Comparing nonrigid registration techniques for motion corrected MR prostate diffusion imaging

Buerger, Christian; Sénégas, Julien; Kabus, Sven; Carolus, Heike; Schulz, Heinrich; Agarwal, Harsh; Türkbey, Barış; Choyke, Peter L.; Renisch, Steffen

doi:10.1118/1.4903262

Cited by 9 publications

(10 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…From the tumor segmentation, the whole tumor volume and the enhancing portion of tumor volume (cm 3 ) could be obtained. To measure the enhancing volume, the CT scan obtained just before contrast medium administration (i.e., unenhanced CT scan) was registered to the arterial phase CT scan and then subtracted in order to remove any background attenuation [5, 15]. The subtraction is a key feature because it mitigates contribution of background attenuation from the Lipiodol deposition that would otherwise obscure the true enhancement from the contrast medium injection (Fig.…”

Section: Methodsmentioning

confidence: 99%

Which Criteria Applied in Multi-Phasic CT Can Predict Early Tumor Response in Patients with Hepatocellular Carcinoma Treated Using Conventional TACE: RECIST, mRECIST, EASL or qEASL?

Zhao

Durán

Bai

et al. 2017

Cardiovasc Intervent Radiol

View full text Add to dashboard Cite

Purpose Our study aimed to evaluate quantitative tumor response assessment (quantitative EASL-[qEASL]) on computed tomography (CT) images in patients with hepatocellular carcinoma (HCC) treated using conventional transarterial chemoembolization (cTACE), compared to existing 1-dimensional and 2-dimensional methods (RECIST, mRECIST, EASL). Materials and Methods In this IRB-approved, single-institution retrospective cohort study, 52 consecutive patients with intermediate-stage HCC were consecutively included. All patients underwent contrast-enhanced CT scan at baseline and 4 weeks after cTACE. Results Median follow-up period was 13.5 months (range 1.2–54.1). RECIST, mRECIST and EASL identified progression in 2 (4%), 1 (2%) and 1 (2%) patients, respectively, whereas qEASL identified 10 (19%) patients. qEASL was the only tumor response method able to predict survival among different tumor response groups (P<0.05), whereas RECIST, mRECIST and EASL did not (P>0.05). Both EASL and qEASL were able to identify responders and non-responders and were predictive of survival (P<0.05). Multivariate analysis showed that progression was an independent predictor of overall survival with hazard ratio of 1.9 (P = 0.025). Patients who demonstrated progression with qEASL had significantly shorter survival than those with non-progression (7.6 vs. 20.4 months, P = 0.012). Similar multivariate analysis using RECIST, mRECIST and EASL could not be performed because too few patients were categorized as progressive disease. Conclusion qEASL could be applied on CT images to assess tumor response following cTACE and is a more sensitive biomarker to predict survival and identify tumor progression than RECIST, mRECIST and EASL at an early time point. Level of Evidence Level 2a, retrospective cohort study.

show abstract

Section: Methodsmentioning

confidence: 99%

Which Criteria Applied in Multi-Phasic CT Can Predict Early Tumor Response in Patients with Hepatocellular Carcinoma Treated Using Conventional TACE: RECIST, mRECIST, EASL or qEASL?

Zhao

Durán

Bai

et al. 2017

Cardiovasc Intervent Radiol

View full text Add to dashboard Cite

show abstract

“…Crum et al found FFD B‐spline methods utilizing the NMI metric superior to affine registration using the correlation ratio metric and fluid modeling methods utilizing the CC metric, when propagating segmentations of brain regions on MR. Hawkins, Wittek, and Miller contrasted the use of a hyperviscoelastic material, a hyperelastic model and an elastic model for modeling brain deformations, finding no significant performance variation between the models. Buerger et al performed an evaluation of FFD B‐spline registration (with a gradient descent and a Levenberg–Marquardt optimizer), HALA registration, Demons registration and elastic model registration for motion correction in prostate MR imaging. The elastic model was found to provide superior accuracy and computation time.…”

Section: Technologies and Techniquesmentioning

confidence: 99%

PET motion correction in context of integrated PET/MR: Current techniques, limitations, and future projections

et al. 2017

View full text Add to dashboard Cite

Patient motion is an important consideration in modern PET image reconstruction. Advances in PET technology mean motion has an increasingly important influence on resulting image quality. Motion-induced artifacts can have adverse effects on clinical outcomes, including missed diagnoses and oversized radiotherapy treatment volumes. This review aims to summarize the wide variety of motion correction techniques available in PET and combined PET/CT and PET/MR, with a focus on the latter. A general framework for the motion correction of PET images is presented, consisting of acquisition, modeling, and correction stages. Methods for measuring, modeling, and correcting motion and associated artifacts, both in literature and commercially available, are presented, and their relative merits are contrasted. Identified limitations of current methods include modeling of aperiodic and/or unpredictable motion, attaining adequate temporal resolution for motion correction in dynamic kinetic modeling acquisitions, and maintaining availability of the MR in PET/MR scans for diagnostic acquisitions. Finally, avenues for future investigation are discussed, with a focus on improvements that could improve PET image quality, and that are practical in the clinical environment.

show abstract

“…Specifically, several studies have compared registration techniques for various MRI sequences in the prostate[31][32][33]. For example, Buerger et al compared the performance of five state-of-the-art DIR image registration techniques for accurate image fusion of DWI with T2W images and found fast elastic image registration provided improved performance compared to other deformable techniques such as B-spline and Demons[32]. This result was further echoed in Eriksson et al, which confirmed that fast elastic image registration was the best technique for T1-weighted to T2W anatomic sequence registration[33].…”

mentioning

confidence: 99%

“…However, intra-acquisition MRI registration techniques have been investigated in other anatomical sites. Specifically, several studies have compared registration techniques for various MRI sequences in the prostate[31][32][33]. For example, Buerger et al compared the performance of five state-of-the-art DIR image registration techniques for accurate image fusion of DWI with T2W images and found fast elastic image registration provided improved performance compared to other deformable techniques such as B-spline and Demons[32].…”

mentioning

confidence: 99%

Quality Assurance Assessment of Intra-Acquisition Diffusion-Weighted and T2-Weighted Magnetic Resonance Imaging Registration and Contour Propagation for Head and Neck Cancer Radiotherapy

Naser

Wahid

Ahmed

et al. 2021

Preprint

View full text Add to dashboard Cite

Background/Purpose: Adequate image registration of anatomic and functional MRI scans is necessary for MR-guided head and neck cancer (HNC) adaptive radiotherapy planning. Despite the quantitative capabilities of diffusion-weighted imaging (DWI) MRI for treatment plan adaptation, geometric distortion remains a considerable limitation. Therefore, we systematically investigated various deformable image registration (DIR) algorithms to co-register DWI and T2-weighted (T2W) images. Materials/Methods: We compared post-acquisition registration algorithms from three software packages (ADMIRE, Velocity, and 3D Slicer) applied to T2W and DWI MRI images in twenty HNC patients. In addition, we investigated implicit rigid registration (no algorithm applied) as a control comparator. Ground truth segmentations of radiotherapy structures (tumor and organs at risk) were generated by a physician expert on both image sequences. Three additional experts provided segmentations for five cases for interobserver variability studies. For each registration approach, structures were propagated from T2W to DWI images. These propagated structures were then compared with ground truth DWI structures using the Dice similarity coefficient (DSC), false-negative DSC, false-positive DSC, surface DSC, 95% Hausdorff distance, and mean surface distance. Results: 19 left submandibular glands, 18 right submandibular glands, 20 left parotid glands, 20 right parotid glands, 20 spinal cords, 9 brainstems, and 12 tumors were delineated. ADMIRE, the atlas-based auto segmentation DIR algorithm, demonstrated improved performance over implicit rigid registrations for most comparison metrics and structures (Bonferroni-corrected p < 0.05), while Velocity and 3D Slicer algorithms did not. Moreover, the ADMIRE methods significantly improved performance in individual and pooled analysis compared to all other methods. Interobserver variability analysis revealed no significant difference between observers (p > 0.05). Conclusions: Certain deformable registration software packages, such as those provided by ADMIRE, may be favorable for registering T2W and DWI images. These results are important to ensure the appropriate selection of registration strategies for MR-guided radiotherapy.

show abstract

Comparing nonrigid registration techniques for motion corrected MR prostate diffusion imaging

Abstract: The authors' results show that the "fast elastic image registration" provides most accurate results with a target registration error of 1.07 ± 0.41 mm at minimum execution times of 11 ± 1 s.

Cited by 9 publications

References 27 publications

Which Criteria Applied in Multi-Phasic CT Can Predict Early Tumor Response in Patients with Hepatocellular Carcinoma Treated Using Conventional TACE: RECIST, mRECIST, EASL or qEASL?

Which Criteria Applied in Multi-Phasic CT Can Predict Early Tumor Response in Patients with Hepatocellular Carcinoma Treated Using Conventional TACE: RECIST, mRECIST, EASL or qEASL?

PET motion correction in context of integrated PET/MR: Current techniques, limitations, and future projections

Quality Assurance Assessment of Intra-Acquisition Diffusion-Weighted and T2-Weighted Magnetic Resonance Imaging Registration and Contour Propagation for Head and Neck Cancer Radiotherapy

Contact Info

Product

Resources

About