Organ-focused mutual information for nonrigid multimodal registration of liver CT and Gd–EOB–DTPA-enhanced MRI

Abstract

Accurate detection of liver lesions is of great importance in hepatic surgery planning. Recent studies have shown that the detection rate of liver lesions is significantly higher in gadoxetic acid-enhanced magnetic resonance imaging (Gd-EOB-DTPA-enhanced MRI) than in contrast-enhanced portal-phase computed tomography (CT); however, the latter remains essential because of its high specificity, good performance in estimating liver volumes and better vessel visibility. To characterize liver lesions using both the above image modalities, we propose a multimodal nonrigid registration framework using organ-focused mutual information (OF-MI). This proposal tries to improve mutual information (MI) based registration by adding spatial information, benefiting from the availability of expert liver segmentation in clinical protocols. The incorporation of an additional information channel containing liver segmentation information was studied. A dataset of real clinical images and simulated images was used in the validation process. A Gd-EOB-DTPA-enhanced MRI simulation framework is presented. To evaluate results, warping index errors were calculated for the simulated data, and landmark-based and surface-based errors were calculated for the real data. An improvement of the registration accuracy for OF-MI as compared with MI was found for both simulated and real datasets. Statistical significance of the difference was tested and confirmed in the simulated dataset (p < 0.01).

Fully automated convolutional neural network-based affine algorithm improves liver registration and lesion co-localization on hepatobiliary phase T1-weighted MR images

“…Conversely, Fernandez-de-Manuel et al [36] proposed a liver-focused deformable registration algorithm using high SNR gadoxetate disodium-enhanced 3D T1-weighted HBP images for liver lesion evaluation. In their study, they reported a mean intra-observation distance of 7.07 mm after registration, which is similar to our results.…”

Structure guided deformable image registration for treatment planning CT and post stereotactic body radiation therapy (SBRT) Primovist® (Gd‐EOB‐DTPA) enhanced MRI

“…Select past studies that looked at the CT‐MRI liver region registration according to the MIDRAS (Results of a M ulti‐ I nstituion D eformable R egistration A ccuracy S tudy) have found that the average error ranged from 3.9 to 6.5 mm for different registration approaches . More recently, the study by Manuel et al 2014 used an organ‐focused mutual information approach for the purpose of registering CT and Gd‐EOB‐DTPA MRI has reported a median landmark‐based error of 6.86 mm, and a median surface‐based mean error of 3.23 mm . Furthermore, the majority of selected studies tended to acquire images on the same day, or in the case of Manuel et al 2014 , the MRI scans did not correspond to patients who had undergone radiation therapy.…”

“Patient‐specific validation of deformable image registration in radiation therapy: Overview and caveats”

“…Landmarks indeed represent another common way to evaluate DIR accuracy. 75 In order to avoid the invasiveness of implanted surrogates, 71 corresponding anatomical landmarks are usually extracted manually 15,27,34,[76][77][78][79][80][81][82] and then used to compute their distance (or the so-called Target Registration Error, if landmarks are within the tumor). 51 Landmark techniques are, however, limited with poor image quality and contrast.…”