Thermal Ablation of Liver Tumors Guided by Augmented Reality: An Initial Clinical Experience.

Background: Over the last two decades, augmented reality (AR) has been used as a visualization tool in many medical fields in order to increase precision, limit the radiation dose, and decrease the variability among operators. Here, we report the first in vivo study of a novel AR system for the guidance of percutaneous interventional oncology procedures. Methods: Eight patients with 15 liver tumors (0.7−3.0 cm, mean 1.56 + 0.55) underwent percutaneous thermal ablations using AR guidance (i.e., the Endosight system). Prior to the intervention, the patients were evaluated with US and CT. The targeted nodules were segmented and three-dimensionally (3D) reconstructed from CT images, and the probe trajectory to the target was defined. The procedures were guided solely by AR, with the position of the probe tip was subsequently confirmed by conventional imaging. The primary endpoints were the targeting accuracy, the system setup time, and targeting time (i.e., from the target visualization to the correct needle insertion). The technical success was also evaluated and validated by co-registration software. Upon completion, the operators were assessed for cybersickness or other symptoms related to the use of AR. Results: Rapid system setup and procedural targeting times were noted (mean 14.3 min; 12.0−17.2 min; 4.3 min, 3.2−5.7 min, mean, respectively). The high targeting accuracy (3.4 mm; 2.6−4.2 mm, mean) was accompanied by technical success in all 15 lesions (i.e., the complete ablation of the tumor and 13/15 lesions with a >90% 5-mm periablational margin). No intra/periprocedural complications or operator cybersickness were observed. Conclusions: AR guidance is highly accurate, and allows for the confident performance of percutaneous thermal ablations.

A novel software platform for volumetric assessment of ablation completeness.

PURPOSE: To retrospectively evaluate the accuracy of a novel software platform for assessing completeness of percutaneous thermal ablations. MATERIALS & METHODS: Ninety hepatocellular carcinomas (HCCs) in 50 patients receiving percutaneous ultrasound-guided microwave ablation (MWA) that resulted in apparent technical success at 24-h post-ablation computed tomography (CT) and with ≥1-year imaging follow-up were randomly selected from a 320 HCC ablation database (2010-2016). Using a novel volumetric registration software, pre-ablation CT volumes of the HCCs without and with the addition of a 5 mm safety margin, and corresponding post-ablation necrosis volumes were segmented, co-registered and overlapped. These were compared to visual side-by-side inspection of axial images. RESULTS: At 1-year follow-up, CT showed absence of local tumor progression (LTP) in 69/90 (76.7%) cases and LTP in 21/90 (23.3%). For HCCs classified by the software as "incomplete tumor treatments", LTP developed in 13/17 (76.5%) and all 13 (100%) of these LTPs occurred exactly where residual non-ablated tumor was identified by retrospective software analysis. HCCs classified as "complete ablation with <100% 5 mm ablative margins" had LTP in 8/49 (16.3%), while none of 24 HCCs with "complete ablation including 100% 5 mm ablative margins" had LTP. Differences in LTP between both partially ablated HCCs vs completely ablated HCCs, and ablated HCCs with <100% vs with 100% 5 mm margins were statistically significant (p < .0001 and p = .036, respectively). Thus, 13/21 (61.9%) incomplete tumor treatments could have been detected immediately, were the software available at the time of ablation. CONCLUSIONS: A novel software platform for volumetric assessment of ablation completeness may increase the detection of incompletely ablated tumors, thereby holding the potential to avoid subsequent recurrences.

Augmented reality for interventional oncology: proof-of-concept study of a novel high-end guidance system platform.

BACKGROUND: To assess the feasibility of a novel system that uses augmented reality to guide interventional oncology procedures. METHODS: This study was conducted in accordance to the guidelines of the local institutional review boards. Evaluation of an augmented reality system based upon a tablet, a needle handle and a set of markers was performed in three experimental models. Initially, a male anthropomorphic trunk phantom equipped with five polyvinyl chloride bars (two of 16 cm in length and 3 cm in diameter and four of 45, 30 or 20 cm in length and 2 cm in diameter) was used to study the accuracy of the system without respiratory motion or tissue compression. Next, small metallic targets were placed in a porcine model to evaluate how respiration affects the system accuracy. Finally, the performance of the system on a more complete model, a cadaver with liver metastasis, was tested. RESULTS: In all experimental settings, extremely high targeting accuracy of < 5 mm in all cases was achieved: 2.0 ± 1.5 mm (mean ± standard deviation) for the anthropomorphic model, 3.9 ± 0.4 mm for the porcine model, and 2.5 mm and 2.8 mm for the two metastases in the cadaver model. CONCLUSIONS: Augmented reality can assist with needle guidance with great target accuracy for interventional procedures by simultaneously visualising three-dimensional reconstructed anatomical structures, tumour targets and interventional devices on a patient's body, enabling performance of procedures in a simple and confident way.

A Novel CT to Cone-Beam CT Registration Method Enables Immediate Real-Time Intraprocedural Three-Dimensional Assessment of Ablative Treatments of Liver Malignancies.

AIM: To evaluate a novel contrast-enhanced cone-beam computed tomography (CE-CBCT) registration method for accurate immediate assessment of ablation outcomes. MATERIALS AND METHODS: Contrast-enhanced computed tomography (CECT) was registered with CE-CBCT by applying semiautomatic landmark registration followed by automatic affine and non-rigid registration to correct for respiratory phase differences and liver deformation. This scheme was retrospectively applied to 30 patients who underwent 38 percutaneous microwave liver ablations. Three datasets were obtained for each case: (1) conventional CECT scans 24 h before ablation, (2) intraprocedural CE-CBCT scans, and (3) CECT scans 24 h post-ablation. Using a five-point scale, two experienced radiologists qualitatively assessed registration quality, equivalence of CE-CBCT assessment of ablation outcome to 24 h post-ablation CECT, and perceived increase of confidence using the fusion method to CBCT alone. Additionally, residual post-ablation tumor volumes were measured at both CE-CBCT and 24 h CECT and compared to the pre-CECT. RESULTS: Registration quality was high for both radiologists (R1: 4.3 ± 0.6, R2: 4.4 ± 0.5; p = 0.87). Comparisons between the registration of pre-ablation CECT with CE-CBCT versus post-ablation CECT regarding the position of the ablated area to the treated target (R1: 4.4 ± 0.6, R2: 4.6 ± 0.4) and treatment outcome (R1: 4.5 ± 0.5, R2: 4.6 ± 0.4) were equivalent (p > 0.35). Increased confidence was noted when using fusion (R1: 4.6 ± 0.4, R2: 4.6 ± 0.4; p = 0.84). Moreover, in 6 ablations (15.8%) the intraprocedural registered CBCT showed residual tumor precisely where identified on the 24 h post-ablation CECT. CONCLUSIONS: Combined CE-CBCT holds the potential to change the current workflow of mini-invasive cancer local treatments. Given earlier visual identification of residual tumor post-ablation, this includes potentially eliminating the need for some additional treatments.

Computational model for simulation of vascular adaptation following vascular access surgery in haemodialysis patients.

An important number of surgical procedures for creation of vascular access (VA) in haemodialysis patients still results in non-adequate increase in blood flow (non-maturation). The rise in blood flow in arteriovenous shunts depends on vascular remodelling. Computational tools to predict the outcome of VA surgery would be important in this clinical context. The aim of our investigation was then to develop a 0D/1D computational model of arm vasculature able to simulate vessel wall remodelling and related changes in blood flow. We assumed that blood vessel remodelling is driven by peak wall shear stress. The model was calibrated with previously reported values of radial artery diameter and blood flow after end-to-end distal fistula creation. Good agreement was obtained between predicted changes in VA flow and in arterial diameter after surgery and corresponding measured values. The use of this computational model may allow accurate vascular surgery planning and ameliorate VA surgery outcomes.

Validation of a patient-specific hemodynamic computational model for surgical planning of vascular access in hemodialysis patients.

Vascular access dysfunction is one of the main causes of morbidity and hospitalization in hemodialysis patients. This major clinical problem points out the need for prediction of hemodynamic changes induced by vascular access surgery. Here we reviewed the potential of a patient-specific computational vascular network model that includes vessel wall remodeling to predict blood flow change within 6 weeks after surgery for different arteriovenous fistula configurations. For model validation, we performed a multicenter, prospective clinical study to collect longitudinal data on arm vasculature before and after surgery. Sixty-three patients with newly created arteriovenous fistula were included in the validation data set and divided into four groups based on fistula configuration. Predicted brachial artery blood flow volumes 40 days after surgery had a significantly high correlation with measured values. Deviation of predicted from measured brachial artery blood flow averaged 3% with a root mean squared error of 19.5%, showing that the computational tool reliably predicted patient-specific blood flow increase resulting from vascular access surgery and subsequent vascular adaptation. This innovative approach may help the surgeon to plan the most appropriate fistula configuration to optimize access blood flow for hemodialysis, potentially reducing the incidence of vascular access dysfunctions and the need of patient hospitalization.

Radiofrequency ablation of liver tumors: quantitative assessment of tumor coverage through CT image processing.

BACKGROUND: Radiofrequency ablation (RFA) is one of the most promising non-surgical treatments for hepatic tumors. The assessment of the therapeutic efficacy of RFA is usually obtained by visual comparison of pre- and post-treatment CT images, but no numerical quantification is performed. METHODS: In this work, a novel method aiming at providing a more objective tool for the evaluation of RFA coverage is described. Image registration and segmentation techniques were applied to enable the visualization of the tumor and the corresponding post-RFA necrosis in the same framework. In addition, a set of numerical indexes describing tumor/necrosis overlap and their mutual position were computed. RESULTS: After validation of segmentation step, the method was applied on a dataset composed by 10 tumors, suspected not to be completed treated. Numerical indexes showed that only two tumors were totally treated and the percentage of a residual tumor was in the range of 5.12%-35.92%. CONCLUSIONS: This work represents a first attempt to obtain a quantitative tool aimed to assess the accuracy of RFA treatment. The possibility to visualize the tumor and the correspondent post-RFA necrosis in the same framework and the definition of some synthetic numerical indexes could help clinicians in ameliorating RFA treatment.

Patient-specific model of arterial circulation for surgical planning of vascular access.

PURPOSE: To report the technical aspects of a novel method to generate patient-specific vascular network models of arterial vasculature for the surgical planning of vascular access (VA) for hemodialysis. METHODS: On the basis of literature data, we defined a set of rules for estimation of diameter, length and compliance of arterial network segments, at patient-specific level, as a function of general descriptors (i.e. sex, age, body size and pathology). Using this method we generated vascular network models of height hypothetical patients with different age, sex and body surface area and we computed pressures and blood flows along the arterial arm vasculature using a wave propagation model. RESULTS: Simulation results show that vascular geometry is influenced by sex, age and body size leading to important differences in hemodynamic function. Calculated wall shear stress is higher in women females as compared to men, regardless of body size and age. CONCLUSIONS: Our method facilitates estimating vascular network model parameters useful for patient-specific pre-operative assessment of blood flow distribution in the arterial arm circulation.

A method for morphological characterization of dural ectasia in Marfan syndrome.

In this paper we reported a novel method to detect and quantify dural ectasia in Marfan syndrome. Firstly, the dural sacs of 8 Marfan patients were segmented by applying an unsupervised Fuzzy C-Means method on T2-weighed magnetic resonance images. Then, for each patient a tubular model of the dural sac was extracted by detecting and removing the existent pathological extrusions. The segmented images together with the resulting tube were then rendered using a marching cubes algorithm. The proposed algorithm represents a first attempt to quantify and to morphologically characterize the pathological ectasia that usually accompanies the Marfan disorder. The generated 3D reconstruction and the opportunity to overlap them with a physiological model provides the clinician with a tool for a panoramic view of the structures and a means for a more accurate inspection of ectasia. In addition the extracted parameters furnish quantitative and reproducible measures that could be useful as discriminative indexes for an automatic and more objective diagnosis.

ITAC volume assessment through a Gaussian hidden Markov random field model-based algorithm.

In this paper, a semi-automatic segmentation method for volume assessment of Intestinal-type adenocarcinoma (ITAC) is presented and validated. The method is based on a Gaussian hidden Markov random field (GHMRF) model that represents an advanced version of a finite Gaussian mixture (FGM) model as it encodes spatial information through the mutual influences of neighboring sites. To fit the GHMRF model an expectation maximization (EM) algorithm is used. We applied the method to a magnetic resonance data sets (each of them composed by T1-weighted, Contrast Enhanced T1-weighted and T2-weighted images) for a total of 49 tumor-contained slices. We tested GHMRF performances with respect to FGM by both a numerical and a clinical evaluation. Results show that the proposed method has a higher accuracy in quantifying lesion area than FGM and it can be applied in the evaluation of tumor response to therapy.

Improved detection of liver metastasis by registration and subtraction of dynamic contrast-enhanced magnetic resonance imaging.

The purpose of this work was to validate a subtraction method for dynamic contrast-enhanced magnetic resonance volumes acquired at portal and delayed (3 hours) phases, to obtain a better depiction and delineation of hepatic secondary lesions. As the clinical readability of subtraction images depends on the degree of co-registration between volumes, we applied a 3D non-rigid registration procedure to realign portal and delayed-phase volumes before subtraction. Our method combines a rigid registration, based on Normalized Mutual Information maximization and a non-rigid registration, based on a multiresolution analysis performed through Wavelet Transform. The feasibility of the method was tested on thirty-five secondary lesions. Results showed that the proposed subtraction produces images of easy interpretation and improves diagnostic confidence. In particular, subtraction image of subcentimetric lesions was scored as diagnostic in the 89% of the cases.

A method for dynamic subtraction MR imaging of the liver.

BACKGROUND: Subtraction of Dynamic Contrast-Enhanced 3D Magnetic Resonance (DCE-MR) volumes can result in images that depict and accurately characterize a variety of liver lesions. However, the diagnostic utility of subtraction images depends on the extent of co-registration between non-enhanced and enhanced volumes. Movement of liver structures during acquisition must be corrected prior to subtraction. Currently available methods are computer intensive. We report a new method for the dynamic subtraction of MR liver images that does not require excessive computer time. METHODS: Nineteen consecutive patients (median age 45 years; range 37-67) were evaluated by VIBE T1-weighted sequences (TR 5.2 ms, TE 2.6 ms, flip angle 20 degrees , slice thickness 1.5 mm) acquired before and 45s after contrast injection. Acquisition parameters were optimized for best portal system enhancement. Pre and post-contrast liver volumes were realigned using our 3D registration method which combines: (a) rigid 3D translation using maximization of normalized mutual information (NMI), and (b) fast 2D non-rigid registration which employs a complex discrete wavelet transform algorithm to maximize pixel phase correlation and perform multiresolution analysis. Registration performance was assessed quantitatively by NMI. RESULTS: The new registration procedure was able to realign liver structures in all 19 patients. NMI increased by about 8% after rigid registration (native vs. rigid registration 0.073 +/- 0.031 vs. 0.078 +/- 0.031, n.s., paired t-test) and by a further 23% (0.096 +/- 0.035 vs. 0.078 +/- 0.031, p < 0.001, paired t-test) after non-rigid realignment. The overall average NMI increase was 31%. CONCLUSION: This new method for realigning dynamic contrast-enhanced 3D MR volumes of liver leads to subtraction images that enhance diagnostic possibilities for liver lesions.