Atlas-guided non-uniform attenuation correction in cerebral 3D PET imaging
Introduction
Functional brain imaging using single-photon emission computed tomography (SPECT) and positron emission tomography (PET) has steadily gained importance both in clinical setting and research environment over the past few years. Reliable subjective qualitative visual interpretation and accurate objective quantitative analysis of functional brain images rely heavily on the intrinsic performance parameters of the PET scanner and the computational models used to correct the data for physical degrading factors. There is in general a consensus among the nuclear medicine community that photon attenuation is the dominant physical degrading factor besides contribution from scattered photons and other associated errors (Zaidi and Sossi, 2004). The scientific community has witnessed an impressive development of computational models for accurate attenuation correction in PET imaging as an increasing number of clinical indications and research applications are being explored.
The accuracy achieved by the attenuation correction procedure is evidently dependent on the rigour followed to derive the attenuation map. Two broad categories of techniques have emerged: calculated methods, which are based on an assumed anatomical model representing the shape and spatial distribution of attenuation coefficients in the head and measured methods, which in general rely on an additional acquisition of a transmission scan using either positron-emitting (68Ga/68Ge) or single-photon emitting (137Cs) radionuclide sources or an X-ray tube on recently developed dual-modality PET/CT imaging systems (Zaidi and Hasegawa, 2003). It has been shown that motion-induced misalignment between pre-injection transmission and emission scans can result in erroneous estimation of regional tissue activity concentrations (van den Heuvel et al., 2003). More recently, a new method based on coregistered segmented magnetic resonance imaging (MRI) was proposed for brain imaging (Zaidi et al., 2003). The main motivation behind the development of this method is to achieve accurate attenuation correction with a transmissionless prototype brain PET tomograph. Removal of the transmission scanning component simplifies greatly the complexity of the tomograph's design and acquisition protocols and contributes significantly to lowering the cost of the prototype and the radiation dose delivered to patients and healthy subjects. In fact, the authors are involved within the Computed Imaging for Medical Applications (CIMA) collaboration in the design of a novel and innovative high-resolution Compton-enhanced 3D brain PET tomograph dedicated to brain research1 (Braem et al., 2004). This concept leads to an image reconstruction which is free of any parallax error and provides a uniform spatial and energy resolution over the whole sensitive volume. Ideally, it was planned that a 3D brain T1-weighted MRI should be acquired for all subjects participating to research protocols prior to the PET scan. It was realized afterwards that for logistic and practical organizational reasons, the MRI is not always available on the hospital picture archiving and communication system (PACS) and thus another alternative for accurate attenuation correction should be sought.
Historically, empiric calculated methods for deriving the attenuation map in functional brain imaging such as the uniform fit-ellipse method and the automated detection of the head contour followed by assignment of known attenuation coefficients (brain and surrounding skull) were proposed and implemented in software supplied by scanner manufacturers to end-users (Zaidi et al., 2004). Their limitations led to the development of more sophisticated models including the automated method computing a 3-component attenuation map (Weinzapfel and Hutchins, 2001) and the inferring anatomy from a head atlas approach (Stodilka et al., 2000). The former generates an estimated skull image by filtered backprojection of the reciprocal of an emission sinogram whose thickness and radius are estimated from profiles extracted from this image. Whereas the latter derives the attenuation map by registering the brain component of a digital head phantom of a single subject (Zubal et al., 1994) with a source distribution having appropriately scaled specific activities of the gray matter, white matter, and ventricles, to a preliminary PET reconstruction and then applying the resulting spatial transformation to the full head atlas. As reported by many investigators, the major limitation of the Zubal head phantom is that the sinus is larger than usual (Arlig et al., 2000, Stodilka et al., 2000, Zaidi et al., 2004). The method presented in this work further extends this approach and improves its robustness by constructing both transmission and tracer-specific emission atlases based on average patient populations rather than relying on an atlas based on a single subject and a hypothetical tracer distribution. The second improvement is related to application of nonlinear warping for anatomic standardization of stereotactic templates and patient images in contrast to simple global rescaling (7 parameters model) procedures used in the previous studies. In the narrow sense of the word, there is a major conceptual difference between anatomic standardization—also called spatial normalization—and coregistration (Senda, 2000). Basically, coregistration aims to match images of a single subject, usually of a different tracer or modality, through a rigid-body transformation. On the other hand, the purpose of anatomic standardization is to transform brain images of individual subjects into a standard brain. Another important difference is that the true solution exists for registration but not for anatomic standardization (Van Laere and Zaidi, 2005). Standardizing patient brain images should therefore be performed with caution (Senda, 2000). The performance of the proposed attenuation correction algorithm is evaluated using clinical data through comparison to the standard procedure used in clinical routine based on measured pre-injection transmission scanning.
Section snippets
Description of algorithm
The proposed attenuation correction algorithm uses an emission and transmission atlases and preliminary PET reconstructions of the subject's brain images to construct a non-uniform attenuation map adapted to the subject anatomy. The main advantage being that the method does not require additional acquisition of a transmission scan and does not rely on the questionable assumption of perfect coregistration between the transmission and emission scans when using a pre-injection transmission
Results
A typical plane of a patient brain attenuation map obtained with measured pre-injection transmission and atlas-guided methods are shown in Fig. 3. Horizontal profiles through the sinus cavities and middle of the slice are also shown to demonstrate quantitatively the differences between the different techniques. Note that the typical profile generated by the calculated fit-ellipse method is shown to highlight the limitations of this approach often used in clinical routine in the sense that
Discussion
There are many physiological, biochemical and pharmacological functions of the human brain that can be explored with PET imaging, using for example tracers as 18F-[FDG] to measure the metabolism of glucose, 15O-[H2O] to assess the rate of blood flow or a large and increasing library of 11C-labeled radioligands to characterize neuroreceptor function. It should be emphasized, however, that many of these applications rely on a solid quantitative foundation, which is highly dependent on the
Conclusion
A new attenuation correction method for 3D brain PET guided by transmission and tracer-specific emission atlases constructed from normal databases representative of average patient populations has been proposed. The method is suitable for either clinical routine and research applications in 3D brain PET imaging on a transmissionless PET scanner or when a transmission scan is not available. Moreover, the removal of the usual pre-injection transmission scan contribute to overall reduction of
Acknowledgments
This work was supported by the Swiss National Science Foundation under grant SNSF 3152A0-102143, the National Center of Competence in Research CO-ME and Geneva University Hospital R and D funds under grant PRD-04-1-08. This paper is dedicated to the memory of Prof. F. Terrier (Head of the Department of Radiology, Geneva University Hospital) who sadly passed away this summer.
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