Coregistration of brain single-positron emission computed tomography and magnetic resonance images using anatomical features

Medical Image Fusion using bi-dimensional empirical mode decomposition (BEMD) and an Efficient Fusion Scheme

Background

Medical image fusion is being widely used for capturing complimentary information from images of different modalities. Combination of useful information presented in medical images is the aim of image fusion techniques, and the fused image will exhibit more information in comparison with source images.

Objective

In the current study, a BEMD-based multi-modal medical image fusion technique is utilized. Moreover, Teager-Kaiser energy operator (TKEO) was applied to lower BIMFs. The results were compared to six routine methods.

Material and Methods

In this study, which is of experimental type, an image fusion technique using bi-dimensional empirical mode decomposition (BEMD), Teager-Kaiser energy operator (TKEO) as a local feature selection and Hierarchical Model And X (HMAX) model is presented. BEMD fusion technique can preserve much functional information. In the process of fusion, we adopt the fusion rule of TKEO for lower bi-dimensional intrinsic mode functions (BIMFs) of two images and HMAX visual cortex model as a fusion rule for higher BIMFs, which are verified to be more appropriate for human vision system. Integrating BEMD and this efficient fusion scheme can retain more spatial and functional features of input images.

Results

We compared our method with IHS, DWT, LWT, PCA, NSCT and SIST methods. The simulation results and fusion performance show that the presented method is effective in terms of mutual information, quality of fused image (QAB/F), standard deviation, peak signal to noise ratio, structural similarity and considerably better results compared to six typical fusion methods.

Conclusion

The statistical analyses revealed that our algorithm significantly improved spatial features and diminished the color distortion compared to other fusion techniques. The proposed approach can be used for routine practice. Fusion of functional and morphological medical images is possible before, during and after treatment of tumors in different organs. Image fusion can enable interventional events and can be further assessed.

Magnetic resonance imaging in radiotherapy treatment target volumes definition for brain tumours: a systematic review and meta-analysis

Purpose

The aim of this study is to establish clinical evidence regarding the use of magnetic resonance imaging (MRI) in target volume definition for radiotherapy treatment planning of brain tumours.

Methods

Primary studies were systematically retrieved from six electronic databases and other sources. Studies included were only those that quantitatively compared computed tomography (CT) and MRI in target volume definition for radiotherapy of brain tumours. Study characteristics and quality were assessed and the data were extracted from eligible studies. Effect estimates for each study was computed as mean percentage difference based on individual patient data where available. The included studies were then combined in meta-analysis using Review Manager (RevMan) software version 5.0.

Result

Five studies with a total number of 72 patients were included in this review. The quality of the studies was rated strong. The percentages mean differences of the studies were 7·47, 11·36, 30·70, 41·69 and −24·6% using CT as the baseline. The result of statistical analysis showed small-to-moderate heterogeneity; τ2=36·8; χ2=6·23; df=4 (p=0·18); I2=36%. The overall effect estimate was −1·85 [95% confidence interval (CI); −7·24, 10·94], Z=0·40 (p=0·069>0·5).

Conclusion

Brain tumour volumes measured using MRI-based method for radiotherapy treatment planning were larger compared with CT defined volumes but the difference lacks statistical significance.

Feasibility of fused imaging for the evaluation of radiofrequency ablative margin for hepatocellular carcinoma

AIM

To evaluate the feasibility of fusion of conventional imaging modalities to facilitate assessment of ablative margin of radiofrequency ablation (RFA) of hepatocellular carcinoma (HCC).

METHODS

Two hundred and thirty-nine liver lesions in 109 patients underwent percutaneous RFA under ultrasound for HCC from January 2008 to December 2010. Within these patients, 13 lesions in 12 patients who developed local tumor progression in the follow-up period of at least 8 months were retrospectively reviewed. Imaging obtained before and after RFA was used for creating fused images on a workstation. Ablative margins were assessed using only axial images, and with fused images.

RESULTS

The ablative margin was assessed as sufficient in all 13 lesions using side-by-side axial images; however, all lesions were assessed as insufficient with fused imaging evaluation. The reason for the discrepancy of the assessment results were differences in the respiratory dislocation of the liver in the pre- and post-RFA images in eight lesions (61.5%), and rotational displacement of the liver and the torso in five (38.5%). The site of local tumor recurrence relative to the HCC lesion was craniocaudal in 12 lesions, dorsoventral in seven and lateral in seven. In all lesions, the site of local tumor recurrence was congruent with the area of the thinnest ablative margin.

CONCLUSION

Assessment of ablative margin with fused imaging revealed insufficiency of ablation previously evaluated as sufficient with conventional axial imaging. Fused imaging evaluation has proved to be an accurate and useful tool for the assessment of RFA margins.

Image fusion using CT, MRI and PET for treatment planning, navigation and follow up in percutaneous RFA

AIM

To evaluate the feasibility of fusion of morphologic and functional imaging modalities to facilitate treatment planning, probe placement, probe re-positioning, and early detection of residual disease following radiofrequency ablation (RFA) of cancer.

METHODS

Multi-modality datasets were separately acquired that included functional (FDG-PET and DCE-MRI) and standard morphologic studies (CT and MRI). Different combinations of imaging modalities were registered and fused prior to, during, and following percutaneous image-guided tumor ablation with radiofrequency. Different algorithms and visualization tools were evaluated for both intra-modality and inter-modality image registration using the software MIPAV (Medical Image Processing, Analysis and Visualization). Semi-automated and automated registration algorithms were used on a standard PC workstation: 1) landmark-based least-squares rigid registration, 2) landmark-based thin-plate spline elastic registration, and 3) automatic voxel-similarity, affine registration.

RESULTS

Intra- and inter-modality image fusion were successfully performed prior to, during and after RFA procedures. Fusion of morphologic and functional images provided a useful view of the spatial relationship of lesion structure and functional significance. Fused axial images and segmented three-dimensional surface models were used for treatment planning and post-RFA evaluation, to assess potential for optimizing needle placement during procedures.

CONCLUSION

Fusion of morphologic and functional images is feasible before, during and after radiofrequency ablation of tumors in abdominal organs. For routine use, the semi-automated registration algorithms may be most practical. Image fusion may facilitate interventional procedures like RFA and should be further evaluated.

Virtual Reality Neurosurgery: A Simulator Blueprint

OBJECTIVE

This article details preliminary studies undertaken to integrate the most relevant advancements across multiple disciplines in an effort to construct a highly realistic neurosurgical simulator based on a distributed computer architecture. Techniques based on modified computational modeling paradigms incorporating finite element analysis are presented, as are current and projected efforts directed toward the implementation of a novel bidirectional haptic device.

METHODS

Patient-specific data derived from noninvasive magnetic resonance imaging sequences are used to construct a computational model of the surgical region of interest. Magnetic resonance images of the brain may be coregistered with those obtained from magnetic resonance angiography, magnetic resonance venography, and diffusion tensor imaging to formulate models of varying anatomic complexity.

RESULTS

The majority of the computational burden is encountered in the presimulation reduction of the computational model and allows realization of the required threshold rates for the accurate and realistic representation of real-time visual animations.

CONCLUSION

Intracranial neurosurgical procedures offer an ideal testing site for the development of a totally immersive virtual reality surgical simulator when compared with the simulations required in other surgical subspecialties. The material properties of the brain as well as the typically small volumes of tissue exposed in the surgical field, coupled with techniques and strategies to minimize computational demands, provide unique opportunities for the development of such a simulator. Incorporation of real-time haptic and visual feedback is approached here and likely will be accomplished soon.