ESMRMB 2013, 30th Annual Scientific Meeting,Toulouse, France, 3-5 October: Abstracts,Thursday

After the very successful clinical introduction of combined PET/CT imaging a decade ago, a hardware combination of PET and MR is following suit. Today, three different approaches towards integrated PET/MR have been proposed: (1) a triple-modality system with a 3T MRI and a time-of-flight PET/CT installed in adjacent rooms, (2) a tandem system with a 3T MRI and a time-of-flight PET/CT in a co-planar installation with a joint patient handling system, and (3) a fully-integrated system with a whole-body PET system mounted inside a 3T MRI system. This special issue of MAGMA brings together contributions from key experts in the field of PET/MR, PET/CT and CT. The various papers share the author’s perspectives on the state-of-the-art PET/MR imaging with any of the three approaches mentioned above. In addition to several reviews discussing advantages and challenges of combining PET and MRI for clinical diagnostics, first clinical data are also presented. We expect this special issue to nurture future improvements in hardware, clinical protocols, and efficient post-processing strategies to further assess the diagnostic value of combined PET/MR imaging. It remains to be seen whether a so-called “killer application” for PET/MRI will surface. In that case PET/MR is likely to excel in pre-clinical and selected research applications for now. This special issue helps the readers to stay on track of this exciting development.     

PET–MR imaging using a tri-modality PET/CT–MR system with a dedicated shuttle in clinical routine

Tri-modality PET/CT–MRI includes the transfer of the patient on a dedicated shuttle from one system into the other. Advantages of this system include a true CT-based attenuation correction, reliable PET-quantification and higher flexibility in patient throughput on both systems. Comparative studies of PET/MRI versus PET/CT are readily accomplished without repeated PET with a different PET scanner at a different time point. Additionally, there is a higher imaging flexibility based on the availability of three imaging modalities, which can be combined for the characterization of the disease. The downside is a somewhat higher radiation dose of up to 3 mSv with a low dose CT based on the CT-component, longer acquisition times and potential misalignment between the imaging components. Overall, the tri-modality PET/CT–MR system offers comparative studies using the three different imaging modalities in the same patient virtually at the same time, and may help to develop reliable attenuation algorithms at the same time.     

PET/MRI in cancer patients: first experiences and vision from Copenhagen

Combined PET/MRI systems are now commercially available and are expected to change the medical imaging field by providing combined anato-metabolic image information. We believe this will be of particular relevance in imaging of cancer patients. At the Department of Clinical Physiology, Nuclear Medicine & PET at Rigshospitalet in Copenhagen we installed an integrated PET/MRI in December 2011. Here, we describe our first clinical PET/MR cases and discuss some of the areas within oncology where we envision promising future application of integrated PET/MR imaging in clinical routine. Cases described include brain tumors, pediatric oncology as well as lung, abdominal and pelvic cancer. In general the cases show that PET/MRI performs well in all these types of cancer when compared to PET/CT. However, future large-scale clinical studies are needed to establish when to use PET/MRI. We envision that PET/MRI in oncology will prove to become a valuable addition to PET/CT in diagnosing, tailoring and monitoring cancer therapy in selected patient populations.     

Image artifacts from MR-based attenuation correction in clinical, whole-body PET/MRI

Purpose

Integrated whole-body PET/MRI tomographs have become available. PET/MR imaging has the potential to supplement, or even replace combined PET/CT imaging in selected clinical indications. However, this is true only if methodological pitfalls and image artifacts arising from novel MR-based attenuation correction (MR-AC) are fully understood.

Results

Here we present PET/MR image artifacts following routine MR-AC, as most frequently observed in clinical operations of an integrated whole-body PET/MRI system.

Conclusion

A clinical adoption of integrated PET/MRI should entail the joint image display and interpretation of MR data, MR-based attenuation maps and uncorrected plus attenuation-corrected PET images in order to recognize potential pitfalls from MR-AC and to ensure clinically accurate image interpretation.     

Evaluation of an attenuation correction method for PET/MR imaging of the head based on substitute CT images

Object

The aim of this study was to evaluate MR-based attenuation correction of PET emission data of the head, based on a previously described technique that calculates substitute CT (sCT) images from a set of MR images.

Materials and methods

Images from eight patients, examined with ¹⁸F-FLT PET/CT and MRI, were included. sCT images were calculated and co-registered to the corresponding CT images, and transferred to the PET/CT scanner for reconstruction. The new reconstructions were then compared with the originals. The effect of replacing bone with soft tissue in the sCT-images was also evaluated.

Results

The average relative difference between the sCT-corrected PET images and the CT-corrected PET images was 1.6 % for the head and 1.9 % for the brain. The average standard deviations of the relative differences within the head were relatively high, at 13.2 %, primarily because of large differences in the nasal septa region. For the brain, the average standard deviation was lower, 4.1 %. The global average difference in the head when replacing bone with soft tissue was 11 %.

Conclusion

The method presented here has a high rate of accuracy, but high-precision quantitative imaging of the nasal septa region is not possible at the moment.     

Sequential whole-body PET/MR scanner: concept, clinical use, and optimisation after two years in the clinic. The manufacturer’s perspective

PET and MRI are established clinical tools which provide complementary information, but clinical workflow limits widespread clinical application of both modalities in combination. The two modalities are usually situated in different hospital departments and operated and reported independently, and patients are referred for both scans, often consecutively. With the advent of PET/MR as a new hybrid imaging modality there is now a possibility of addressing these concerns. There are two different design philosophies for integrated PET/MR imaging—positioning PET inside the MRI magnet or in tandem, similar to PET/CT. The Ingenuity TF PET/MR by Philips Healthcare is a sequential PET/MR tomograph combining state-of-the-art time-of-flight PET and high-field MRI with parallel transmission capabilities. In this review article we describe the technology implemented in the system, for example RF and magnetic shielding, MR-based attenuation correction, peculiarities in scatter correction, MR system optimisation, and the philosophy behind its design. Furthermore, we provide an overview of how the system has been used during the last two years, and expectations of how the use of PET/MR may continue in the years to come. On the basis of these observations and experiences we discuss the utility of the system, clinical workflow and acquisition times, and possible ways of optimization.     

Principles and methods for automatic and semi-automatic tissue segmentation in MRI data

The development of magnetic resonance imaging (MRI) revolutionized both the medical and scientific worlds. A large variety of MRI options have generated a huge amount of image data to interpret. The investigation of a specific tissue in 3D or 4D MR images can be facilitated by image processing techniques, such as segmentation and registration. In this work, we provide a brief review of the principles and methods that are commonly applied to achieve superior tissue segmentation results in MRI. The impacts of MR image acquisition on segmentation outcome and the principles of selecting and exploiting segmentation techniques tailored for specific tissue identification tasks are discussed. In the end, two exemplary applications, breast and fibroglandular tissue segmentation in MRI and myocardium segmentation in short-axis cine and real-time MRI, are discussed to explain the typical challenges that can be posed in practical segmentation tasks in MRI data. The corresponding solutions that are adopted to deal with these challenges of the two practical segmentation tasks are thoroughly reviewed.     

Does PET/MR in human brain imaging provide optimal co-registration? A critical reflection

The introduction of hybrid positron emission/magnetic resonance tomography (PET/MR) in diagnostic clinical imaging was a major step in the evolution of ever-more sophisticated imaging systems combining two strategies formerly regarded as technically incompatible in a single device. The advent of PET/MR opened up many new avenues in clinical and research environments, mainly by providing multi-modality images obtained during a single examination. Ideally, simultaneous data acquisition with hybrid PET/MR should warrant exact image co-registration of all multi-modality image volumes provided by both systems. This assumes that there is negligible mutual electronic, technical and logistical interference on the respective simultaneous measurements. Recently, such hybrid dedicated head and whole-body systems were successfully applied in an increasing number of cases. When employed for brain imaging, PET/MR has the potential to provide high-resolution multi-modality datasets. However, it also demands careful consideration of the multitude of features offered, as well as the limitations. There are open issues that have to be considered, such as the handling of patient motion during extended periods of data acquisition, optimized sampling of derived images to ease the visual interpretation and quantitative evaluation of co-registered images. This paper will briefly summarize the current status of PET/MR within the framework of developments for image co-registration and discuss current limitations and future perspectives.     

Challenges and current methods for attenuation correction in PET/MR

Quantitative PET imaging requires an attenuation map to correct for attenuation. In stand-alone PET or PET/CT, the attenuation map is usually derived from a transmission scan or CT image, respectively. In PET/MR, these methods will most likely not be used. Therefore, attenuation correction has long been regarded as one of the major challenges in the development of PET/MR. In the past few years, much progress has been made in this field. In this review, the challenges faced in attenuation correction for PET/MR are discussed. Different methods have been proposed to overcome these challenges. An overview of the MR-based (template-based and voxel-based), transmission-based and emission-based methods and the results that have been obtained is provided. Although several methods show promising results, no single method fulfils all of the requirements for the ideal attenuation correction method for PET/MR. Therefore, more work is still necessary in this field. To allow implementation in routine clinical practice, extensive evaluation of the proposed methods is necessary to demonstrate robustness and automation.     

Tissue classification and segmentation of MR images

Previously reported classification or segmentation methods are reviewed, and some statistical approaches that may be capable of automatically classifying tissues and segmenting magnetic resonance (MR) images are discussed. The image segmentation methods reviewed are edge detection methods and region detection methods. The key feature of statistical approaches toward automatically classifying tissues and segmenting MR images is the determination of the number of image classes and the model parameters of these classes from the image data directly by a computer. Any free parameter requiring extensive user interactions should be avoided. Further research on the Gaussian Markov random field (GMRF) model and the MRF penalty term will push the statistical approaches further along the automatic track. As these approaches become more practical they will become more valuable     

Potential influence of Gadolinium contrast on image segmentation in MR-based attenuation correction with Dixon sequences in whole-body 18F-FDG PET/MR

Objective

To evaluate the influence of Gadolinium contrast agent on image segmentation in magnetic resonance (MR)-based attenuation correction (AC) with four-segment dual-echo time Dixon-sequences in whole-body [18F]-fluorodeoxyglucose positron emission tomography (PET)/MR imaging, and to analyze the consecutive effect on standardized uptake value (SUV).

Materials and methods

Hybrid imaging with an integrated PET/MR system was performed in 30 oncological patients. AC was based on MR imaging with a Dixon sequence with subsequent automated image segmentation. AC maps (µmaps) were acquired and reconstructed prior to (µmap_?gd) and after (µmap_+gd) Gd-contrast agent application. For quantification purposes, the SUV of organs and tumors based on both µmaps were compared.

Results

Tissue classification based on µmap_?gd was correct in 29/30 patients; based on µmap_+gd, the brain was falsely classified as fat in 12/30 patients with significant underestimation of SUV. In all cancerous lesions, tissue segmentation was correct. All concordant µmaps_?gd/+gd resulted in no significant difference in SUV.

Conclusion

In PET/MR, Gd-contrast agent potentially influences fat/water separation in Dixon-sequences of the head with above-average false tissue segmentation and an associated underestimation of SUV. Thus, MR-based AC should be acquired prior to Gd-contrast agent application. Additionally, integrating the MR-based AC maps into the reading-routine in PET/MR is recommended to avoid interpretation errors in cases where tissue segmentation fails.

     

Comparative evaluation of active contour model extensions for automated cardiac MR image segmentation by regional error assessment

OBJECTIVE: In the field of cardiac MR image segmentation, active contour models, or snakes have been extensively used, owing to their promising results and to the numerous extensions proposed to improve their performance. This paper explores a methodology for evaluating cardiac MR image segmentation algorithms, which assesses the distance between computer-generated and the observer's hand-outlined boundaries. This metric was applied to various external force extensions of the traditional snake, since no systematic comparison has been performed. MATERIALS AND METHODS: Cardiac MRI from six patients were analyzed. Imaging was performed on a 1.5 T MR scanner with ECG-gated balanced steady-state free precession (b-SSFP) sequences. Segmentation performances were established for traditional snake, gradient vector flow snake, standard- and guided- pressure force-based snake. The use of a pre-treatment with non-linear anisotropic filtering was also compared to non-filtered images. RESULTS: Agreement between manual and segmentation algorithms was satisfactory for ejection fraction for every segmentation scheme. However end-systolic and end-diastolic volumes were systematically underestimated. CONCLUSION: The developed regional error metric provided a more rigorous evaluation of the segmentation schemes in comparison to the classical derived parameters based on left ventricle volume estimation, usually used in functional cardiac MR studies. These derived parameters can furthermore mask local segmentation errors.     

基于多阈值分割和B样条插值的CT图像金属伪影去除方法研究

为了解决重建后CT(computed tomography)图像中出现的金属伪影问题,提出了基于多阈值分割和B样条插值的CT图像金属伪影去除方法。首先,介绍了CT图像中金属伪影产生的原因;然后详细剖析基于多阈值分割和B样条插值的CT图像金属伪影去除方法实施过程;最后,使用于基于多阈值分割和B样条插值的CT图像金属伪影去除方法对含有金属伪影的临床CT图像和模拟phantom图像进行实验。实验表明,提出的CT图像金属伪影去除方法能够有效地对CT图像中的金属伪影进行减少或去除,这将为医务工作诊断病灶提供了清晰的CT图像。     

3D image understanding in radiology

The role of 3-D imaging in medicine and the questions it raises regarding what should be automated and how the information is to be used are addressed. The discussion then turns to imagery generated by equipment using computed tomography (CT), magnetic resonance (MR) images, or positron/single-photon emission tomograms (PET/SPECT). Such image data are considered as spatial image sequences. Low-level and high-level processing for spatial image sequence understanding are examined. Conclusions are drawn regarding the value of 3-D imaging and the issues to be considered in its future development.     

A scale space based algorithm for automated segmentation of single shot tagged MRI of shearing deformation

Object

This study proposes a scale space based algorithm for automated segmentation of single-shot tagged images of modest SNR. Furthermore the algorithm was designed for analysis of discontinuous or shearing types of motion, i.e. segmentation of broken tag patterns.

Materials and methods

The proposed algorithm utilises non-linear scale space for automatic segmentation of single-shot tagged images. The algorithm's ability to automatically segment tagged shearing motion was evaluated in a numerical simulation and in vivo. A typical shearing deformation was simulated in a Shepp-Logan phantom allowing for quantitative evaluation of the algorithm's success rate as a function of both SNR and the amount of deformation. For a qualitative in vivo evaluation tagged images showing deformations in the calf muscles and eye movement in a healthy volunteer were acquired.

Results

Both the numerical simulation and the in vivo tagged data demonstrated the algorithm’s ability for automated segmentation of single-shot tagged MR provided that SNR of the images is above 10 and the amount of deformation does not exceed the tag spacing. The latter constraint can be met by adjusting the tag delay or the tag spacing.

Conclusion

The scale space based algorithm for automatic segmentation of single-shot tagged MR enables the application of tagged MR to complex (shearing) deformation and the processing of datasets with relatively low SNR.     

Quantitative accuracy of attenuation correction in the Philips Ingenuity TF whole-body PET/MR system: a direct comparison with transmission-based attenuation correction

Objective

Evaluation of the quantitative accuracy of MR-based attenuation correction (MRAC) in the Philips Ingenuity TF whole-body PET/MR.

Materials and methods

In 13 patients, PET emission data from the PET/MR were reconstructed using two different methods for attenuation correction. In the first reconstruction, the vendor-provided standard MRAC was used. In the second reconstruction, a coregistered transmission-based attenuation map from a second immediately preceding investigation with a stand-alone Siemens ECAT EXACT HR⁺ PET scanner was used (TRAC). The two attenuation maps were compared regarding occurrence of segmentation artifacts in the MRAC procedure. Standard uptake values (SUVs) of multiple VOIs (liver, cerebellum, hot focal structures at various locations in the trunk) were compared between both reconstructed data sets. Furthermore, a voxel-wise intensity correlation analysis of both data sets in the lung and trunk was performed.

Results

VOI averaged SUV differences between MRAC and TRAC were as follows (relative differences, mean ± standard deviation): (+12 ± 6) % cerebellum, (?4 ± 9) % liver, (?2 ± 11) % hot focal structures. The fitted slopes of the voxel-wise correlations in the lung and trunk were 0.87 ± 0.17 and 0.95 ± 0.10 with averaged adjusted R ² values of 0.96 and 0.98, respectively. These figures include two instances with partially erroneous lung segmentation due to artifacts in the underlying MR images.

Conclusion

The MR-based attenuation correction implemented on the Philips Ingenuity PET/MR provides reasonable quantitative accuracy. On average, deviations from TRAC-based results are small (on the order of 10 %  or below) across the trunk, but due to interindividual variability of the segmentation quality, deviations of more than 20 %  can occur. Future improvement of the segmentation quality would help to increase the quantitation accuracy further and to reduce the inter-subject variability.     

MR imaging of the prostate in clinical practice

Magnetic resonance imaging (MRI) is the imaging tool of choice in the evaluation of prostate cancer. The main applications of MR imaging in the management of prostate cancer are: (1) to guide targeted biopsy when prostate cancer is clinically suspected and previous ultrasound-guided biopsy results are negative; (2) to localize and stage prostate cancer and provide a roadmap for treatment planning; and (3) to detect residual or locally recurrent cancer after treatment. Other MR techniques such as proton MR spectroscopic imaging (MRSI), diffusion-weighted imaging (DWI), and contrast-enhanced MRI (CE-MRI) complement conventional MR imaging by providing metabolic and functional information that can improve the accuracy of prostate cancer detection and characterization. In everyday clinical practice, and to account for patient comfort, MR imaging studies are limited to 1 h. To obtain consistently high-quality images, a well-designed protocol is necessary. Routine MR imaging can be supplemented by other MR techniques such as MRSI, DWI or CE-MRI depending on the expertise available and the clinical questions that need to be answered. This review summarizes the role of MR imaging in the management of prostate cancer and describes practical approaches to implementing anatomic, metabolic and functional MR imaging techniques in the clinic.     

Segmentation of the human spinal cord

Segmenting the spinal cord contour is a necessary step for quantifying spinal cord atrophy in various diseases. Delineating gray matter (GM) and white matter (WM) is also useful for quantifying GM atrophy or for extracting multiparametric MRI metrics into specific WM tracts. Spinal cord segmentation in clinical research is not as developed as brain segmentation, however with the substantial improvement of MR sequences adapted to spinal cord MR investigations, the field of spinal cord MR segmentation has advanced greatly within the last decade. Segmentation techniques with variable accuracy and degree of complexity have been developed and reported in the literature. In this paper, we review some of the existing methods for cord and WM/GM segmentation, including intensity-based, surface-based, and image-based methods. We also provide recommendations for validating spinal cord segmentation techniques, as it is important to understand the intrinsic characteristics of the methods and to evaluate their performance and limitations. Lastly, we illustrate some applications in the healthy and pathological spinal cord. One conclusion of this review is that robust and automatic segmentation is clinically relevant, as it would allow for longitudinal and group studies free from user bias as well as reproducible multicentric studies in large populations, thereby helping to further our understanding of the spinal cord pathophysiology and to develop new criteria for early detection of subclinical evolution for prognosis prediction and for patient management. Another conclusion is that at the present time, no single method adequately segments the cord and its substructure in all the cases encountered (abnormal intensities, loss of contrast, deformation of the cord, etc.). A combination of different approaches is thus advised for future developments, along with the introduction of probabilistic shape models. Maturation of standardized frameworks, multiplatform availability, inclusion in large suite and data sharing would also ultimately benefit to the community.     

A PC-based workstation for processing and analysis of MRI data

The present work demonstrates that a low cost, flexible and user-friendly workstation for the MRI laboratory can be implemented by using a personal computer and public-domain software. The workstation is based on a Pentium^® personal computer, operating under the Linux operative system, and uses the software Khoros^® (Khoral Research, Albuquerque, NM). This software is a general purpose package for handling signals and we here report its suitability for MR images analysis. Khoros^® allows to create workspaces where different procedures (also written by the users) can be combined for implementing more complex procedures. We created workspaces for obtaining 2D and 3D images from time domain data which also allow for apodization and zero-filling. The time required for a 3D-FFT (matrix size 128×128×128) is about 12 min with the presently used microprocessor. We have also created workspaces for calculating apparent diffusion coefficient maps and for segmentation of MR images. Our results demonstrate that a personal computer equipped with public-domain software can represent a powerful tool to fulfil the MRI laboratory common needs.     

Knowledge-based 3D analysis from 2D medical images

An anatomical knowledge-based system for image analysis that interprets CT/MR (computed tomography/magnetic resonance) images of the human chest cavity is reported. The approach utilizes a low-level image analysis system with the ability to analyze the data in bottom-up (or data-driven) and top-down (or model-driven) modes to improve the high-level recognition process. Several image segmentation algorithms, including K-means clustering, pyramid-based region extraction, and rule-based merging, are used for obtaining the segmented regions. To obtain a reasonable number of well-segmented regions that have a good correlation with the anatomy, a priori knowledge in the form of masks is used to guide the segmentation process. Segmentation of the brain is also considered.