Evidence map›Paper›PMID 27811396›Full record

ArticlePhysics in medicine and biology2016

Performance evaluation of MIND demons deformable registration of MR and CT images in spinal interventions.

S Reaungamornrat, T De Silva, A Uneri, J Goerres, M Jacobson, M Ketcha, S Vogt, G Kleinszig, A J Khanna, J-P Wolinsky and 2 more

Abstract readEvaluation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Physics in medicine and biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Inter-scanner Variation Independent Descriptors for Constrained Diffeomorphic Demons Registration of Retina OCT.Proceedings of SPIE--the International Society for Optical Engineering · 2018
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

S ReaungamornratDepartment of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA.
T De SilvaDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21202, USA.
A UneriDepartment of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA.
J GoerresDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21202, USA.
M JacobsonDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21202, USA.
M KetchaDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21202, USA.
S VogtSiemens Healthcare XP Division, Erlangen 91052, Germany.
G KleinszigSiemens Healthcare XP Division, Erlangen 91052, Germany.
A J KhannaDepartment of Orthopaedic Surgery, Johns Hopkins Orthopaedic Surgery-DC, Bethesda, MD 20817, USA.
J-P WolinskyDepartment of Neurosurgery, Johns Hopkins Hospital, Baltimore, MD 21202, USA.
J L PrinceDepartment of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA.
J H SiewerdsenDepartment of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA.

Funding

Intraoperative Imaging for Guidance, Patient Safety, and OR Quality AssuranceR01EB017226 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI SIEWERDSEN, JEFFREY H · 2014 to 2017
$2.1M
NIBIB NIH HHS R01 EB017226
6 · The paper itself

Abstract

Accurate intraoperative localization of target anatomy and adjacent nervous and vascular tissue is essential to safe, effective surgery, and multimodality deformable registration can be used to identify such anatomy by fusing preoperative CT or MR images with intraoperative images. A deformable image registration method has been developed to estimate viscoelastic diffeomorphisms between preoperative MR and intraoperative CT using modality-independent neighborhood descriptors (MIND) and a Huber metric for robust registration. The method, called MIND Demons, optimizes a constrained symmetric energy functional incorporating priors on smoothness, geodesics, and invertibility by alternating between Gauss-Newton optimization and Tikhonov regularization in a multiresolution scheme. Registration performance was evaluated for the MIND Demons method with a symmetric energy formulation in comparison to an asymmetric form, and sensitivity to anisotropic MR voxel-size was analyzed in phantom experiments emulating image-guided spine-surgery in comparison to a free-form deformation (FFD) method using local mutual information (LMI). Performance was validated in a clinical study involving 15 patients undergoing intervention of the cervical, thoracic, and lumbar spine. The target registration error (TRE) for the symmetric MIND Demons formulation (1.3  ±  0.8 mm (median  ±  interquartile)) outperformed the asymmetric form (3.6  ±  4.4 mm). The method demonstrated fairly minor sensitivity to anisotropic MR voxel size, with median TRE ranging 1.3-2.9 mm for MR slice thickness ranging 0.9-9.9 mm, compared to TRE  =  3.2-4.1 mm for LMI FFD over the same range. Evaluation in clinical data demonstrated sub-voxel TRE (<2 mm) in all fifteen cases with realistic deformations that preserved topology with sub-voxel invertibility (0.001 mm) and positive-determinant spatial Jacobians. The approach therefore appears robust against realistic anisotropic resolution characteristics in MR and yields registration accuracy suitable to application in image-guided spine-surgery.

Indexed as

AlgorithmsPhantoms, ImagingHumansImage Processing, Computer-AssistedImaging, Three-DimensionalMagnetic Resonance ImagingMultimodal ImagingSpineSurgery, Computer-AssistedTomography, X-Ray Computed

Identifiers

PMID27811396
PMCPMC5217769

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.