An evaluation of physical and augmented patient-specific intracranial aneurysm simulators on microsurgical clipping performance and skills: a randomized controlled study.

OBJECTIVE: In the era of flow diversion, there is an increasing demand to train neurosurgeons outside the operating room in safely performing clipping of unruptured intracranial aneurysms. This study introduces a clip training simulation platform for residents and aspiring cerebrovascular neurosurgeons, with the aim to visualize peri-aneurysm anatomy and train virtual clipping applications on the matching physical aneurysm cases. METHODS: Novel, cost-efficient techniques allow the fabrication of realistic aneurysm phantom models and the additional integration of holographic augmented reality (AR) simulations. Specialists preselected suitable and unsuitable clips for each of the 5 patient-specific models, which were then used in a standardized protocol involving 9 resident participants. Participants underwent four sessions of clip applications on the models, receiving no interim training (control), a video review session (video), or a video review session and holographic clip simulation training (video + AR) between sessions 2 and 3. The study evaluated objective microsurgical skills, which included clip selection, number of clip applications, active simulation time, wrist tremor analysis during simulations, and occlusion efficacy. Aneurysm occlusions of the reference sessions were assessed by indocyanine green videoangiography, as well as conventional and photon-counting CT scans. RESULTS: A total of 180 clipping procedures were performed without technical complications. The measurements of the active simulation times showed a 39% improvement for all participants. A median of 2 clip application attempts per case was required during the final session, with significant improvement observed in experienced residents (postgraduate year 5 or 6). Wrist tremor improved by 29% overall. The objectively assessed aneurysm occlusion rate (Raymond-Roy class 1) improved from 76% to 80% overall, even reaching 93% in the extensively trained cohort (video + AR) (p = 0.046). CONCLUSIONS: The authors introduce a newly developed simulator training platform combining physical and holographic aneurysm clipping simulators. The development of exchangeable, aneurysm-comprising housings allows objective radio-anatomical evaluation through conventional and photon-counting CT scans. Measurable performance metrics serve to objectively document improvements in microsurgical skills and surgical confidence. Moreover, the different training levels enable a training program tailored to the cerebrovascular trainees' levels of experience and needs.

Impact of advanced imaging techniques on cardiac surgery-New insights provided by cardiac magnetic resonance.

This dialog between a cardiac surgeon (C.L.) and cardiac imager (J.W.W.) provides an overview of cardiac MRI (CMR) methods relevant to cardiac surgery. Major areas of focus include logistics of performing a CMR exam, as well as established and emerging methods for assessment of cardiac structure, function, valvular performance, and tissue characterization. Regarding tissue characterization, a major area of focus concerns CMR assessment of viability, for which this modality has been shown to provide incremental utility to conventional techniques for detection of presence and transmural extent of infarction, as well as powerful predictive utility of recovery of left ventricular systolic function as well as long term clinical prognosis in patients with an array of clinical conditions, including coronary artery disease and valvular heart disease both before and following cardiac surgery.

A Deep Learning-Based and Fully Automated Pipeline for Thoracic Aorta Geometric Analysis and Planning for Endovascular Repair from Computed Tomography.

Feasibility assessment and planning of thoracic endovascular aortic repair (TEVAR) require computed tomography (CT)-based analysis of geometric aortic features to identify adequate landing zones (LZs) for endograft deployment. However, no consensus exists on how to take the necessary measurements from CT image data. We trained and applied a fully automated pipeline embedding a convolutional neural network (CNN), which feeds on 3D CT images to automatically segment the thoracic aorta, detects proximal landing zones (PLZs), and quantifies geometric features that are relevant for TEVAR planning. For 465 CT scans, the thoracic aorta and pulmonary arteries were manually segmented; 395 randomly selected scans with the corresponding ground truth segmentations were used to train a CNN with a 3D U-Net architecture. The remaining 70 scans were used for testing. The trained CNN was embedded within computational geometry processing pipeline which provides aortic metrics of interest for TEVAR planning. The resulting metrics included aortic arch centerline radius of curvature, proximal landing zones (PLZs) maximum diameters, angulation, and tortuosity. These parameters were statistically analyzed to compare standard arches vs. arches with a common origin of the innominate and left carotid artery (CILCA). The trained CNN yielded a mean Dice score of 0.95 and was able to generalize to 9 pathological cases of thoracic aortic aneurysm, providing accurate segmentations. CILCA arches were characterized by significantly greater angulation (p = 0.015) and tortuosity (p = 0.048) in PLZ 3 vs. standard arches. For both arch configurations, comparisons among PLZs revealed statistically significant differences in maximum zone diameters (p < 0.0001), angulation (p < 0.0001), and tortuosity (p < 0.0001). Our tool allows clinicians to obtain objective and repeatable PLZs mapping, and a range of automatically derived complex aortic metrics.

Applications of augmented reality in the neurosurgical operating room: A systematic review of the literature.

Advancements in imaging techniques are key forces of progress in neurosurgery. The importance of accurate visualization of intraoperative anatomy cannot be overemphasized and is commonly delivered through traditional neuronavigation. Augmented Reality (AR) technology has been tested and applied widely in various neurosurgical subspecialties in intraoperative, clinical use and shows promise for the future. This systematic review of the literature explores the ways in which AR technology has been successfully brought into the operating room (OR) and incorporated into clinical practice. A comprehensive literature search was performed in the following databases from inception-April 2020: Ovid MEDLINE, Ovid EMBASE, and The Cochrane Library. Studies retrieved were then screened for eligibility against predefined inclusion/exclusion criteria. A total of 54 articles were included in this systematic review. The studies were sub- grouped into brain and spine subspecialties and analyzed for their incorporation of AR in the neurosurgical clinical setting. AR technology has the potential to greatly enhance intraoperative visualization and guidance in neurosurgery beyond the traditional neuronavigation systems. However, there are several key challenges to scaling the use of this technology and bringing it into standard operative practice including accurate and efficient brain segmentation of magnetic resonance imaging (MRI) scans, accounting for brain shift, reducing coregistration errors, and improving the AR device hardware. There is also an exciting potential for future work combining AR with multimodal imaging techniques and artificial intelligence to further enhance its impact in neurosurgery.

Aortic hemodynamics assessment prior and after valve sparing reconstruction: A patient-specific 4D flow-based FSI model.

INTRODUCTION: Valve-sparing root replacement (VSRR) of the ascending aorta is a life-saving procedure for the treatment of aortic aneurysms, but patients remain at risk for post-operative events involving the downstream native aorta, the mechanism for which is uncertain. It is possible that proximal graft replacement of the ascending aorta induces hemodynamics alterations in the descending aorta, which could trigger adverse events. Herein, we present a fluid-structure interaction (FSI) protocol, based on patient-specific geometry and boundary conditions, to assess impact of proximal aortic grafts on downstream aortic hemodynamics and distensibility. METHODS: Cardiac magnetic resonance (CMR), including MRA, cine-CMR and 4D flow sequences, was performed prior and after VSRR on one subject. Central blood pressure was non-invasively acquired at the time of the CMR: data were used to reconstruct the pre- and post-VSRR model and derive patient-specific boundary conditions for the FSI and a computational fluid dynamic (CFD) analysis with the same settings. Results were validated comparing the predicted velocity field against 4D flow dataset, over four landmarks along the aorta, and the predicted distensibility against the cine-CMR derived value. RESULTS: Instantaneous velocity magnitudes extracted from 4D flow and FSI were similar (p > 0.05), while CFD-predicted velocity was significantly higher (p < 0.001), especially in the descending aorta of the pre-VSRR model (vmax was 73 cm/s, 76 cm/s and 99 cm/s, respectively). As measured in cine-CMR, FSI predicted an increase in descending aorta distensibility after grafting (i.e., 4.02 to 5.79 10-3 mmHg-1). In the descending aorta, the post-VSRR model showed increased velocity, aortic distensibility, stress and strain and wall shear stress. CONCLUSIONS: Our Results indicate that i) the distensibility of the wall cannot be neglected, and hence the FSI method is necessary to obtain reliable results; ii) graft implantation induces alterations in the hemodynamics and biomechanics along the thoracic aorta, that may trigger adverse vessel remodeling.

Transcatheter MitraClip repair alters mitral annular geometry - device induced annular remodeling on three-dimensional echocardiography predicts therapeutic response.

BACKGROUND: Echocardiography (echo) is widely used to guide therapeutic decision-making for patients being considered for MitraClip. Relative utility of two- (2D) and three-dimensional (3D) echo predictors of MitraClip response, and impact of MitraClip on mitral annular geometry, are uncertain. METHODS: The study population comprised patients with advanced (> moderate) MR undergoing MitraClip. Mitral annular geometry was quantified on pre-procedural 2D transthoracic echocardiography (TTE) and intra-procedural 3D transesophageal echocardiography (TEE); 3D TEE was used to measure MitraClip induced changes in annular geometry. Optimal MitraClip response was defined as ≤mild MR on follow-up (mean 2.7 ± 2.5 months) post-procedure TTE. RESULTS: Eighty patients with advanced MR underwent MitraClip; 41% had optimal response (≤mild MR). Responders had smaller pre-procedural global left ventricular (LV) end-diastolic size and mitral annular diameter on 2D TTE (both p ≤ 0.01), paralleling smaller annular area and circumference on 3D TEE (both p = 0.001). Mitral annular size yielded good diagnostic performance for optimal MitraClip response (AUC 0.72, p < 0.01). In multivariate analysis, sub-optimal MitraClip response was independently associated with larger pre-procedural mitral annular area on 3D TEE (OR 1.93 per cm2/m2 [CI 1.19-3.13], p = 0.007) and global LV end-diastolic volume on 2D TTE (OR 1.29 per 10 ml/m2 [CI 1.02-1.63], p = 0.03). Substitution of 2D TTE derived mitral annular diameter for 3D TEE data demonstrated a lesser association between pre-procedural annular size (OR 5.36 per cm/m2 [CI 0.95-30.19], p = 0.06) and sub-optimal MitraClip response. Matched pre- and post-procedural TEE analyses demonstrated MitraClip to acutely decrease mitral annular area and circumference (all p < 0.001) as well as mitral tenting height, area, and volume (all p < 0.05): Magnitude of MitraClip induced reductions in mitral annular circumference on intra-procedural 3D TEE was greater among patients with, compared to those without, sub-optimal MitraClip response (>mild MR) on followup TTE (p = 0.017); greater magnitude of device-induced annular reduction remained associated with sub-optimal MitraClip response even when normalized for pre-procedure annular circumference (p = 0.028). CONCLUSIONS: MitraClip alters mitral annular geometry as quantified by intra-procedural 3D TEE. Pre-procedural mitral annular dilation and magnitude of device-induced reduction in mitral annular size on 3D TEE are each associated with sub-optimal therapeutic response to MitraClip.

Incremental Utility of Right Ventricular Dysfunction in Patients With Myeloproliferative Neoplasm-Associated Pulmonary Hypertension.

BACKGROUND: Myeloproliferative neoplasm (MPN) has been associated with pulmonary hypertension (PH) on the basis of small observational studies, but the mechanism and clinical significance of PH in MPN are not well established. The aims of this study were to expand understanding of PH in a well-characterized MPN cohort via study of PH-related symptoms, mortality risk, and cardiac remodeling sequalae of PH using quantitative echocardiographic methods. METHODS: The population comprised a retrospective cohort of patients with MPN who underwent transthoracic echocardiography: Doppler-derived pulmonary arterial systolic pressure applied established cutoffs for PH (≥35 mm Hg) and advanced PH (≥50 mm Hg); right ventricular (RV) performance was assessed via conventional indices (tricuspid annular plane systolic excursion [TAPSE], S') and global longitudinal strain. Symptoms and mortality were discerned via standardized review. RESULTS: Three hundred one patients were studied; 56% had echocardiography-demonstrated PH (20% advanced) paralleling a high prevalence (67%) among patients with invasively quantified PASP. PH was associated with adverse left ventricular (LV) remodeling indices, including increased myocardial mass and diastolic dysfunction (P ≤ .001 for all): LV mass and filling pressure (P < .01) were associated with PH independent of LV ejection fraction. RV dysfunction by strain and TAPSE and S' increased in relation to PH (P ≤ .001) and was about threefold greater among patients with advanced PH compared with those without PH. Patients with RV dysfunction were more likely to report dyspnea, as were those with advanced PH (P < .05). During median follow-up of 2.2 years, all-cause mortality was 27%. PH grade (hazard ratio, 1.9; 95% CI, 1.1-3.0; P = .012) and TAPSE- and S'-demonstrated RV dysfunction (hazard ratio, 3.3; 95% CI, 1.3-8.2; P = .01) were independently associated with mortality; substitution of global longitudinal strain for TAPSE and S' yielded similar associations of RV dysfunction with death (hazard ratio, 3.2; 95% CI, 1.5-6.7; P = .003) independent of PH. CONCLUSIONS: PH is highly prevalent in patients with MPN and is linked to LV diastolic dysfunction; echocardiography-quantified RV dysfunction augments risk for mortality independent of PH.

Echocardiographic predictors of intraoperative right ventricular dysfunction: a 2D and speckle tracking echocardiography study.

BACKGROUND: Intraoperative or post procedure right ventricular (RV) dysfunction confers a poor prognosis in the post-operative period. Conventional predictors for RV function are limited due the effect of cardiac surgery on traditional RV indices; novel echocardiographic techniques hold the promise to improve RV functional stratification. METHODS: Comprehensive echocardiographic data were collected prospectively during elective cardiac surgery. Tricuspid annular plane systolic excursion (TAPSE), peak RV systolic velocity (S'), and RV fractional area change (FAC) were quantified on transesophageal echo (TEE). RV global and regional (septal and free wall) longitudinal strain was quantified using speckle-tracking echo in RV-focused views. Two intraoperative time points were used for comparison: pre-sternotomy (baseline) and after chest closure. RESULTS: The population was comprised of 53 patients undergoing cardiac surgery [15.1% coronary artery bypass graft (CABG) only, 28.3% valve only, 50.9% combination (e.g. valve/CABG, valve/aortic graft) surgeries], among whom 38% had impaired RV function at baseline defined as RV FAC < 35%. All conventional RV functional indices including TAPSE, S' and FAC declined immediately following CPB (1.5 ± 0.3 vs.1.1 ± 0.3 cm, 8.0 ± 2.1 vs. 6.2 ± 2.5 cm/s, 36.8 ± 9.3 vs. 29.3 ± 10.6%; p < 0.001 for all). However, left ventricular (LV) and RV hemodynamic parameters remained unchanged (LV ejection fraction (EF): 56.8 ± 13.0 vs. 55.8 ± 12.9%; p = 0.40, pulmonary artery systolic pressure (PASP): 26.5 ± 7.4 vs 27.3 ± 6.7 mmHg; p = 0.13). Speckle tracking echocardiographic data demonstrated a significant decline in RV global longitudinal strain (GLS) [19.0 ± 6.5 vs. 13.5 ± 6.9%, p < 0.001]. Pre-procedure FAC, GLS and free wall strain predicted RV dysfunction at chest closure (34.7 ± 9.1 vs. 41.6 ± 8.1%, p = 0.01, 17.7 ± 6.5 vs. 21.8 ± 5.4%; p = 0.03, 20.3 ± 6.4 vs. 24.2 ± 5.8%; p = 0.04), whereas traditional linear RV indices such as TAPSE and RV S' at baseline had no impact on intraoperative RV dysfunction (p = NS for both). CONCLUSIONS: Global and regional RV function, as measured by 2D indices and strain, acutely decline intraoperatively. Impaired RV strain is associated with intraoperative RV functional decline and provides incremental value to traditional RV indices in predicting those who will develop RV dysfunction.

Left ventricular geometry predicts optimal response to percutaneous mitral repair via MitraClip: Integrated assessment by two- and three-dimensional echocardiography.

OBJECTIVES: To assess impact of left ventricular (LV) chamber remodeling on MitraClip (MClp) response. BACKGROUND: MitraClip is the sole percutaneous therapy approved for mitral regurgitation (MR) but response varies. LV dilation affects mitral coaptation; determinants of MClp response are uncertain. METHODS: LV and mitral geometry were quantified on pre- and post-procedure two-dimensional (2D) transthoracic echocardiography (TTE) and intra-procedural three-dimensional (3D) transesophageal echocardiography (TEE). Optimal MClp response was defined as ≤mild MR at early (1-6 month) follow-up. RESULTS: Sixty-seven degenerative MR patients underwent MClp: Whereas MR decreased ≥1 grade in 94%, 39% of patients had optimal response (≤mild MR). Responders had smaller pre-procedural LV end-diastolic volume (94 ± 24 vs. 109 ± 25 mL/m2 , p = 0.02), paralleling smaller annular diameter (3.1 ± 0.4 vs. 3.5 ± 0.5 cm, p = 0.002), and inter-papillary distance (2.2 ± 0.7 vs. 2.5 ± 0.6 cm, p = 0.04). 3D TEE-derived annular area correlated with 2D TTE (r = 0.59, p < 0.001) and was smaller among optimal responders (12.8 ± 2.1 cm2 vs. 16.8 ± 4.4 cm2 , p = 0.001). Both 2D and 3D mitral annular size yielded good diagnostic performance for optimal MClp response (AUC 0.73-0.84, p < 0.01). In multivariate analysis, sub-optimal MClp response was associated with LV end-diastolic diameter (OR 3.10 per-cm [1.26-7.62], p = 0.01) independent of LA size (1.10 per-cm2 [1.02-1.19], p = 0.01); substitution of mitral annular diameter for LV size yielded an independent association with MClp response (4.06 per-cm2 [1.03-15.96], p = 0.045). CONCLUSIONS: Among degenerative MR patients undergoing MClp, LV and mitral annular dilation augment risk for residual or recurrent MR, supporting the concept that MClp therapeutic response is linked to sub-valvular remodeling.

Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantification.

BACKGROUND: Phase contrast (PC) cardiovascular magnetic resonance (CMR) is widely employed for flow quantification, but analysis typically requires time consuming manual segmentation which can require human correction. Advances in machine learning have markedly improved automated processing, but have yet to be applied to PC-CMR. This study tested a novel machine learning model for fully automated analysis of PC-CMR aortic flow. METHODS: A machine learning model was designed to track aortic valve borders based on neural network approaches. The model was trained in a derivation cohort encompassing 150 patients who underwent clinical PC-CMR then compared to manual and commercially-available automated segmentation in a prospective validation cohort. Further validation testing was performed in an external cohort acquired from a different site/CMR vendor. RESULTS: Among 190 coronary artery disease patients prospectively undergoing CMR on commercial scanners (84% 1.5T, 16% 3T), machine learning segmentation was uniformly successful, requiring no human intervention: Segmentation time was < 0.01 min/case (1.2 min for entire dataset); manual segmentation required 3.96 ± 0.36 min/case (12.5 h for entire dataset). Correlations between machine learning and manual segmentation-derived flow approached unity (r = 0.99, p < 0.001). Machine learning yielded smaller absolute differences with manual segmentation than did commercial automation (1.85 ± 1.80 vs. 3.33 ± 3.18 mL, p < 0.01): Nearly all (98%) of cases differed by ≤5 mL between machine learning and manual methods. Among patients without advanced mitral regurgitation, machine learning correlated well (r = 0.63, p < 0.001) and yielded small differences with cine-CMR stroke volume (∆ 1.3 ± 17.7 mL, p = 0.36). Among advanced mitral regurgitation patients, machine learning yielded lower stroke volume than did volumetric cine-CMR (∆ 12.6 ± 20.9 mL, p = 0.005), further supporting validity of this method. Among the external validation cohort (n = 80) acquired using a different CMR vendor, the algorithm yielded equivalently small differences (∆ 1.39 ± 1.77 mL, p = 0.4) and high correlations (r = 0.99, p < 0.001) with manual segmentation, including similar results in 20 patients with bicuspid or stenotic aortic valve pathology (∆ 1.71 ± 2.25 mL, p = 0.25). CONCLUSION: Fully automated machine learning PC-CMR segmentation performs robustly for aortic flow quantification - yielding rapid segmentation, small differences with manual segmentation, and identification of differential forward/left ventricular volumetric stroke volume in context of concomitant mitral regurgitation. Findings support use of machine learning for analysis of large scale CMR datasets.

Experimental quantification of the fluid dynamics in blood-processing devices through 4D-flow imaging: A pilot study on a real oxygenator/heat-exchanger module.

The performance of blood-processing devices largely depends on the associated fluid dynamics, which hence represents a key aspect in their design and optimization. To this aim, two approaches are currently adopted: computational fluid-dynamics, which yields highly resolved three-dimensional data but relies on simplifying assumptions, and in vitro experiments, which typically involve the direct video-acquisition of the flow field and provide 2D data only. We propose a novel method that exploits space- and time-resolved magnetic resonance imaging (4D-flow) to quantify the complex 3D flow field in blood-processing devices and to overcome these limitations. We tested our method on a real device that integrates an oxygenator and a heat exchanger. A dedicated mock loop was implemented, and novel 4D-flow sequences with sub-millimetric spatial resolution and region-dependent velocity encodings were defined. Automated in house software was developed to quantify the complex 3D flow field within the different regions of the device: region-dependent flow rates, pressure drops, paths of the working fluid and wall shear stresses were computed. Our analysis highlighted the effects of fine geometrical features of the device on the local fluid-dynamics, which would be unlikely observed by current in vitro approaches. Also, the effects of non-idealities on the flow field distribution were captured, thanks to the absence of the simplifying assumptions that typically characterize numerical models. To the best of our knowledge, our approach is the first of its kind and could be extended to the analysis of a broad range of clinically relevant devices.