Marie Foley Kijewski

CT and PET: Early Prognostic Indicators of Response to Imatinib Mesylate in Patients with Gastrointestinal Stromal Tumor

OBJECTIVE We report results from a pilot study aimed at optimizing the use of CT bidimensional measurements and 18F-FDG PET maximum standardized uptake values (SUVs-(max)) for determining response to prolonged imatinib mesylate treatment in patients with advanced gastrointestinal stromal tumors (GISTs). SUBJECTS AND METHODS Sixty-three patients enrolled in a multicenter trial evaluating imatinib mesylate therapy for advanced GIST underwent FDG PET at baseline and 1 month after initiation of treatment. Of these 63 patients, 58 underwent concomitant CT. Time-to-treatment failure (TTF) was used as the outcome measure. Patients were followed up over a range of 23.7 to 37 months (median, 31.7 months). The predictive power of change in CT bidimensional measurements, change in PET SUVmax, and PET SUVmax at 1 month after initiation of treatment were determined, optimized, and compared. The effectiveness of combining metrics was also evaluated. RESULTS Both a threshold PET SUVmax value of 2.5 at 1 month (p = 0.04) and the European Organization for Research and Treatment of Cancer (EORTC) criteria for partial response on FDG PET (25% reduction in PET SUVmax) at 1 month (p = 0.004) were predictive of prolonged treatment success. The Southwest Oncology Group (SWOG) criteria for partial response ((3) 50% reduction in CT bidimensional measurements) at 1 month were not predictive (p = 0.55) of TTF. Optimizing metrics improved results performance. An optimized PET SUVmax threshold of 3.4 (p = 0.00002), a reduction in the SUVmax of 40% (p = 0.002), and an optimized CT bidimensional measurement threshold--that is, no growth from baseline to 1 month (p = 0.00005)--outperformed the existing standards (i.e., EORTC and SWOG criteria). Combinations of metrics did not improve performance. CONCLUSION The two best metrics were the optimized PET SUVmax threshold of 3.4 at 1 month (p = 0.00002) and the optimized CT bidimensional measurement threshold (no growth from baseline to 1 month, p = 0.00005) in this patient group.

The noise power spectrum of CT images

An expression for the noise power spectrum of images reconstructed by the discrete filtered backprojection algorithm has been derived. The formulation explicitly includes sampling within the projections, angular sampling, and the two-dimensional sampling implicit in the discrete representation of the image. The effects of interpolation are also considered. Noise power spectra predicted by this analysis differ from those predicted using continuous theory in two respects: they are rotationally asymmetric, and they do not approach zero at zero frequency. Both of these properties can be attributed to two-dimensional aliasing due to pixel sampling. The predictions were confirmed by measurement of noise power spectra of both simulated images and images from a commercial x-ray transmission CT scanner.

Quantification of Myocardial Perfusion Reserve Using Dynamic SPECT Imaging in Humans: A Feasibility Study

Myocardial perfusion imaging (MPI) is well established in the diagnosis and workup of patients with known or suspected coronary artery disease (CAD); however, it can underestimate the extent of obstructive CAD. Quantification of myocardial perfusion reserve with PET can assist in the diagnosis of multivessel CAD. We evaluated the feasibility of dynamic tomographic SPECT imaging and quantification of a retention index to describe global and regional myocardial perfusion reserve using a dedicated solid-state cardiac camera. Methods: Ninety-five consecutive patients (64 men and 31 women; median age, 67 y) underwent dynamic SPECT imaging with 99mTc-sestamibi at rest and at peak vasodilator stress, followed by standard gated MPI. The dynamic images were reconstructed into 60–70 frames, 3–6 s/frame, using ordered-subsets expectation maximization with 4 iterations and 32 subsets. Factor analysis was used to estimate blood-pool time–activity curves, used as input functions in a 2-compartment kinetic model. K1 values (99mTc-sestamibi uptake) were calculated for the stress and rest images, and K2 values (99mTc-sestamibi washout) were set to zero. Myocardial perfusion reserve (MPR) index was calculated as the ratio of the stress and rest K1 values. Standard MPI was evaluated semiquantitatively, and total perfusion deficit (TPD) of at least 5% was defined as abnormal. Results: Global MPR index was higher in patients with normal MPI (n = 51) than in patients with abnormal MPI (1.61 [interquartile range (IQR), 1.33–2.03] vs. 1.27 [IQR, 1.12–1.61], P = 0.0002). By multivariable regression analysis, global MPR index was associated with global stress TPD, age, and smoking. Regional MPR index was associated with the same variables and with regional stress TPD. Sixteen patients undergoing invasive coronary angiography had 20 vessels with stenosis of at least 50%. The MPR index was 1.11 (IQR, 1.01–1.21) versus 1.30 (IQR, 1.12–1.67) in territories supplied by obstructed and nonobstructed arteries, respectively (P = 0.02). MPR index showed a stepwise reduction with increasing extent of obstructive CAD (P = 0.02). Conclusion: Dynamic tomographic imaging and quantification of a retention index describing global and regional perfusion reserve are feasible using a solid-state camera. Preliminary results show that the MPR index is lower in patients with perfusion defects and in regions supplied by obstructed coronary arteries. Further studies are needed to establish the clinical role of this technique as an aid to semiquantitative analysis of MPI.

Reversible cerebral hypoperfusion in Lyme encephalopathy

Lyme encephalopathy (LE) presents with subtle neuropsychiatric symptoms months to years after onset of infection with Borrelia burgdorferi. Brain magnetic resonance images are usually normal. We asked whether quantitative single photon emission computed tomography (SPECT) is a useful method to diagnose LE, to measure the response to antibiotic therapy, and to determine its neuroanatomic basis. In 13 patients with objective evidence of LE, SPECT demonstrated reduced cerebral perfusion (mean perfusion defect index [PDI] = 255), particularly in frontal subcortical and cortical regions. Six months after treatment with 1 month of intravenous ceftriaxone, perfusion significantly improved in all 13 patients (mean PDI = 188). In nine patients with neuropsychiatric symptoms following Lyme disease, but without objective abnormalities (e.g., possible LE), perfusion was similar to that of the treated LE group (mean PDI = 198); six possible LE patients (67%) had already received ceftriaxone prior to our evaluation. Perfusion was significantly lower in patients with LE and possible LE than in 26 normal subjects (mean PDI = 136), but 4 normal subjects (15%) had low perfusion in the LE range. We conclude that LE patients have hypoperfusion of frontal subcortical and cortical structures that is partially reversed after ceftriaxone therapy. However, SPECT cannot be used alone to diagnose LE or determine the presence of active CNS infection.

Quantitative simultaneous 99mTc-ECD/123I-FP-CIT SPECT in Parkinson’s disease and multiple system atrophy

PurposeThe purpose of this study was to investigate the feasibility and utility of dual-isotope SPECT for differential diagnosis of idiopathic Parkinson’s disease (IPD) and multiple system atrophy (MSA).MethodsSimultaneous 99mTc-ECD/123I-FP-CIT studies were performed in nine normal controls, five IPD patients, and five MSA patients. Projections were corrected for scatter, cross-talk, and high-energy penetration, and iteratively reconstructed while correcting for patient-specific attenuation and variable collimator response. Perfusion and dopamine transporter (DAT) function were assessed using voxel-based statistical parametric mapping (SPM2) and volume of interest quantitation. DAT binding potential (BP) and asymmetry index (AI) were estimated in the putamen and caudate nucleus.ResultsStriatal BP was lower in IPD (55%) and MSA (23%) compared to normal controls (p<0.01) , and in IPD compared to MSA (p<0.05). AI was greater for IPD than for MSA and controls in both the caudate nucleus and the putamen (p<0.05). There was significantly decreased perfusion in the left and right nucleus lentiformis in MSA compared to IPD and controls (p<0.05).ConclusionDual-isotope studies are both feasible in and promising for the diagnosis of parkinsonian syndromes.

Scatter and cross-talk corrections in simultaneous Tc-99m/I-123 brain SPECT using constrained factor analysis and artificial neural networks

Simultaneous imaging of Tc-99m and I-123 would have a high clinical potential in the assessment of brain perfusion (Tc-99m) and neurotransmission (I-123) but is hindered by cross-talk between the two radionuclides. Monte Carlo simulations of 15 different dual-isotope studies were performed using a digital brain phantom. Several physiologic Tc-99m and I-123 uptake patterns were modeled in the brain structures. Two methods were considered to correct for cross-talk from both scattered and unscattered photons: constrained spectral factor analysis (SFA) and artificial neural networks (ANN). The accuracy and precision of reconstructed pixel values within several brain structures were compared to those obtained with an energy windowing method (WSA). In I-123 images, mean bias was close to 10% in all structures for SFA and ANN and between 14% (in the caudate nucleus) and 25% (in the cerebellum) for WSA. Tc-99m activity was overestimated by 35% in the cortex and 53% in the caudate nucleus with WSA, but by less than 9% in all structures with SFA and ANN. SFA and ANN performed well even in the presence of high-energy I-123 photons. The accuracy was greatly improved by incorporating the contamination into the SFA model or in the learning phase for ANN. SFA and ANN are promising approaches to correct for cross-talk in simultaneous Tc-99m/I-123 SPECT.

Collimator optimization for lesion detection incorporating prior information about lesion size

A Bayesian estimator has been developed as a paradigm for human observer performance in detecting lesions of unknown size in a uniform noisy background. The Bayesian observer used knowledge of the range of possible lesion sizes as a prior; its predictions agreed well with the results of a six-observer perceptual study. The average human response to changes in collimator resolution, as measured by the detectability index, dA, was tracked by the Bayesian detectors signal-to-noise ratio (SNR) somewhat better than by two other estimation models based, respectively, on lesser and greater degrees of lesion size uncertainty. As the range of possible lesion sizes increased, the Bayesian detectors SNR decreased and the optimal collimator resolution shifted towards better resolution. An analytic approximation for the variance of lesion activity estimates (which included the same prior) was shown to predict the variance of the Bayesian estimator over a wide range of collimator resolution values. Because the bias of the Bayesian estimator was small (< 1%), the analytic variance estimate permitted a rapid and convenient prediction of the Bayesian detection SNR. This calculation was then used to optimize the geometric parameters of a two-layer tungsten collimator being constructed from crossed grids for a new imaging detector. A Monte Carlo program was first run to estimate all contributions to the radial point-spread function for collimators of differing tungsten contents and spatial resolution values, imaging 140-keV photons emitted from the center of a 15-cm-diameter, water-filled attenuator. The optimal collimator design for detecting lesions with unknown diameters in the range 2.5-7.5 mm yielded a system resolution of approximately 8.5-mm FWHM, a geometric collimator efficiency of 1.21 x 10(-4), and a single-septum penetration probability of 1%.

Impact of Acquisition Geometry, Image Processing, and Patient Size on Lesion Detection in Whole-Body 18F-FDG PET

The aim of this work was to develop a rigorous evaluation methodology to assess performance of different acquisition and processing methods for variable patient sizes in the context of lesion detection in whole-body 18F-FDG PET. Methods: Fifty-nine bed positions were acquired in 32 patients in 2-dimensional (2D) and 3-dimensional (3D) modes 1–4 h after 18F-FDG injection (740 MBq) using a BGO PET scanner. Three spheres (1.0-, 1.3-, and 1.6-cm diameter) containing 68Ge were also imaged separately in air, at locations corresponding to possible lesion sites in 2D and 3D (590 targets per condition). Each bed position was acquired for 7 min in 2D and 6 min in 3D and corrected for randoms using delayed window randoms subtraction (DWS) or randoms variance reduction (RVR). Sphere sinograms were attenuated using the 2D or 3D attenuation map derived from the transmission scan of the patient, after scaling 2D and 3D sinograms with identical factors to ensure marginal detectability. Resulting 2D sinograms were reconstructed with filtered backprojection (FBP) and ordered-subsets expectation maximization (OSEM) without any scatter or attenuation correction (FBP-NATS and OSEM-NATS) or corrected for scatter and attenuation and reconstructed using FBP (FBP-ATT) or attenuation-weighted OSEM (AWOSEM). 3D sinograms were processed identically after Fourier rebinning. Next, reconstructed volumes were compared on the basis of performance of a 3-channel Hotelling observer (CHO-SNR [SNR is signal-to-noise ratio]) in detecting the presence of a sphere of unknown size on an anatomic background while modeling observer noise. The noise equivalent count (NEC) rate was computed in 2D and 3D for 3 different phantoms sizes (40, 60, and 95 kg) and compared with lesion detection SNR. Results: 3D imaging yielded better lesion detectability than 2D (P < 0.025, 2-tailed paired t test) in patients of normal size (body mass index [BMI] ≤ 31). However, 2D imaging yielded better lesion detectability than 3D in large patients (BMI > 31), as 3D performance deteriorated in large patients (P < 0.05). 2D and 3D yielded similar results for different lesion sizes. CHO-SNR were 40% greater for AWOSEM, FBP-ATT, and FBPNAT than for OSEM (P < 0.05), and AWOSEM yielded significantly better lesion detectability than did FBP. In all patients, RVR yielded a systematic improvement in CHO-SNR over DWS in both 2D and 3D. √NEC was characterized by a behavior similar to that of SNRCHO for the 3 different phantom sizes considered in this study.

Analysis of rating data from multiple-alternative tasks☆

Abstract A standard method of estimating a single ROC curve from rating data for two stimulus alternatives has been extended to ratings of multiple alternatives. An observers ratings are assumed to represent ordinal classifications of a unidimensional decision variable that has a separate distribution for each of M possible stimuli. From these rating data, a maximum-likelihood procedure simultaneously estimates the rating-category boundary values and the 2(M−1) distribution parameters that specify ROC curves between all pairs of the M stimulus alternatives. Many stimulus manipulations, particularly those investigated in psychophysical experiments with visual or auditory stimuli, could justify this M-alternative rating procedure and analysis. An advantage of this method is that it allows reliable measurement of an observers performance indices at much higher values than does the two-alternative method. The assumption of a unidimensional decision variable may be too restrictive for general decision-making situations, where the decisions among alternatives often involve multiple sources of information. However, the two-alternative method is commonly used to fit rating-ROC curves for some decision-making tasks, such as diagnosis from medical images, for which the multiple-alternative procedure actually might be more appropriate.

Brain SPECT with short focal-length cone-beam collimation.

Single-photon emission-computed tomography (SPECT) imaging of deep brain structures is compromised by loss of photons due to attenuation. We have previously shown that a centrally peaked collimator sensitivity function can compensate for this phenomenon, increasing sensitivity over most of the brain. For dual-head instruments, parallel-hole collimators cannot provide variable sensitivity without simultaneously degrading spatial resolution near the center of the brain; this suggests the use of converging collimators. We have designed collimator pairs for dual-head SPECT systems to increase sensitivity, particularly in the center of the brain, and compared the new collimation approach to existing approaches on the basis of performance in estimating activity concentration of small structures at various locations in the brain. The collimator pairs we evaluated included a cone-beam collimator, for increased sensitivity, and a fan-beam collimator, for data sufficiency. We calculated projections of an ellipsoidal uniform background, with 0.9-cm-radius spherical lesions at several locations in the background. From these, we determined ideal signal-to-noise ratios (SNRCRB) for estimation of activity concentration within the spheres, based on the Cramer-Rao lower bound on variance. We also reconstructed, by an ordered-subset expectation-maximization (OS-EM) procedure, images of this phantom, as well as of the Zubal brain phantom, to allow visual assessment and to ensure that they were free of artifacts. The best of the collimator pairs evaluated comprised a cone-beam collimator with 20 cm focal length, for which the focal point is inside the brain, and a fan-beam collimator with 40 cm focal length. This pair yielded increased SNRCRB, compared to the parallel-parallel pair, throughout the imaging volume. The factor by which SNRCRB increased ranged from 1.1 at the most axially extreme location to 3.5 at the center. The gains in SNRCRB were relatively robust to mismatches between the center of the brain and the center of the imaging volume. Artifact-free reconstructions of simulated data acquired using this pair were obtained. Combining fan-beam and short-focusing cone-beam collimation should greatly improve dual-head brain SPECT imaging, especially for centrally located structures.