Implicit Neural Representations for Modeling of Abdominal Aortic Aneurysm Progression

Abdominal aortic aneurysms (AAAs) are progressive dilatations of the abdominal aorta that, if left untreated, can rupture with lethal consequences. Imaging-based patient monitoring is required to select patients eligible for surgical repair. In this work, we present a model based on implicit neural representations (INRs) to model AAA progression. We represent the AAA wall over time as the zero-level set of a signed distance function (SDF), estimated by a multilayer perception that operates on space and time. We optimize this INR using automatically extracted segmentation masks in longitudinal CT data. This network is conditioned on spatiotemporal coordinates and represents the AAA surface at any desired resolution at any moment in time. Using regularization on spatial and temporal gradients of the SDF, we ensure proper interpolation of the AAA shape. We demonstrate the network’s ability to produce AAA interpolations with average surface distances ranging between 0.72 and 2.52 mm from images acquired at highly irregular intervals. The results indicate that our model can accurately interpolate AAA shapes over time, with potential clinical value for a more personalised assessment of AAA progression.</p

Global Control for Local SO(3)-Equivariant Scale-Invariant Vessel Segmentation

Personalized 3D vascular models can aid in a range of diagnostic, prognostic, and treatment-planning tasks relevant to cardiovascular disease management. Deep learning provides a means to automatically obtain such models. Ideally, a user should have control over the exact region of interest (ROI) to be included in a vascular model, and the model should be watertight and highly accurate. To this end, we propose a combination of a global controller leveraging voxel mask segmentations to provide boundary conditions for vessels of interest to a local, iterative vessel segmentation model. We introduce the preservation of scale- and rotational symmetries in the local segmentation model, leading to generalisation to vessels of unseen sizes and orientations. Combined with the global controller, this enables flexible 3D vascular model building, without additional retraining. We demonstrate the potential of our method on a dataset containing abdominal aortic aneurysms (AAAs). Our method performs on par with a state-of-the-art segmentation model in the segmentation of AAAs, iliac arteries and renal arteries, while providing a watertight, smooth surface segmentation. Moreover, we demonstrate that by adapting the global controller, we can easily extend vessel sections in the 3D model

Going Off-Grid: Implicit Neural Representations for 3D Vascular Modeling

Personalised 3D vascular models are valuable for diagnosis, prognosis and treatment planning in patients with cardiovascular disease. Traditionally, such models have been constructed with explicit representations such as meshes and voxel masks, or implicit representations such as radial basis functions or atomic (tubular) shapes. Here, we propose to represent surfaces by the zero level set of their signed distance function (SDF) in a differentiable implicit neural representation (INR). This allows us to model complex vascular structures with a representation that is implicit, continuous, light-weight, and easy to integrate with deep learning algorithms. We here demonstrate the potential of this approach with three practical examples. First, we obtain an accurate and watertight surface for an abdominal aortic aneurysm (AAA) from CT images and show robust fitting from as little as 200 points on the surface. Second, we simultaneously fit nested vessel walls in a single INR without intersections. Third, we show how 3D models of individual arteries can be smoothly blended into a single watertight surface. Our results show that INRs are a flexible representation with potential for minimally interactive annotation and manipulation of complex vascular structures.Comment: MICCAI STACOM 202

Going Off-Grid: Continuous Implicit Neural Representations for 3D Vascular Modeling

Personalised 3D vascular models are valuable for diagnosis, prognosis and treatment planning in patients with cardiovascular disease. Traditionally, such models have been constructed with explicit representations such as meshes and voxel masks, or implicit representations such as radial basis functions or atomic (tubular) shapes. Here, we propose to represent surfaces by the zero level set of their signed distance function (SDF) in a differentiable implicit neural representation (INR). This allows us to model complex vascular structures with a representation that is implicit, continuous, light-weight, and easy to integrate with deep learning algorithms. We here demonstrate the potential of this approach with three practical examples. First, we obtain an accurate and watertight surface for an abdominal aortic aneurysm (AAA) from CT images and show robust fitting from as little as 200 points on the surface. Second, we simultaneously fit nested vessel walls in a single INR without intersections. Third, we show how 3D models of individual arteries can be smoothly blended into a single watertight surface. Our results show that INRs are a flexible representation with potential for minimally interactive annotation and manipulation of complex vascular structures

Image Fusion During Endovascular Aneurysm Repair, how to Fuse? An Overview of Registration and Implementation Strategies Plus Tips and Tricks

Introduction: The use of image fusion in the hybrid operating room is increasingly used. Image fusion enables physicians to deploy endovascular devices with a 3D roadmap of the vascular anatomy based on preoperative CTA or MRA. Previous studies described a decrease in nephrotoxic contrast volume, fluoroscopy time, radiation dose and procedure time in complex endovascular aortic repair (EVAR).1-4 However, there is no general consensus or guideline on the optimal technique and timing of image fusion. There are several options; 2D-3D bony landmark registration, 3D-3D aortic calcification registration, contrast enhanced cone beam CT (ceCBCT) registration. Moreover, registration can be done before or after the insertion of sheaths and (stiff) guidewires. The goal of this study was to determine image fusion accuracy. Methods: Several fusion strategies were analyzed. Strategy 1: 2D-3D registration before insertion of sheaths and guidewires. Strategy 2: 3D-3D registration before insertion of sheaths and guidewires. Strategy 3: 2D-3D registration after insertion of sheaths and guidewires. Strategy 4: 3D-3D registration after insertion of sheaths and guidewires. An overview is displayed in Figure 1A-1D. Strategy 1 was evaluated with clinical patient data. Strategies 2, 3 and 4 were evaluated with an infrarenal AAA phantom model with pelvis, vertebral column and renal calcifications as displayed in Figure 1E. For strategy 1, in total 11 EVAR patients (median age 75.5, all male) were included of which 4 were complex EVAR (fenestrated) and 7 standard EVAR. In all patients, digital subtraction angiography (DSA) was used as roadmap to deploy the devices. After DSA, manual correction was performed to correct fusion overlay to match the lowest renal artery between image fusion and DSA. Registration accuracy was determined by ostium displacement (in millimeters) of the lowest renal artery (proximal accuracy) and ostium displacement of the right and left internal iliac arteries (distal accuracy), when compared to the intra-operative DSA images (see Figure 1A & 1F). Proximal accuracy was measured before and after DSA correction. Displacement accuracy was defined as follows; accurate (0-1 mm), medium (1-4 mm) and poor (>4 mm). Tips are to register with vertebral L1/L2 centered and to correct navigation markers in axial CT-view to prevent misplacement due to ostia calcification, as displayed in Figure 1 G-H. Results: For the 11 patients the mean proximal accuracy was 0.7 (0.4-0.9) mm and distal accuracy was 5.8 (1.3-12.3) mm compared to the DSA. Before DSA correction proximal accuracy was 7.4 (1.4-11) mm. With phantom data, proximal accuracy was 0.8 (0.5-1.1) mm and distal accuracy was 2.3 (0.6-1.2) mm for strategy 2. Strategy 3 resulted in a proximal accuracy of 2.6 (1.9-3.4) mm and distal accuracy of 14.0 (13.0-15.0) mm. Strategy 4 resulted in a proximal accuracy of 1.6 (1.5-1.8) mm and distal accuracy of 4.0 (2.0- 5.9) mm. See Table 1 for an overview. Conclusion: Based on this data, image fusion proximal accuracy is equal with 2D-3D and 3D-3D registration before sheath and guidewire insertion. Manual DSA correction for 2D-3D registration is required to improve accuracy. After the insertion of guidewires, the accuracy of 3D-3D registration is superior to 2D-3D registration

Long-Term Outcomes of Nonoperative and Surgical Management of Paget-Schroetter Syndrome

Purpose: In Paget-Schroetter Syndrome (PSS), subclavian vein thrombosis is caused by external compression of the subclavian vein at the costoclavicular junction. Paget-Schroetter Syndrome can be treated nonoperatively, surgically, or with a combination of treatments. Nonoperative management consists, in most cases, of anticoagulation (AC) or catheter-directed thrombolysis (CDT). With surgical management, decompression of the subclavian vein is performed by resection of the first rib. No prospective randomized trials are available to determine whether nonoperative or surgical management is superior. We report our long-term outcomes of both nonoperative and surgically treated patients. Materials and Methods: We retrospectively analyzed all patients with PSS who were treated between January 1990 and December 2015. Patients were divided based on primary nonoperative or primary surgical therapy. Long-term outcomes regarding functional outcomes were assessed by questionnaires using the “Disability of the Arm, Shoulder, and Hand” (DASH) questionnaire, a modified Villalta score, and a disease-specific question regarding lifestyle changes. Results: In total, 91 patients (95 limbs) were included. Seventy patients (73 limbs) were treated nonoperatively and 21 patients (22 limbs) surgically. Questionnaires were returned by 67 patients (70 limbs). The mean follow-up was 184 months (range, 43–459 months). All functional outcomes were better in the surgical group compared with the nonoperatively treated group (DASH general 3.11 vs 9.86; DASH work 0.35 vs 11.47; DASH sport 5.85 vs 17.98, and modified Villalta score 1.11 vs 3.20 points). Surgically treated patients were more likely to be able to continue their original lifestyle and sports activities (84% vs 40%, p=0.005). Patients with recurrence of thrombosis or the need for surgical intervention after primary nonoperative management reported worse functional outcomes. Conclusion: Surgical management of PSS with immediate CDT followed by first rib resection leads to excellent functional outcomes with low risk of complications. The results of nonoperative management in our non-matched retrospective comparative series were satisfactory, but resulted in worse functional outcomes and more patients needing to adjust their lifestyle compared with surgically treated patients. Clinical Impact: Patients with Paget-Schroetter Syndrome and their attending physicians are burdened by the lack of evidence concerning the optimal treatment of this entity. Case series comparing the outcomes of non-operative treatment with surgical treatment are scarce and often not focussed on functional outcomes. Data from this series can aid in the shared decision making after diagnosis of Paget-Schroetter Syndrome. Functional outcomes of non-operative management can be satisfying although high demand patient who are not willing to alter their daily activities are probably better off with surgical management

A Standardized Bolus of 5 000 IU of Heparin Does not Lead to Adequate Heparinization during Non-cardiac Arterial Procedures

Background: In non-cardiac arterial procedures (NCAP), heparin is administered to prevent arterial thromboembolic complications (ATEC). Heparin has a nonpredictable effect in the individual patient, also known as variation in heparin sensitivity. Various dosing protocols are in use, but the optimal dose is currently still unknown. A standardized bolus of 5 000 IU heparin is most frequently used by vascular surgeons and interventional radiologists. The activated clotting time (ACT) is an established method to measure the level of anticoagulation, but has, until now, not gained widespread use in NCAP. The purpose of this study was to evaluate the anticoagulant effect during NCAP of a standardized bolus of 5 000 IU heparin by measuring the ACT. Methods: In this prospective study, 190 patients undergoing NCAP were enrolled between December 2016 and September 2018. The ACT was measured during open and endovascular/hybrid procedures. All patients received a standardized bolus of 5 000 IU heparin. The ACT was measured by the Hemostasis Management System Plus (HMS Plus, Medtronic®), before, 5 minutes after administration of heparin, and every 30 minutes thereafter. The primary outcome was periprocedural ACT values measured. Secondary outcomes were ATEC and hemorrhagic complications. Results: A large individual patient variability in the response to heparin was found. The mean baseline ACT in all patients was 129 ± 18 s., and the mean ACT 5 minutes after the initial bolus of heparin was 191 ± 36 s. After the initial dose of 5 000 IU heparin 60 (33%) and 10 (6%) patients reached an ACT of 200 and 250 s., respectively. Despite the use of heparin, ATEC occurred in 17 patients (9%). The lowest number of ATEC occurred in the group of patients with an ACT between 200 and 250 s. Conclusions: A standardized bolus of 5 000 IU heparin does not lead to adequate and safe heparinization in non-cardiac arterial procedures. Patient response to heparin shows a large individual variability. Therefore, routine ACT measurements are necessary to ascertain adequate anticoagulation. Further research is needed to investigate if heparin dosing based on the ACT could result in less arterial thromboembolic complications, without increasing hemorrhagic complications

A Novel Hypothesis: A Role for Follicle Stimulating Hormone in Abdominal Aortic Aneurysm Development in Postmenopausal Women

An abdominal aortic aneurysm (AAA) is a dilatation of the abdominal aorta, which can potentially be fatal due to exsanguination following rupture. Although AAA is less prevalent in women, women with AAA have a more severe AAA progression compared to men as reflected by enhanced aneurysm growth rates and a higher rupture risk. Women are diagnosed with AAA at an older age than men, and in line with increased osteoporosis and cardiovascular events, the delayed AAA onset has been attributed to the reduction of the protective effect of oestrogens during the menopausal transition. However, new insights have shown that a high follicle stimulating hormone (FSH) level during menopause may also play a key role in those diseases. In this report we hypothesize that FSH may aggravate AAA development and progression in postmenopausal women via a direct and/or indirect role, promoting aorta pathology. Since FSH receptors (FSHR) are reported on many other cell types than granulosa cells in the ovaries, it is feasible that FSH stimulation of FSHR-bearing cells such as aortic endothelial cells or inflammatory cells, could promote AAA formation directly. Indirectly, AAA progression may be influenced by an FSH-mediated increase in osteoporosis, which is associated with aortic calcification. Also, an FSH-mediated decrease in cholesterol uptake by the liver and an increase in cholesterol biosynthesis will increase the cholesterol level in the circulation, and subsequently promote aortic atherosclerosis and inflammation. Lastly, FSH-induced adipogenesis may lead to obesity-mediated dysfunction of the microvasculature of the aorta and/or modulation of the periaortic adipose tissue. Thus the long term increased plasma FSH levels during the menopausal transition may contribute to enhanced AAA disease in menopausal women and could be a potential novel target for treatment to lower AAA-related events in women