A novel use of biomechanical model-based deformable image registration (DIR) for assessing colorectal liver metastases ablation outcomes

Using Patient-Specific 3D Modeling and Simulations to Optimize Microwave Ablation Therapy for Liver Cancer

Microwave ablation (MWA) of liver tumors presents challenges like under- and over-ablation, potentially leading to inadequate tumor destruction and damage to healthy tissue. This study aims to develop personalized three-dimensional (3D) models to simulate MWA for liver tumors, incorporating patient-specific characteristics. The primary objective is to validate the predicted ablation zones compared to clinical outcomes, offering insights into MWA before therapy to facilitate accurate treatment planning. Contrast-enhanced CT images from three patients were used to create 3D models. The simulations used coupled electromagnetic wave propagation and bioheat transfer to estimate the temperature distribution, predicting tumor destruction and ablation margins. The findings indicate that prolonged ablation does not significantly improve tumor destruction once an adequate margin is achieved, although it increases tissue damage. There was a substantial overlap between the clinical ablation zones and the predicted ablation zones. For patient 1, the Dice score was 0.73, indicating high accuracy, with a sensitivity of 0.72 and a specificity of 0.76. For patient 2, the Dice score was 0.86, with a sensitivity of 0.79 and a specificity of 0.96. For patient 3, the Dice score was 0.8, with a sensitivity of 0.85 and a specificity of 0.74. Patient-specific 3D models demonstrate potential in accurately predicting ablation zones and optimizing MWA treatment strategies.

Ablative margin quantification using deformable versus rigid image registration in colorectal liver metastasis thermal ablation: a retrospective single-center study

PURPOSE

To investigate the correlation of minimal ablative margin (MAM) quantification using biomechanical deformable (DIR) versus intensity-based rigid image registration (RIR) with local outcomes following colorectal liver metastasis (CLM) thermal ablation.

METHODS

This retrospective single-institution study included consecutive patients undergoing thermal ablation between May 2016 and October 2021. Patients who did not have intraprocedural pre- and post-ablation contrast-enhanced CT images for MAM quantification or follow-up period less than 1 year without residual tumor or local tumor progression (LTP) were excluded. DIR and RIR methods were used to quantify the MAM. The registration accuracy was compared using Dice similarity coefficient (DSC). Area under the receiver operating characteristic curve (AUC) was used to test MAM in predicting local tumor outcomes.

RESULTS

A total of 72 patients (mean age 57; 44 men) with 139 tumors (mean diameter 1.5 cm ± 0.8 (SD)) were included. During a median follow-up of 29.4 months, there was one residual unablated tumor and the LTP rate was 17% (24/138). The ranges of DSC were 0.96-0.98 and 0.67-0.98 for DIR and RIR, respectively (p < 0.001). When using DIR, 27 (19%) tumors were partially or totally registered outside the liver, compared to 46 (33%) with RIR. Using DIR versus RIR, the corresponding median MAM was 4.7 mm versus 4.0 mm, respectively (p = 0.5). The AUC in predicting residual tumor and 1-year LTP for DIR versus RIR was 0.89 versus 0.72, respectively (p < 0.001).

CONCLUSION

Ablative margin quantified on intra-procedural CT imaging using DIR method outperformed RIR for predicting local outcomes of CLM thermal ablation.

CLINICAL RELEVANCE STATEMENT

The study supports the role of biomechanical deformable image registration as the preferred image registration method over rigid image registration for quantifying minimal ablative margins using intraprocedural contrast-enhanced CT images.

KEY POINTS

• Accurate and reproducible image registration is a prerequisite for clinical application of image-based ablation confirmation methods. • When compared to intensity-based rigid image registration, biomechanical deformable image registration for minimal ablative margin quantification was more accurate for liver registration using intraprocedural contrast-enhanced CT images. • Biomechanical deformable image registration outperformed intensity-based rigid image registration for predicting local tumor outcomes following colorectal liver metastasis thermal ablation.

Analysis and prediction of liver volume change maps derived from computational tomography scans acquired pre- and post-radiation therapy

External beam radiation therapy (EBRT) of liver cancers can cause local liver atrophy as a result of tissue damage or hypertrophy as a result of liver regeneration. Predicting those volumetric changes would enable new strategies for liver function preservation during treatment planning. However, understanding of the spatial dose/volume relationship is still limited. This study leverages the use of deep learning-based segmentation and biomechanical deformable image registration (DIR) to analyze and predict this relationship. Pre- and Post-EBRT imaging data were collected for 100 patients treated for hepatocellular carcinomas, cholangiocarcinoma or CRC with intensity-modulated radiotherapy (IMRT) with prescription doses ranging from 50 to 100 Gy delivered in 10-28 fractions. For each patient, DIR between the portal and venous (PV) phase of a diagnostic computed tomography (CT) scan acquired before radiation therapy (RT) planning, and a PV phase of a diagnostic CT scan acquired after the end of RT (on average 147 ± 36 d) was performed to calculate Jacobian maps representing volume changes in the liver. These volume change maps were used: (i): to analyze the dose/volume relationship in the whole liver and individual Couinaud's segments; and (ii): to investigate the use of deep-learning to predict a Jacobian map solely based on the pre-RT diagnostic CT and planned dose distribution. Moderate correlations between mean equivalent dose in 2 Gy fractions (EQD2) and volume change was observed for all liver sub-regions analyzed individually with Pearson correlationrranging from -0.36 to -067. The predicted volume change maps showed a significantly stronger voxel-wise correlation with the DIR-based volume change maps than when considering the original EQD2 distribution (0.63 ± 0.24 versus 0.55 ± 23, respectively), demonstrating the ability of the proposed approach to establish complex relationships between planned dose and liver volume response months after treatment, which represents a promising prediction tool for the development of future adaptive and personalized liver radiation therapy strategies.

Imaging in Interventional Radiology: 2043 and Beyond

Since its inception in the early 20th century, interventional radiology (IR) has evolved tremendously and is now a distinct clinical discipline with its own training pathway. The arsenal of modalities at work in IR includes x-ray radiography and fluoroscopy, CT, MRI, US, and molecular and multimodality imaging within hybrid interventional environments. This article briefly reviews the major developments in imaging technology in IR over the past century, summarizes technologies now representative of the standard of care, and reflects on emerging advances in imaging technology that could shape the field in the century ahead. The role of emergent imaging technologies in enabling high-precision interventions is also briefly reviewed, including image-guided ablative therapies.

Ablative Margins of Colorectal Liver Metastases Using Deformable CT Image Registration and Autosegmentation

Background Confirming ablation completeness with sufficient ablative margin is critical for local tumor control following colorectal liver metastasis (CLM) ablation. An image-based confirmation method considering patient- and ablation-related biomechanical deformation is an unmet need. Purpose To evaluate a biomechanical deformable image registration (DIR) method for three-dimensional (3D) minimal ablative margin (MAM) quantification and the association with local disease progression following CT-guided CLM ablation. Materials and Methods This single-institution retrospective study included patients with CLM treated with CT-guided microwave or radiofrequency ablation from October 2015 to March 2020. A biomechanical DIR method with AI-based autosegmentation of liver, tumors, and ablation zones on CT images was applied for MAM quantification retrospectively. The per-tumor incidence of local disease progression was defined as residual tumor or local tumor progression. Factors associated with local disease progression were evaluated using the multivariable Fine-Gray subdistribution hazard model. Local disease progression sites were spatially localized with the tissue at risk for tumor progression (<5 mm) using a 3D ray-tracing method. Results Overall, 213 ablated CLMs (mean diameter, 1.4 cm) in 124 consecutive patients (mean age, 57 years ± 12 [SD]; 69 women) were evaluated, with a median follow-up interval of 25.8 months. In ablated CLMs, an MAM of 0 mm was depicted in 14.6% (31 of 213), from greater than 0 to less than 5 mm in 40.4% (86 of 213), and greater than or equal to 5 mm in 45.1% (96 of 213). The 2-year cumulative incidence of local disease progression was 72% for 0 mm and 12% for greater than 0 to less than 5 mm. No local disease progression was observed for an MAM greater than or equal to 5 mm. Among 117 tumors with an MAM less than 5 mm, 36 had local disease progression and 30 were spatially localized within the tissue at risk for tumor progression. On multivariable analysis, an MAM of 0 mm (subdistribution hazard ratio, 23.3; 95% CI: 10.8, 50.5; P < .001) was independently associated with local disease progression. Conclusion Biomechanical deformable image registration and autosegmentation on CT images enabled identification and spatial localization of colorectal liver metastases at risk for local disease progression following ablation, with a minimal ablative margin greater than or equal to 5 mm as the optimal end point. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Sofocleous in this issue.

Use of Contrast Media During CT-guided Thermal Ablation of Colorectal Liver Metastasis for Procedure Planning is Associated with Improved Immediate Outcomes

PURPOSE

The aim of this study was to analyze the impact of using intra-procedural pre-ablation contrast-enhanced CT prior to percutaneous thermal ablation (pre-ablation CECT) of colorectal liver metastases (CLM) on local outcomes.

MATERIALS AND METHODS

This retrospective analysis of a prospectively collected liver ablation registry included 144 consecutive patients (median age 57 years IQR [49, 65], 60% men) who underwent 173 CT-guided ablation sessions for 250 CLM between October 2015 and March 2020. In addition to oncologic outcomes, technical success was retrospectively evaluated using a biomechanical deformable image registration software for 3D-minimal ablative margin (3D-MAM) quantification. Bayesian regression was used to estimate effects of pre-ablation CECT on residual unablated tumor, 3D-MAM, and local tumor progression-free survival (LTPFS).

RESULTS

Pre-ablation CECT was acquired in 71/173 (41%) sessions. Residual unablated tumor was present in one (0.9%) versus nine tumors (6.6%) ablated with versus without using pre-ablation CECT, respectively (p = 0.024). Pre-ablation CECT use decreased the odds of residual disease on first follow-up by 78% (CI95% [5, 86]) and incomplete ablation (3D-MAM ≤ 0 mm) by 58% (CI95% [13, 122]). The odds ratio for residual unablated tumor for larger CLM was lower when pre-ablation CECT was used (odds ratio 1.0 with pre-ablation CECT vs. 2.52 without). Pre-ablation CECT use was not associated with improvements on LTPFS.

CONCLUSIONS

Pre-ablation CECT is associated with improved immediate outcomes by significantly reducing the incidence of residual unablated tumor and by mitigating the risk of incomplete ablation for larger CLM. We recommend performing baseline intra-procedural pre-ablation CECT as a standard imaging protocol.

LEVEL OF EVIDENCE

Level 3 (retrospective cohort study).

Targeted exome-based predictors of patterns of progression of colorectal liver metastasis after percutaneous thermal ablation

BACKGROUND

Percutaneous thermal ablation is a curative-intent locoregional therapy (LRT) for selected patients with unresectable colorectal liver metastasis (CLM). Several factors have been identified that contribute to local tumour control after ablation. However, factors contributing to disease progression outside the ablation zone after ablation are poorly understood.

METHODS

In this retrospective study, using next-generation sequencing, we identified genetic biomarkers associated with different patterns of progression following thermal ablation of CLM.

RESULTS

A total of 191 ablation naïve patients between January 2011 and March 2020 were included in the analysis, and 101 had genomic profiling available. Alterations in the TGFβ pathway were associated with increased risk of development of new intrahepatic tumours (hazard ratio [HR], 2.75, 95% confidence interval [95% CI] 1.39-5.45, P = 0.004); and alterations in the Wnt pathway were associated with increased probability of receiving salvage LRT for any intrahepatic progression (HR, 5.8, 95% CI 1.94-19.5, P = 0.003).

CONCLUSIONS

Our findings indicate that genomic alterations in cancer-related signalling pathways can predict different progression patterns and the likelihood of receiving salvage LRT following percutaneous thermal ablation of CLM.

Optimization of mesh generation for geometric accuracy, robustness, and efficiency of biomechanical-model-based deformable image registration

BACKGROUND

Successful generation of biomechanical-model-based deformable image registration (BM-DIR) relies on user-defined parameters that dictate surface mesh quality. The trial-and-error process to determine the optimal parameters can be labor-intensive and hinder DIR efficiency and clinical workflow.

PURPOSE

To identify optimal parameters in surface mesh generation as boundary conditions for a BM-DIR in longitudinal liver and lung CT images to facilitate streamlined image registration processes.

METHODS

Contrast-enhanced CT images of 29 colorectal liver cancer patients and end-exhale four-dimensional CT images of 26 locally advanced non-small cell lung cancer patients were collected. Different combinations of parameters that determine the triangle mesh quality (voxel side length and triangle edge length) were investigated. The quality of DIRs generated using these parameters was evaluated with metrics for geometric accuracy, robustness, and efficiency. Metrics for geometric accuracy included target registration error (TRE) of internal vessel bifurcations, dice similar coefficient (DSC), mean distance to agreement (MDA), Hausdorff distance (HD) for organ contours, and number of vertices in the triangle mesh. American Association of Physicists in Medicine Task Group 132 was used to ensure parameters met TRE, DSC, MDA recommendations before the comparison among the parameters. Robustness was evaluated as the success rate of DIR generation, and efficiency was evaluated as the total time to generate boundary conditions and compute finite element analysis.

RESULTS

Voxel side length of 0.2 cm and triangle edge length of 3 were found to be the optimal parameters for both liver and lung, with success rate of 1.00 and 0.98 and average DIR computation time of 100 and 143 s, respectively. For this combination, the average TRE, DSC, MDA, and HD were 0.38-0.40, 0.96-0.97, 0.09-0.12, and 0.87-1.17 mm, respectively.

CONCLUSION

The optimal parameters were found for the analyzed patients. The decision-making process described in this study serves as a recommendation for BM-DIR algorithms to be used for liver and lung. These parameters can facilitate consistence in the evaluation of published studies and more widespread utilization of BM-DIR in clinical practice.

Study Protocol COVER-ALL: Clinical Impact of a Volumetric Image Method for Confirming Tumour Coverage with Ablation on Patients with Malignant Liver Lesions

PURPOSE

This study aims to evaluate the intra-procedural use of a novel ablation confirmation (AC) method, consisting of biomechanical deformable image registration incorporating AI-based auto-segmentation, and its impact on tumor coverage by quantitative three-dimensional minimal ablative margin (MAM) CT-generated assessment.

MATERIALS AND METHODS

This single-center, randomized, phase II, intent-to-treat trial is enrolling 100 subjects with primary and secondary liver tumors (≤ 3 tumors, 1-5 cm in diameter) undergoing microwave or radiofrequency ablation with a goal of achieving ≥ 5 mm MAM. For the experimental arm, the proposed novel AC method is utilized for ablation applicator(s) placement verification and MAM assessment. For the control arm, the same variables are assessed by visual inspection and anatomical landmarks-based quantitative measurements aided by co-registration of pre- and post-ablation contrast-enhanced CT images. The primary objective is to evaluate the impact of the proposed AC method on the MAM. Secondary objectives are 2-year LTP-free survival, complication rates, quality of life, liver function, other oncological outcomes, and impact of AC method on procedure workflow.

DISCUSSION

The COVER-ALL trial will provide information on the role of a biomechanical deformable image registration-based ablation confirmation method incorporating AI-based auto-segmentation for improving MAM, which might translate in improvements of liver ablation efficacy.

CONCLUSION

The COVER-ALL trial aims to provide information on the role of a novel intra-procedural AC method for improving MAM, which might translate in improvements of liver ablation efficacy.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT04083378.

Evaluation of DIR algorithm performance in real patients for radiotherapy treatments: A systematic review of operator-dependent strategies

PURPOSE

The performance of deformable medical image registration (DIR) algorithms has become a major concern.

METHODS

We aimed to obtain updated information on DIR algorithm performance quantification through a literature review of articles published between 2010 and 2022. We focused only on studies using operator-based methods to treat real patients. The PubMed, Google Scholar and Embase databases were searched following PRISMA guidelines.

RESULTS

One hundred and seven articles were identified. The mean number of patients and registrations per publication was 20 and 63, respectively. We found 23 different geometric metrics appearing at least twice, and the dosimetric impact of DIR was quantified in 32 articles. Forty-eight different at-risk organs were described, and target volumes were studied in 43 publications. Prostate, head-and-neck and thoracic locations represented more than ¾ of the studied locations. We summarized the type of DIR and the images used, and other key elements. Intra/interobserver variability, threshold values and the correlation between metrics were also discussed.

CONCLUSIONS

This literature review covers the past decade and should facilitate the implementation of DIR algorithms in clinical practice by providing practical and pertinent information to quantify their performance on real patients.

Fat Quantification Imaging and Biophysical Modeling for Patient-Specific Forecasting of Microwave Ablation Therapy

Computational tools are beginning to enable patient-specific surgical planning to localize and prescribe thermal dosing for liver cancer ablation therapy. Tissue-specific factors (e.g., tissue perfusion, material properties, disease state, etc.) have been found to affect ablative therapies, but current thermal dosing guidance practices do not account for these differences. Computational modeling of ablation procedures can integrate these sources of patient specificity to guide therapy planning and delivery. This paper establishes an imaging-data-driven framework for patient-specific biophysical modeling to predict ablation extents in livers with varying fat content in the context of microwave ablation (MWA) therapy. Patient anatomic scans were segmented to develop customized three-dimensional computational biophysical models and mDIXON fat-quantification images were acquired and analyzed to establish fat content and determine biophysical properties. Simulated patient-specific microwave ablations of tumor and healthy tissue were performed at four levels of fatty liver disease. Ablation models with greater fat content demonstrated significantly larger treatment volumes compared to livers with less severe disease states. More specifically, the results indicated an eightfold larger difference in necrotic volumes with fatty livers vs. the effects from the presence of more conductive tumor tissue. Additionally, the evolution of necrotic volume formation as a function of the thermal dose was influenced by the presence of a tumor. Fat quantification imaging showed multi-valued spatially heterogeneous distributions of fat deposition, even within their respective disease classifications (e.g., low, mild, moderate, high-fat). Altogether, the results suggest that clinical fatty liver disease levels can affect MWA, and that fat-quantitative imaging data may improve patient specificity for this treatment modality.

Biopsy and Margins Optimize Outcomes after Thermal Ablation of Colorectal Liver Metastases

Simple Summary

Thermal ablation (TA) is a non-surgical treatment of cancer that has been used with success in the treatment of colorectal liver metastases (CLM). TA consists of burning the cancer and a rim of surrounding tissue (margin) with a special needle placed in the tumor under image guidance. Despite the technological evolution of TA, tumor progression/recurrence rates remain higher than expected. We present a method that combines tissue and imaging tests performed immediately after ablation to determine whether there is complete tumor destruction or remaining live cancer cells that can cause tumor progression/recurrence. This information can provide guidance for additional treatments for patients with evidence of residual cancer, i.e.,: additional TA at the same or subsequent sitting, or additional chemotherapy and short-interval imaging follow-up to detect recurrence. The presented method proposes a clinical practice paradigm change that can improve clinical outcomes in a large population of patients with CLM treated by TA.

Abstract

Background: Thermal ablation is a definitive local treatment for selected colorectal liver metastases (CLM) that can be ablated with adequate margins. A critical limitation has been local tumor progression (LTP). Methods: This prospective, single-group, phase 2 study enrolled patients with CLM < 5 cm in maximum diameter, at a tertiary cancer center between November 2009 and February 2019. Biopsy of the ablation zone center and margin was performed immediately after ablation. Viable tumor in tissue biopsy and ablation margins < 5 mm were assessed as predictors of 12-month LTP. Results: We enrolled 107 patients with 182 CLMs. Mean tumor size was 2.0 (range, 0.6–4.6) cm. Microwave ablation was used in 51% and radiofrequency ablation in 49% of tumors. The 12- and 24-month cumulative incidence of LTP was 22% (95% confidence interval [CI]: 17, 29) and 29% (95% CI: 23, 36), respectively. LTP at 12 months was 7% (95% CI: 3, 14) for the biopsy tumor-negative ablation zone with margins ≥ 5 mm vs. 63% (95% CI: 35, 85) for the biopsy-positive ablation zone with margins < 5 mm (p < 0.001). Conclusions: Biopsy-proven complete tumor ablation with margins of at least 5 mm achieves optimal local tumor control for CLM, regardless of the ablation modality used.

3D margin assessment predicts local tumor progression after ablation of colorectal cancer liver metastases

OBJECTIVE

To determine the feasibility and prognostic value of 3D measuring of the ablation margins using a dedicated image registration software.

METHODS

This retrospective study included 104 colorectal liver metastases in 68 consecutive patients that underwent microwave ablation between 08/2012 and 08/2019. The minimal ablation margin (MM) was measured in 2D using anatomic landmarks on contrast enhanced CT(CECT) 4-8 weeks post-ablation, and in 3D using an image registration software and immediate post-ablation CECT. Local tumor progression (LTP) was assessed by imaging up to 24 months after ablation. A blinded interventional radiologist provided feedback on the possibility of additional ablation after examining the 3D-margin measurements.

RESULTS

The 3D-margin assessment was completed in 79/104 (76%) tumors without the need for target manipulation. In 25/104 (24%) tumors, manipulation was required due to image misregistration. LTP was observed in 40/104 (38.5%) tumors: 92.5% vs 7.5% for those with margin <5mm vs ≥5mm, respectively (p = 0.0001). The 2D and 3D-assessments identified margin <5mm in 17/104 (16%), and in 74/104 (71%) ablated tumors, respectively (p < 0.01). The sensitivity and specificity of the 3D software for predicting LTP was 93% (37/40) and 42% (27/64), respectively. Additional ablation to achieve a MM of 5 mm would have been offered in 26/37 cases if the 3D-margin assessment was available intraoperatively.

CONCLUSION

Image registration software can measure ablation margins and detect MM under 5 mm intraoperatively, with significantly higher sensitivity than the 2D technique using landmarks on the post-ablation CECT. The identification of a margin under 5 mm is strongly associated with LTP.

3D Quantitative Ablation Margins for Prediction of Ablation Site Recurrence After Stereotactic Image-Guided Microwave Ablation of Colorectal Liver Metastases: A Multicenter Study

Background

Three-dimensional (3D) volumetric ablation margin assessment after thermal ablation of liver tumors using software has been described, but its predictive value on treatment efficacy when accounting for other factors known to correlate ablation site recurrence (ASR) remains unknown.

Purpose

To investigate 3D quantitative ablation margins (3D-QAMs) as an algorithm to predict ASR within 1 year after stereotactic microwave ablation (SMWA) for colorectal liver metastases (CRLM).

Materials and Methods

Sixty-five tumors in 47 patients from a prospective multicenter study of patients undergoing SMWA for CRLM were included in this retrospective 3D-QAM analysis. Using a previously developed algorithm, 3D-QAM defined as the distribution of tumor to ablation surface distances was assessed in co-registered pre- and post-ablation CT scans. The discriminatory power and optimal cutoff values for 3D-QAM were assessed using receiver operating characteristic (ROC) curves. Multivariable logistic regression analysis using generalized estimating equations was applied to investigate the impact of various 3D-QAM outputs on 1-year ASR while accounting for other known influencing factors.

Results

Ten of the 65 (15.4%) tumors included for 3D-QAM analysis developed ASR. ROC analyses identified i) 3D-QAM <1 mm for >23% of the tumor surface, ii) 3D-QAM <5 mm for >45%, and iii) the minimal ablation margin (MAM) as the 3D-QAM outputs with optimal discriminatory qualities. The multivariable regression model without 3D-QAM yielded tumor diameter and KRAS mutation as 1-year ASR predictors. When adding 3D-QAM, this factor became the main predictor of 1-year ASR [odds ratio (OR) 21.67 (CI 2.48, 165.21) if defined as >23% <1 mm; OR 0.52 (CI 0.29, 0.95) if defined as MAM].

Conclusions

3D-QAM allows objectifiable and standardized assessment of tumor coverage by the ablation zone after SMWA. Our data shows that 3D-QAM represents the most important factor predicting ASR within 1 year after SMWA of CRLM.