Percutaneous liver ablation is a minimally invasive procedure to treat liver tumors. Postablation images are highly significant as they distinguish normal post-procedure changes from abnormalities, preventing unnecessary retreatment and confirming procedural quality. However, the cancer surveillance imaging reports after the procedure can be numerous and challenging to read. Moreover, annotated data is limited in this setting. In this study we used the cutting-edge large language model Llama 2 to automatically extract critical findings from real-world diagnostic imaging reports without the need of training a new information extraction model. This could potentially automate part of the outcome research and registry construction process, as well as decrease the number of studies needed to review for research purposes. A dataset of 87 full-text reports from 13 patients who underwent percutaneous thermal ablation for pancreatic liver metastases were used to benchmark the capability of Llama 2 for cancer progression finding extraction and classification. We asked Llama 2 to determine whether there is cancer progression within the given report and then classify progression findings into Local Tumor Progression (LTP), Intrahepatic Progression (IHP) and Extrahepatic Progression (EHP). Llama 2 achieved decent performance for detecting progression at study level. The precision is 0.91 and recall is 0.96, with specificity 0.84. However, the classification of progression into LTP, IHP and EHP still needs to be improved.
Microwave ablation (MWA) is an effective minimally invasive therapy for treating liver cancers, among various local cancer treatments. Computational studies are crucial in simulating MWA, offering insights that may be unreachable from experimental methods. This study investigated the complex relationships between blood perfusion rate and metabolic heat concerning MWA outcomes. 3D patient-specific finite element models are employed, shedding light on the interplay of these parameters and their impact on the efficacy of MWA procedures. Image data from five patients treated with MWA are chosen, creating detailed 3D models of the liver, tumor, and vasculature. Simulations are performed using a triaxial antenna operating at 2.45 GHz, with a standard ablation time of 10 minutes and an input power of 65 Watts. In addition, the microwave antenna mimics the clinical insertion path in each case. The simulation model encompasses the coupled electromagnetic field and bioheat transfer, comprehensively understanding the underlying dynamics. The simulations contain seven distinct blood perfusion rates, both with and without considering metabolic heat. This variation allows for a thorough exploration of their combined impact on tissue damage and tumor destruction throughout MWA therapy. These findings underscore the intricate interplay of factors influencing the outcomes of MWA procedures, emphasizing the importance of comprehensive modeling that incorporates various parameters for accurate predictions.
Image guided percutaneous thermal ablation is widely used for patients with primary or secondary liver tumors who do not qualify for surgical resection. The COVER-ALL study is a randomized Phase II clinical trial that evaluates the impact of using software aid in confirming probe position and ablation coverage. Current practice in the trial involves acquisition of a pre-procedure contrast enhanced computed tomography (CECT) scan for gross tumor volume (GTV) definition and non-contrast CT after probe placement, followed by a biomechanical model-based deformable image registration (Morfeus) between the two scans to map the GTV onto the non-contrast CT for position confirmation. CT scan length that covers the entire liver is needed for Morfeus. In this work, we investigated an alternative workflow with a reduced length non-contrast CT using image padding on the first 50 COVER-ALL trial patients. The full-length non-contrast CT was first cropped to a fixed thickness, ranging from 2.5-7.5 cm, along the GTV. The remaining volume was padded with the CECT based on intensity-based deformable image registration (DIR). Morfeus DIR was performed between the CECT and resultant padded non-contrast CT to map the GTV segmentation from CECT to padded non-contrast CT. The GTV mapping results were compared to the original GTV mapping results performed on the full-length CT. The median mapping differences using cropping thickness of 7.5 cm was 1.2 (0.5-2.3) mm, with only 3 cases having larger than 5 mm discrepancies. The comparable DIR performance suggests the feasibility of acquiring a reduced-length non-contrast CT to maintain image registration accuracy.
The purpose of this research is to improve treatment of colorectal liver metastases (CLM) in the clinic. It has been previously shown that an ablation margin of 5 mm or more for CLM greatly increases 5 year local tumor progression free survival, however it is often difficult to ensure proper ablation using intraprocedural imaging. CT images of 30 patients with CLM treated with ablation were retrospectively obtained from the MD Anderson Cancer Center. Contours defining the liver, ablation probes, CLM margins, and ablation margin were created from the pre-treatment contrast enhanced CTs and intra-interventional CT images. Using a biomechanical model-based deformable image registration these contours were deformed onto the contrast enhanced CT images obtained just after treatment. The propagated ablation region was then compared with the GTV, as defined before the procedure, to determine the ablation margin delivered. There was a statistically significant difference (p<0.01) in the achieved ablation margin between patients who did and did not have local recurrence. Results showed that patients without local recurrence received on average 3.19 mm of minimum ablation margin around the gross tumor volume(GTV), while those with local recurrence received an average of 1.14 mm. The model presented can assist in the treatment of CLM by identifying the minimum distance to agreement between the GTV and the ablation region directly after treatment. This metric can help determine if sufficient ablation has been delivered to the treat the disease.
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