., channel concatenation, dense connection, and spatial interpolation. The fusion mechanisms are regarded as the enhancement of features in non-contrast CTs where the boundary of aorta is ambiguous. Results: All of the networks are validated by three-fold cross-validation on our dataset of non-contrast CTs, which contains 5749 slices in total from 30 individual patients. Our methods achieve a Dice score of 88.7% as the overall performance, which is better than the results reported in the related works. Conclusions: The analysis indicates that our methods yield a competitive performance by overcoming the above-mentioned problems in most general cases. Further, experiments on our non-contrast CTs demonstrate the superiority of the proposed methods, especially in low-contrast, similar-shaped, and extreme-sized cases.

Assessment of shape-based features ability to predict the ascending aortic aneurysm growth.

The current guidelines for the ascending aortic aneurysm (AsAA) treatment recommend surgery mainly according to the maximum diameter assessment. This criterion has already proven to be often inefficient in identifying patients at high risk of aneurysm growth and rupture. In this study, we propose a method to compute a set of local shape features that, in addition to the maximum diameter D, are intended to improve the classification performances for the ascending aortic aneurysm growth risk assessment. Apart from D, these are the ratio DCR between D and the length of the ascending aorta centerline, the ratio EILR between the length of the external and the internal lines and the tortuosity T. 50 patients with two 3D acquisitions at least 6 months apart were segmented and the growth rate (GR) with the shape features related to the first exam computed. The correlation between them has been investigated. After, the dataset was divided into two classes according to the growth rate value. We used six different classifiers with input data exclusively from the first exam to predict the class to which each patient belonged. A first classification was performed using only D and a second with all the shape features together. The performances have been evaluated by computing accuracy, sensitivity, specificity, area under the receiver operating characteristic curve (AUROC) and positive (negative) likelihood ratio LHR+ (LHR-). A positive correlation was observed between growth rate and DCR (r = 0.511, p = 1.3e-4) and between GR and EILR (r = 0.472, p = 2.7e-4). Overall, the classifiers based on the four metrics outperformed the same ones based only on D. Among the diameter-based classifiers, k-nearest neighbours (KNN) reported the best accuracy (86%), sensitivity (55.6%), AUROC (0.74), LHR+ (7.62) and LHR- (0.48). Concerning the classifiers based on the four shape features, we obtained the best accuracy (94%), sensitivity (66.7%), specificity (100%), AUROC (0.94), LHR+ (+∞) and LHR- (0.33) with support vector machine (SVM). This demonstrates how automatic shape features detection combined with risk classification criteria could be crucial in planning the follow-up of patients with ascending aortic aneurysm and in predicting the possible dangerous progression of the disease.

Patient-specific finite element simulation of peripheral artery percutaneous transluminal angioplasty to evaluate the procedure outcome without stent implantation.

The purpose of this work is to present a patient-specific (PS) modeling approach for simulating percutaneous transluminal angioplasty (PTA) endovascular treatment and assessing the balloon sizing influence on short-term outcomes in peripheral arteries, i.e. without stent implantation. Two 3D PS stenosed femoral artery models, one with a dominant calcified atherosclerosis while the other with a lipidic plaque, were generated from pre-operative computed tomography angiography images. Elastoplastic constitutive laws were implemented within the plaque and artery models. Implicit finite element method (FEM) was used to simulate the balloon inflation and deflation for different sizings. Besides vessel strains, results were mainly evaluated in terms of the elastic recoil ratio (ERR) and lumen gain ratio (LGR) attained immediately after PTA. Higher LGR values were shown within the stenosed region of the lipidic patient. Simulated results also showed a direct and quantified correlation between balloon sizing and LGR and ERR for both patients after PTA, with a more significant influence on the lumen gain. The max principal strain values in the outer arterial wall increased at higher balloon sizes during inflation as well, with higher rates of increase when the plaque was calcified. Results show that our model could serve in finding a compromise for each stenosis type: maximizing the achieved lumen gain after PTA, but at the same time without damaging the arterial tissue. The proposed methodology can serve as a step toward a clinical decision support system to improve angioplasty balloon sizing selection prior to the surgery.

Validation of a Whole Heart Segmentation from Computed Tomography Imaging Using a Deep-Learning Approach.

The aim of this study is to develop an automated deep-learning-based whole heart segmentation of ECG-gated computed tomography data. After 21 exclusions, CT acquired before transcatheter aortic valve implantation in 71 patients were reviewed and randomly split in a training (n = 55 patients), validation (n = 8 patients), and a test set (n = 8 patients). A fully automatic deep-learning method combining two convolutional neural networks performed segmentation of 10 cardiovascular structures, which was compared with the manually segmented reference by the Dice index. Correlations and agreement between myocardial volumes and mass were assessed. The algorithm demonstrated high accuracy (Dice score = 0.920; interquartile range: 0.906-0.925) and a low computing time (13.4 s, range 11.9-14.9). Correlations and agreement of volumes and mass were satisfactory for most structures. Six of ten structures were well segmented. Deep-learning-based method allowed automated WHS from ECG-gated CT data with a high accuracy. Challenges remain to improve right-sided structures segmentation and achieve daily clinical application.

Statistical shape model of vessel centerline for endovascular paths comparison in mechanical thrombectomy.

Endovascular interventions are experiencing an important development. Despite many advantages of this type of intervention, catheter navigation is still a cause of difficulties or failure. Mechanical thrombectomy is one of these interventions where navigation difficulties are related to the ability to navigate the aortic arch and access the carotid. These difficulties are due to the selection of adequate catheters and guides for a specific anatomy and to the technical gesture to operate. The objective of this work is to propose a method to find similar endovascular navigation paths from pre-existing patients to support intervention in mechanical thrombectomy. For each patient, iso-centerlines of the aortic arch and supra-aortic trunks are extracted from pre-operative magnetic resonance angiography volume. A statistical shape model is computed from these vascular structure iso-centerlines. Euclidean distance between vectors of statistical shape model modes is used to compare endovascular navigation paths. A set of 6 patient cases was used to compute the statistical shape model. For validation, an additional set of 5 patient cases was considered to generate new iso-centerlines.Retrieval of closest iso-centerlines were correct in more than 95% of cases with the proposed method while this percentage goes down to 43% with Euclidean distance between 3D points of iso-centerlines.Clinical relevance-The presented method allows physicians to retrieve past navigation paths similar to a new one. Used in planning, this could allow to anticipate navigation difficulties in mechanical thrombectomy.

Influence of balloon design, plaque material composition, and balloon sizing on acute post angioplasty outcomes: An implicit finite element analysis.

In this work we propose a generic modeling approach for simulating percutaneous transluminal angioplasty (PTA) endovascular treatment, and evaluating the influence of balloon design, plaque composition, and balloon sizing on acute post-procedural outcomes right after PTA, without stent implantation. Clinically-used PTA balloons were classified into two categories according to their compliance characteristics, and were modeled correspondingly. Self-defined elastoplastic constitutive laws were implemented within the plaque and artery models, after calibration based on experimental and clinical data. Finite element method (FEM) implicit solver was used to simulate balloon inflation and deflation. Besides balloon profile at max inflation, results are mainly assessed in terms of the elastic recoil ratio (ERR) and lumen gain ratio (LGR) obtained immediately after PTA. No variations in ERR nor LGR values were detected when the balloon design changed, despite the differences observed in their profile at max inflation. Moreover, LGR and ERR inversely varied with the augmentation of calcification level within the plaque (-11% vs. +4% respectively, from fully lipidic to fully calcified plaque). Furthermore, results showed a direct correlation between balloon sizing and LGR and ERR, with noticeably higher rates of change for LGR (+18% and +2% for LGR and ERR respectively for a calcified plaque and a balloon pressure increasing from 10 to 14 atm). However a larger LGR comes with a higher risk of arterial rupture. This proposed methodology opens the way for evaluation of angioplasty balloon selections towards clinical procedure optimization.

Numerical simulation of fenestrated graft deployment: Anticipation of stent graft and vascular structure adequacy.

Fenestrated endovascular aneurism repair (FEVAR) is a minimally invasive technique, and its success depends on the adequacy of the correspondence between the visceral arteries ostia and position of the fenestrations of the stent graft (SG) during its deployment in juxtarenal aneurisms. However, the fenestration position is generally determined from a preoperative computerised tomography (CT) scan, without considering the vascular deformation induced by the insertion of the endovascular tools. Catheterisation difficulties may occur during clinical procedures. Accordingly, the objective of this work is to present an initial proof of concept aimed at anticipating and optimising the position of the fenestrations, while considering the vascular deformation induced by the insertion of the endovascular tools. The proposed method relies on the finite element method to simulate the SG deployment in a vascular structure (VS), and considers the vascular deformation induced by the tools. After determining the optimal simulation parameters for a patient-specific case, the robustness of the method is demonstrated on six other representative anatomies. The simulated SG is also compared with post-deployment CT observations, and demonstrates good adequacy. The results show that the numerically corrected fenestration positions, as determined from the simulated results following the insertion of the endovascular tools, deviate from those of the standard plan (as determined from the preoperative CT scan). This indicates that the SG-VS adequacy could be improved via simulation-based planning, to anticipate potential catheterisation difficulties.

Computer-assisted valve in valve in a deteriorated Mosaic valve using a library of bioprostheses.

Valve-in-valve (ViV) procedures have emerged from an off-label procedure to a safe and efficient alternative to redo aortic valve replacement in the treatment of symptomatic structural valve deterioration (SVD). During ViV procedures, optimal placement of the transcatheter heart valve (THV) inside the degenerated bioprosthesis is of paramount importance regarding complications such as device embolization, coronary obstruction, periprosthetic regurgitation, residual gradients, and mitral valve injury, but also for the attainment of optimal hemodynamics. In the case of the Mosaic (Medtronic, Minneapolis, MN) valve, the limited radiopaque landmarks represent a challenge to a reproducible, optimal implantation. Such implantation may require multiple contrast injections and transesophageal echocardiogram (TEE) guidance. We herein describe a computer-assisted ViV procedure inside a deteriorated Mosaic valve, achieving reproducible optimal placement using a preacquired library of bioprostheses 3D models. Our approach suggests an evolving paradigm in ViV procedures, from safe and efficient toward optimal therapy for symptomatic SVD.

Planning With Patient-Specific Rectal Sub-Region Constraints Decreases Probability of Toxicity in Prostate Cancer Radiotherapy.

Background: A rectal sub-region (SRR) has been previously identified by voxel-wise analysis in the inferior-anterior part of the rectum as highly predictive of rectal bleeding (RB) in prostate cancer radiotherapy. Translating the SRR to patient-specific radiotherapy planning is challenging as new constraints have to be defined. A recent geometry-based model proposed to optimize the planning by determining the achievable mean doses (AMDs) to the organs at risk (OARs), taking into account the overlap between the planning target volume (PTV) and OAR. The aim of this study was to quantify the SRR dose sparing by using the AMD model in the planning, while preserving the dose to the prostate. Material and Methods: Three-dimensional volumetric modulated arc therapy (VMAT) planning dose distributions for 60 patients were computed following four different strategies, delivering 78 Gy to the prostate, while meeting the genitourinary group dose constraints to the OAR: (i) a standard plan corresponding to the standard practice for rectum sparing (STDpl), (ii) a plan adding constraints to SRR (SRRpl), (iii) a plan using the AMD model applied to the rectum only (AMD_RECTpl), and (iv) a final plan using the AMD model applied to both the rectum and the SRR (AMD_RECT_SRRpl). After PTV dose normalization, plans were compared with regard to dose distributions, quality, and estimated risk of RB using a normal tissue complication probability model. Results: AMD_RECT_SRRpl showed the largest SRR dose sparing, with significant mean dose reductions of 7.7, 3, and 2.3 Gy, with respect to the STDpl, SRRpl, and AMD_RECTpl, respectively. AMD_RECT_SRRpl also decreased the mean rectal dose by 3.6 Gy relative to STDpl and by 3.3 Gy relative to SRRpl. The absolute risk of grade ≥1 RB decreased from 22.8% using STDpl planning to 17.6% using AMD_RECT_SRRpl considering SRR volume. AMD_RECT_SRRpl plans, however, showed slightly less dose homogeneity and significant increase of the number of monitor units, compared to the three other strategies. Conclusion: Compared to a standard prostate planning, applying dose constraints to a patient-specific SRR by using the achievable mean dose model decreased the mean dose by 7.7 Gy to the SRR and may decrease the relative risk of RB by 22%.

Catheter navigation support for liver radioembolization guidance: feasibility of structure-driven intensity-based registration.

PURPOSE: The fusion of pre/intraoperative images may improve catheter manipulation during radioembolization (RE) interventions by adding relevant information. The objective of this work is to propose and evaluate the performance of a RE guidance strategy relying on structure-driven intensity-based registration between preoperative CTA and intraoperative X-ray images. METHODS: The navigation strategy is decomposed into three image fusion steps, supporting the catheter navigation from the femoral artery till reaching the injection site (IS). During the pretreatment assessment intervention, the aorta and the origins of its side branches are projected on the intraoperative 2D fluoroscopy following a 3D/2D bone-based registration process, to assist the celiac trunk access. Subsequently, a similar approach consisting in projecting the hepatic vasculature on intraoperative DSA through 3D/2D vessel-based registration is performed to assist the IS location. Lastly, the selected IS is reproduced during the treatment intervention by employing 2D/2D image-based registration between pretreatment and treatment fluoroscopic images. RESULTS: The three fusion steps were independently evaluated on subsets of 20, 19 and 5 patient cases, respectively. Best results were obtained with gradient difference as similarity measure and with a delimited preoperative vascular structure for vessel-based registration. The approach resulted in qualitatively appropriate anatomical correspondences when projecting the preoperative structures on intraoperative images. With the best configuration, the registration steps showed accuracy and feasibility in aligning data, with global mean landmarks errors of 1.59 mm, 2.32 mm and 2.17 mm, respectively, a computation time that never exceeded 5 s, 25 s and 11 s, respectively, and a user interaction limited to manual initialization of the 3D/2D registration. CONCLUSION: An image fusion-based approach has been specifically proposed for RE procedures guidance. The catheter manipulation strategy based on the fusion of pre- and intraoperative images has the potential to support different steps of the RE clinical workflow and to guide the overall procedure.

Similarity measures and attribute selection for case-based reasoning in transcatheter aortic valve implantation.

In a clinical decision support system, the purpose of case-based reasoning is to help clinicians make convenient decisions for diagnoses or interventional gestures. Past experience, which is represented by a case-base of previous patients, is exploited to solve similar current problems using four steps-retrieve, reuse, revise, and retain. The proposed case-based reasoning has been focused on transcatheter aortic valve implantation to respond to clinical issues pertaining vascular access and prosthesis choices. The computation of a relevant similarity measure is an essential processing step employed to obtain a set of retrieved cases from a case-base. A hierarchical similarity measure that is based on a clinical decision tree is proposed to better integrate the clinical knowledge, especially in terms of case representation, case selection and attributes weighting. A case-base of 138 patients is used to evaluate the case-based reasoning performance, and retrieve- and reuse-based criteria have been considered. The sensitivity for the vascular access and the prosthesis choice is found to 0.88 and 0.94, respectively, with the use of the hierarchical similarity measure as opposed to 0.53 and 0.79 for the standard similarity measure. Ninety percent of the suggested solutions are correctly classified for the proposed metric when four cases are retrieved. Using a dedicated similarity measure, with relevant and weighted attributes selected through a clinical decision tree, the set of retrieved cases, and consequently, the decision suggested by the case-based reasoning are substantially improved over state-of-the-art similarity measures.

Patient-specific access planning in minimally invasive mitral valve surgery.

BACKGROUND: Minimally invasive mitral valve repair or replacement (MIMVR) approaches have been increasingly adopted for the treatment of mitral regurgitation, allowing a shorter recovery time and improving postoperative quality of life. However, inadequate positioning of the right mini thoracotomy access (working port) translates into suboptimal exposure, prolonged operative times and, potentially, reduction in the quality of mitral repair. At present, we are missing tools to further improve the positioning of the working port in order to ameliorate surgical exposure in a patient- specific fashion. METHODS AND EVALUATION OF THE HYPOTHESIS: We hypothesized that computation of relevant anatomical measurements from preoperative CT scans in patients undergoing MIMVR may provide patient-specific information in order to propose the surgical access that best fits to the patient's morphology. We hypothesized that this may systematize optimal mitral valve exposure, facilitating the procedure and potentially ameliorating the outcomes. We also hypothesized that preoperative simulation of the working port site and surgical instruments' insertion using a three-dimensional virtual model of the patient is feasible and may help in the customization of ports positioning. The hypothesis was evaluated by a multidisciplinary team including cardiac surgeons, experts in medical image processing and biomedical engineers. CT scans of 14 patients undergoing MIMVR were segmented to visualize 3D chest bones and heart structures meshes. The mitral valve annulus is pointed manually by the expert or extracted automatically when contrast-enhanced CT scan was available. The valve plane was then calculated and the optimal incision location analyzed according to a) the perpendicularity and b) the distance between the intercostal spaces and the valve plane. An angle-chart representation for the 4th, 5th and 6th intercostal spaces and a color map illustrating the distance between the skin and the mitral valve were created. We started the development of a simulation tool for preoperative planning using 3D Slicer software. CONCLUSIONS: Several patient-specific factors (including the orientation of the mitral valve plane and the morphology of the chest cage) may influence the performance of a MIMVR procedure, but they are not quantitatively considered in the current planning strategy. We suggest that the clinical results of MIMVR can be improved through preoperative virtual simulation and computer-assisted surgery (through determination of working port and surgical instruments insertion positioning). Further research is justified and the development of a software tool for clinical evaluation is warranted to verify the current hypothesis.

Use of Numerical Simulation to Predict Iliac Complications During Placement of An Aortic Stent Graft.

BACKGROUND: During endovascular aneurysm repair (EVAR), complex iliac anatomy is a source of complications such as unintentional coverage of the hypogastric artery. The aim of our study was to evaluate ability to predict coverage of the hypogastric artery using a biomechanical model simulating arterial deformations caused by the delivery system. METHODS: The biomechanical model of deformation has been validated by many publications. The simulations were performed on 38 patients included retrospectively, for a total of 75 iliac arteries used for the study. On the basis of objective measurements, two groups were formed: one with "complex" iliac anatomy (n = 38 iliac arteries) and the other with "simple" iliac anatomy (n = 37 iliac arteries). The simulation enabled measurement of the lengths of the aorta and the iliac arteries once deformed by the device. Coverage of the hypogastric artery was predicted if the deformed renal/iliac bifurcation length (Lpre) was less than the length of the implanted device (Lstent-measured on the postoperative computed tomography [CT]) and nondeformed Lpre was greater than Lstent. RESULTS: Nine (12%) internal iliac arteries were covered unintentionally. Of the coverage attributed to perioperative deformations, 1 case (1.3%) occurred with simple anatomy and 6 (8.0%) with complex anatomy (P = 0.25). All cases of unintentional coverage were predicted by the simulation. The simulation predicted hypogastric coverage in 35 cases (46.7%). There were therefore 26 (34.6%) false positives. The simulation had a sensitivity of 100% and a specificity of 60.6%. On multivariate analysis, the factors significantly predictive of coverage were the iliac tortuosity index (P = 0.02) and the predicted margin between the termination of the graft limb and the origin of the hypogastric artery in nondeformed (P = 0.009) and deformed (P = 0.001) anatomy. CONCLUSIONS: Numerical simulation is a sensitive tool for predicting the risk of hypogastric coverage during EVAR and allows more precise preoperative sizing. Its specificity is liable to be improved by using a larger cohort.

Deformable image registration for radiation therapy: principle, methods, applications and evaluation.

Background: Deformable image registration (DIR) is increasingly used in the field of radiation therapy (RT) to account for anatomical deformations. The aims of this paper are to describe the main applications of DIR in RT and discuss current DIR evaluation methods. Methods: Articles on DIR published from January 2000 to October 2018 were extracted from PubMed and Science Direct. Our search was restricted to articles that report data obtained from humans, were written in English, and address DIR methods for RT. A total of 207 articles were selected from among 2506 identified in the search process. Results: At planning, DIR is used for organ delineation using atlas-based segmentation, deformation-based planning target volume definition, functional planning and magnetic resonance imaging-based dose calculation. In image-guided RT, DIR is used for contour propagation and dose calculation on per-treatment imaging. DIR is also used to determine the accumulated dose from fraction to fraction in external beam RT and brachytherapy, both for dose reporting and adaptive RT. In the case of re-irradiation, DIR can be used to estimate the cumulated dose of the two irradiations. Finally, DIR can be used to predict toxicity in voxel-wise population analysis. However, the evaluation of DIR remains an open issue, especially when dealing with complex cases such as the disappearance of matter. To quantify DIR uncertainties, most evaluation methods are limited to geometry-based metrics. Software companies have now integrated DIR tools into treatment planning systems for clinical use, such as contour propagation and fraction dose accumulation. Conclusions: DIR is increasingly important in RT applications, from planning to toxicity prediction. DIR is routinely used to reduce the workload of contour propagation. However, its use for complex dosimetric applications must be carefully evaluated by combining quantitative and qualitative analyses.

Structural valve deterioration does not alter tissue valves' radiopaque landmarks: Implications for valve-in-valve therapy.

BACKGROUND: Valve-in-valve is established as a safe and efficient alternative to redo surgery in the treatment of structural valve deterioration (SVD). In vitro models rely on the radiopaque landmarks of undeteriorated tissue valves to establish the optimal implantation level of the transcatheter heart valves inside the deteriorated valves. In computed assisted procedures, the radiopaque landmarks of the deteriorated valves may be used to guide valve implantation through image fusion. The purpose of this study is to determine whether SVD alters the radiopaque landmarks of stented tissue valves. METHODS: Our approach was based on the computation of relevant anatomical measurements from CT images. Radiopaque landmarks of degenerated bioprostheses and the corresponding undeteriorated valves were extracted to create surface meshes and cloud points using grey-level thresholding. 3D registration using an iterative closest point algorithm was used to align the corresponding cloud points, while the modified Hausdorff Distance was applied to determine the differences between them. RESULTS: The proposed evaluation was performed on 19 degenerated tissue valves. 15 valves were scanned from patients evaluated for valve-in-valve procedures, and 4 bioprostheses were scanned after surgical extraction during redo aortic valve replacement. All the degenerated valves were compared to the corresponding undeteriorated models. Overall, the mean difference between degenerated and undeteriorated valves was 0.33 ±â€¯0.12 mm. The maximum observed registration error was 0.66 mm. CONCLUSIONS: Our study demonstrates no significant difference between the radiopaque landmarks of deteriorated and undeteriorated bioprostheses after the occurrence of SVD. Our findings suggest therefore that SVD does not alter radiopaque landmarks of stented tissue valves. These results validate in-vitro studies of optimal transcatheter heart valves implantation inside deteriorated tissue valves based on their radiopaque landmarks, and allow the use of non-deteriorated valves' imaging features in computer assisted valve-in-valve procedures.

Automatic aortic root segmentation and anatomical landmarks detection for TAVI procedure planning.

PURPOSE: Minimally invasive trans-catheter aortic valve implantation (TAVI) has emerged as a treatment of choice for high-risk patients with severe aortic stenosis. However, the planning of TAVI procedures would greatly benefit from automation to speed up, secure and guide the deployment of the prosthetic valve. We propose a hybrid approach allowing the computation of relevant anatomical measurements along with an enhanced visualization. MATERIAL AND METHODS: After an initial step of centerline detection and aorta segmentation, model-based and statistical-based methods are used in combination with 3 D active contour models to exploit the complementary aspects of these methods and automatically detect aortic leaflets and coronary ostia locations. Important anatomical measurements are then derived from these landmarks. RESULTS: A validation on 50 patients showed good precision with respect to expert sizing for the ascending aorta diameter calculation (2.2 ± 2.1 mm), the annulus diameter (1.31 ± 0.75 mm), and both the right and left coronary ostia detection (1.96 ± 0.87 mm and 1.80 ± 0.74 mm, respectively). The visualization is enhanced thanks to the aorta and aortic root segmentation, the latter showing good agreement with manual expert delineation (Jaccard index: 0.96 ± 0.03). CONCLUSION: This pipeline is promising and could greatly facilitate TAVI planning.

Statistical Shape Model to Generate a Planning Library for Cervical Adaptive Radiotherapy.

External beam radiotherapy is extensively used to treat cervical carcinomas. A single planning CT scan enables the calculation of the dose distribution. The treatment is delivered over five weeks. Large per-treatment anatomical variations may hamper the dose delivery, with the potential of an organ-at-risk (OAR) overdose and a tumor underdose. To anticipate these deformations, a recent approach proposed three planning CTs with variable bladder volumes, which had the limitation of not covering all per-treatment anatomical variations. An original patient-specific population-based library has been proposed. It consisted of generating two representative anatomies, in addition to the standard planning CT anatomy. First, the cervix and bladder meshes of a population of 20 patients (314 images) were registered to an anatomical template, using a deformable mesh registration. An iterative point-matching algorithm was developed based on local shape context (histogram of polar or cylindrical coordinates and geodesic distance to the base) and on a topology constraint filter. Second, a standard principal component analysis (PCA) model of the cervix and bladder was generated to extract the dominant deformation modes. Finally, specific deformations were obtained using posterior PCA models, with a constraint representing the top of the uterus deformation. For a new patient, the cervix-uterus and bladder were registered to the template, and the patient's modeled planning library was built according to the model deformations. This method was applied following a leave-one-patient-out cross-validation. The performances of the modeled library were compared to those of the three-CT-based library, showing an improvement in both target coverage and OAR sparing.