Clinical Research

The Imaging Research Laboratory is funded to explore improvements and evaluate the quantitation in nuclear medicine imaging. 

Recent Selected Abstracts:

Compensating respiratory blurring in PET/CT imaging with the registration-and-summed-phase (RASP) method

Lawrence R. MacDonald, Paul E. Kinahan, Adam M. Alessio, Tsui Segars
American Roentgen Ray Society, 106th Annual Meeting
April 30-May 5, 2006 Vancouver, BC, Canada

Purpose: PET/CT imaging has introduced new challenges in accurate quantitation of lung nodules due to respiratory motion and mismatches in CT-based attenuation correction (CTAC). We used Monte Carlo simulations to investigate how attenuation correction (AC) methods for PET can be optimized to account for mis-registration between the CTAC data and the PET data due to respiratory motion. This is a first step in developing a method of compensating for respiratory motion by non-rigid image registration and summation of separate respiratory phases (RASP).

Materials and Methods: The NCAT digital phantom was used to generate anthropomorphic distributions of radiotracer and linear attenuation coefficients that were used as source emission and attenuation data. A 2-cm diameter lesion, positioned in the lower right lung just above the liver, was added to the NCAT anatomy. The NCAT phantom models respiratory motion; Ten sets of both PET and CTAC data were generated at 0.5 sec. intervals covering one respiratory cycle. Simulated sinograms modeled the PET measurement process including the effects of attenuation, photon noise, and CTAC The processed sinograms were then reconstructed with filtered backprojection with a Hanning filter. This process was repeated using a single respiratory frame for both PET and CTAC data (ideal case with RASP) and the same single frame CTAC data and the respiratory averaged PET data (current PET/CT CTAC method).

Results: Images that used the current method of CT-based attenuation correction in PET/CT imaging clearly showed distortions of the simulated lesion. This was caused by the respiratory mismatch between the respiratory averaged PET data and the single 'snapshot', or respiratory phase, of the CTAC data. Images that used phase-matched data removed these distortions.

Conclusions: The idea of respiratory phase alignment and summing in PET/CT imaging can significantly improve image quality in terms of image fidelity and SNR.

Consistency driven respiratory phase alignment and motion compensation in PET/CT

Adam M. Alessio, Steven G. Kohlmyer, and Paul E. Kinahan
IEEE Nuclear Science Symposium and Medical Imaging Conference
2007, Honolulu, HI

Respiratory motion in PET/CT imaging degrades PET image quantitation due to misaligned attenuation correction (AC) factors and motion blurring.
This work explores the use of the Radon consistency conditions to compensate for these limitations in respiratory gated PET images in which only a single CT scan is available for AC.  Specifically, we use the Radon consistency of AC-PET data as a metric to transform the attenuation map to match each phase of respiratory gated data, perform phase matched AC, and then use the inverse of the transformation parameters to align the gated PET images into a single phase.  A final image volume is formed from summing PET images aligned to a single phase.  We test this method with three transformation types applied to simulated data and measured patient PET/CT data.  Results show successful alignment of attenuation maps and minor quantitative improvement with the proposed methods.
 

 

Coronal views of attenuation map transformed to respiratory bin 1 of 5 (row 1), AC-PET image from bin 3 of 5 (row 2), and PET image summed across all 5 respiratory bins (row 3). The PET images were attenuation corrected either with a single helical CT, similar to current clinical practice (a), or with different transformations of the single attenuation map to each phase (b,c,d).

Application of a spatially variant system model for 3-D whole-body PET image reconstruction

Adam M. Alessio and Paul E. Kinahan
IEEE International Symposium on Biomedical Imaging
2008, Paris, France
Accurate system modeling in tomographic image reconstruction has been shown to reduce the spatial variance of resolution and improve quantitative accuracy.  System modeling can be improved through analytic calculations, Monte Carlo simulations, and physical measurements. This work presents a novel measured system model and incorporates this model into a fully 3-D statistical reconstruction method. Empirical testing of the resolution versus noise benefits reveal a modest improvement in spatial resolution at matched image noise levels. Convergence analysis demonstrate improved resolution and contrast versus noise properties can be achieved with the proposed method with similar computation time as the conventional approach.  Images reconstructed with the proposed model contain correlated noise structures which are difficult to characterize with accepted NEMA noise metrics.

Initial experience with weight-based, low-dose pediatric PET/CT protocols

Adam M. Alessio, Vivek Manchanda, Paul E. Kinahan, Victor Ghioni, Lisa Aldape, Joshua Busch, Marguerite Parisi
Journal of Nuclear Medicine (abstract to appear), 2008

Objectives: To develop pediatric PET/CT acquisition protocols customized to patient weight and estimate the dosimetry of these low-dose protocols.

Method: FDG-PET CT scans were performed on 45 patients weighing 9.2-109kg (aged 1.4-23 years).  These patients were scanned first in PET mode with a weight-based injected activity (0.144mCi/kg, 1mCi minimum/10mCi maximum) and acquisition times (3-5 min/FOV) and then received a CT for attenuation correction (CTAC, 120kVp) with a weight-based tube current ranging from 10-40mAs.  Patients were categorized based on the Braslow color-coded weight scale with 11 categories defining different acquisition settings.  Dosimetry for the PET and CTAC acquisition in each category was derived from mean patient sizes and the interpolation of scaling terms for accepted 1,5, 10, 15 year old, and adult models. 

Results: Whole-body PET/CT acquisitions using the proposed weight-based protocols result in an approximate total effective dose of 5.4mSv for 9 kg 70cm patient up to 10.0 mSv for a 70kg 170cm patient.  The effective dose from the proposed CTAC was on average a factor a 3.4 less than a conventional diagnostic abdomen CT and was on average 25% of the total dose from the entire PET/CT exam. Qualitative review of these exams revealed that all CTAC’s performed were acceptable to perform PET localization and serve as an anatomical reference. 

Conclusions: Low-dose PET/CT protocols for 11 patient weight categories were developed and implemented in our clinic. The use of 11 categories as opposed to fewer categories allows for refinement of maximum CTAC tube current to minimize dose while maintaining image quality.  Future effort will determine optimal PET acquisition durations and further refine CT tube voltage and current for each category.

Quantitative PET myocardial perfusion through integrated volume manipulation, display, and modeling

Adam M. Alessio, Erik Butterworth, James Caldwell, and James Bassingthwaighte
Workshop on Multi-scale Modeling of the Heart
March 2008, Auckland, NZ

bloodflow

Integration of multiple post-processing steps with physiologic modeling will result in reduced variance and bias in estimated parameters.  With positron emission tomography (PET), myocardial blood flow can be estimated with a variety of validated perfusion models for several tracers.  These models are applied after several independently-run processing steps: raw data correction, image reconstruction, image reorientation, myocardial segmentation, region-of-interest placement, and then model optimization. By combining several sequential steps we take advantage of the case-dependent nature of the data to gain efficiency and automate the modeling analysis to estimate regional flows. For example, to take advantage of the fractal nature of myocardial flow distributions with neighboring regions having similar flows, we analyze relatively large regions first to obtain initial estimates of parameters for estimating flow in subregions.  Thus, we have developed an integrated platform for myocardial perfusion, which will allow for the exploration of synergies between post-processing steps and the rapid testing of novel blood flow models. Future improvements will seek to include wall motion models in the processing chain and the collection of all steps into a complete imaging and physiologic system model for parametric estimation directly from raw PET measurements.

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