Abstract

ObjectivesTo compare the accuracy of liver tumour localisation in intraprocedural computed tomography (CT) images of computer-based rigid registration or non-rigid registration versus mental registration performed by interventional radiologists.MethodsRetrospectively (2009-2017), 35 contrast-enhanced CT (CECT) images incorporating 56 tumours, acquired during CT-guided ablation procedures and their corresponding pre-procedural diagnostic CECTs were retrieved from the picture archiving and communication system (PACS). The original intraprocedural CECTs were de-enhanced to create a virtually unenhanced CT image (VUCT). Alignment of diagnostic CECTs to their corresponding intraprocedural VUCTs was performed with non-rigid or rigid registration. Mental registration was performed by four interventional radiologists. The original intraprocedural CECT served as the reference standard. Accuracy of tumour localisation was assessed with the target registration error (TRE). Statistical differences were analysed with the Wilcoxon signed-rank test.ResultsNon-rigid registration failed to register two CT datasets, incorporating four tumours. In the remaining 33 datasets, non-rigid, rigid and mental registration showed a median TRE of 3.9 mm, 9.0 mm and 10.9 mm, respectively. Non-rigid registration was significantly more accurate in tumour centre localisation in comparison to rigid (p < 0.001) or mental registration (p < 0.001). Rigid registration was not statistically different from mental registration (p = 0.169). Non-rigid registration was most accurate in localising tumour centres in 42 out of 52 tumours (80.8%), while rigid and mental registration were most accurate in only seven (13.5%) and three (5.8%) tumours, respectively.ConclusionsComputer-based non-rigid registration is statistically significantly more accurate in localising liver tumours in intraprocedural unenhanced CT images in comparison to rigid registration or interventional radiologists’ mental mapping abilities.Key Points• Computer-based non-rigid registration is better (p < 0.001) in localising target tumours prior to ablation in intraprocedural CT images in comparison to rigid registration or interventional radiologists’ mental mapping abilities.• Human experts perform sub-optimal localisation of target tumours when relying solely on mental mapping during challenging CT-guided procedures.• This non-rigid registration method shows promising results as a safe alternative to intravenous contrast media in liver tumour localisation prior to ablation during CT-guided procedures.

Highlights

  • Radiofrequency ablation (RFA) and microwave ablation (MWA) are widely accepted minimally invasive procedures for the treatment of malignant liver tumours [1, 2]

  • The intraprocedural virtually unenhanced Computed tomography (CT) (VUCTs) were created by replacing hyperattenuated regions [hepatocellular carcinomas (HCCs) and contrast-enhanced vessels] or manual segmented hypoattenuated regions with values that are representative for the normal liver tissue

  • Secondary tumours showed a hypovascular appearance on the original intraprocedural contrast-enhanced CT (CECT) and mainly concerned colorectal metastases (n = 16) or metastases from neuroendocrine (n = 3), gastric (n = 1) or breast (n = 1) origin

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Summary

Introduction

Radiofrequency ablation (RFA) and microwave ablation (MWA) are widely accepted minimally invasive procedures for the treatment of malignant liver tumours [1, 2]. To localise liver tumours during image-guided ablation procedures, ultrasound (US) is often preferred as the initial imaging modality. Computed tomography (CT) is used to target tumours that cannot be localised with US. Interventional radiologists mentally map tumour information such as location and size from the diagnostic pre-procedural contrast-enhanced CT (CECT) scan and apply it to the intraprocedural unenhanced CT scan. This is challenging, since few landmarks are available in unenhanced CT scans [3]. Diagnostic and intraprocedural CT scans are generally acquired weeks apart and, tumour evolution, image quality, patient positioning and respiratory motion may hamper localisation [4, 5]

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