Computerized Image Registration approaches can offer automatic and accurate image alignments without extensive user involvement and provide tools for visualizing combined images. The aim of this survey is to present a review of publications related to Medical Image Registration. This paper paints a comprehensive picture of image registration methods and their applications. This paper is an introduction for those new to the ﬁeld, an overview for those working in the ﬁeld and a reference for those searching for literature on a speciﬁc application. Methods are classiﬁed according to the diﬀerent aspects of Medical Image Registration.

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Survey of Medical Image Registration

Objective A major shortcoming of image-guided navigational systems is the use of preoperatively acquired image data, which does not account for intraoperative changes in brain morphology. The occurrence of these surgically induced volumetric deformations ("brain shift") has been well established. Maximal measurements for surface and midline shifts have been reported. There has been no detailed analysis, however, of the changes that occur during surgery. The use of intraoperative magnetic resonance imaging provides a unique opportunity to obtain serial image data and characterize the time course of brain deformations during surgery. Methods The vertically open intraoperative magnetic resonance imaging system (SignaSP, 0.5 T; GE Medical Systems, Milwaukee, WI) permits access to the surgical field and allows multiple intraoperative image updates without the need to move the patient. We developed volumetric display software (the 3D Slicer) that allows quantitative analysis of the degree and direction of brain shift. For 25 patients, four or more intraoperative volumetric image acquisitions were extensively evaluated. Results Serial acquisitions allow comprehensive sequential descriptions of the direction and magnitude of intraoperative deformations. Brain shift occurs at various surgical stages and in different regions. Surface shift occurs throughout surgery and is mainly attributable to gravity. Subsurface shift occurs during resection and involves collapse of the resection cavity and intraparenchymal changes that are difficult to model. Conclusion Brain shift is a continuous dynamic process that evolves differently in distinct brain regions. Therefore, only serial imaging or continuous data acquisition can provide consistently accurate image guidance. Furthermore, only serial intraoperative magnetic resonance imaging provides an accurate basis for the computational analysis of brain deformations, which might lead to an understanding and eventual simulation of brain shift for intraoperative guidance.

Serial intraoperative magnetic resonance imaging of brain shift.

We present a new algorithm for the nonrigid registration of three-dimensional magnetic resonance (MR) intraoperative image sequences showing brain shift. The algorithm tracks key surfaces of objects (cortical surface and the lateral ventricles) in the image sequence using a deformable surface matching algorithm. The volumetric deformation field of the objects is then inferred from the displacements at the boundary surfaces using a linear elastic biomechanical finite-element model. Two experiments on synthetic image sequences are presented, as well as an initial experiment on intraoperative MR images showing brain shift. The results of the registration algorithm show a good correlation of the internal brain structures after deformation, and a good capability of measuring surface as well as subsurface shift. We measured distances between landmarks in the deformed initial image and the corresponding landmarks in the target scan. Cortical surface shifts of up to 10 mm and subsurface shifts of up to 6 mm were recovered with an accuracy of 1 mm or less and 3 mm or less respectively.

Registration of 3-d intraoperative MR images of the brain using a finite-element biomechanical model

OBJECTIVE To evaluate diffusion tensor imaging (DTI)-based functional neuronavigation in surgery of cerebral gliomas with pyramidal tract (PT) involvement with respect to both perioperative assessment and follow-up outcome. METHODS A prospective, randomized controlled study was conducted between 2001 and 2005. A consecutive series of 238 eligible patients with initial imaging diagnosis of cerebral gliomas involving PTs were randomized into study (n = 118) and control (n = 120) groups. The study cases underwent DTI and three-dimensional magnetic resonance imaging scans. The maps of fractional anisotropy were calculated for PT mapping. Both three-dimensional magnetic resonance imaging data sets and fractional anisotropy maps were integrated by rigid registration, after which the tumor and adjacent PT were segmented and reconstructed for presurgical planning and intraoperative guidance. The control cases were operated on using routine neuronavigation. RESULTS There was a trend for high-grade gliomas (HGGs) in the study group to be more likely to achieve gross total resection (74.4 versus 33.3%, P < 0.001). There was no significant difference of low-grade gliomas resection between the two groups. Postoperative motor deterioration occurred in 32.8% of control cases, whereas it occurred in only 15.3% of the study cases (P < 0.001). The 6-month Karnofsky Performance Scale score of study cases was significantly higher than that of control cases (86 +/- 20 versus 74 +/- 28 overall, P < 0.001; 93 +/- 10 versus 86 +/- 17 for low-grade gliomas, P = 0.013; and 77 +/- 27 versus 53 +/- 32 for HGGs, P = 0.001). For 81 HGGs, the median survival of study cases was 21.2 months (95% confidence interval, 14.1-28.3 mo) compared with 14.0 months (95% confidence interval, 10.2-17.8 mo) of control cases (P = 0.048). The estimated hazard ratio for the effect of DTI-based functional neuronavigation was 0.570, representing a 43.0% reduction in the risk of death. CONCLUSION DTI-based functional neuronavigation contributes to maximal safe resection of cerebral gliomas with PT involvement, thereby decreasing postoperative motor deficits for both HGGs and low-grade gliomas while increasing high-quality survival for HGGs.

Clinical evaluation and follow-up outcome of diffusion tensor imaging-based functional neuronavigation: a prospective, controlled study in patients with gliomas involving pyramidal tracts.

Over the past decade, several methods have been proposed to image tissue elasticity based on imaging methods collectively called elastography. While progress in developing these systems has been rapid, the basic understanding of tissue properties to interpret elastography images is generally lacking. To address this limitation, we developed a system to measure the Young's modulus of small soft tissue specimens. This system was designed to accommodate biological soft tissue constraints such as sample size, geometry imperfection and heterogeneity. The measurement technique consists of indenting an unconfined small block of tissue while measuring the resulting force. We show that the measured force-displacement slope of such a geometry can be transformed to the tissue Young's modulus via a conversion factor related to the sample's geometry and boundary conditions using finite element analysis. We also demonstrate another measurement technique for tissue elasticity based on quasi-static magnetic resonance elastography in which a tissue specimen encased in a gelatine-agarose block undergoes cyclical compression with resulting displacements measured using a phase contrast MRI technique. The tissue Young's modulus is then reconstructed from the measured displacements using an inversion technique. Finally, preliminary elasticity measurement results of various breast tissues are presented and discussed.

https://iopscience.iop.org/article/10.1088/0031-9155/48/14/310/pdf

Measuring the elastic modulus of ex vivo small tissue samples

Image-guided neurosurgery relies on accurate registration of the patient, the preoperative image series, and the surgical instruments in the same coordinate space. Recent clinical reports have documented the magnitude of gravity-induced brain deformation in the operating room and suggest these levels of tissue motion may compromise the integrity of such systems. The authors are investigating a model-based strategy which exploits the wealth of readily-available preoperative information in conjunction with intraoperatively acquired data to construct and drive a three dimensional (3-D) computational model which estimates volumetric displacements in order to update the neuronavigational image set. Using model calculations, the preoperative image database can be deformed to generate a more accurate representation of the surgical focus during an operation. In this paper, the authors present a preliminary study of four patients that experienced substantial brain deformation from gravity and correlate cortical shift measurements with model predictions. Additionally, they illustrate their image deforming algorithm and demonstrate that preoperative image resolution is maintained. Results over the four cases show that the brain shifted, on average, 5.7 mm in the direction of gravity and that model predictions could reduce this misregistration error to an average of 1.2 mm.

http://bmlweb.vuse.vanderbilt.edu/~migami/PUBS/TMI1999a.pdf

J.M. Lemery

Papers

Model-updated image guidance: initial clinical experiences with gravity-induced brain deformation