Tomography, Volume 1, Issue 1 (September 2015) – 9 articles

Parametric response mapping (PRM) of inspiration and expiration computed tomography (CT) images improves the radiological phenotyping of chronic obstructive pulmonary disease (COPD). PRM classifies individual voxels of lung parenchyma as normal, emphysematous, or nonemphysematous air trapping. In this study, bias and noise characteristics of the PRM methodology to CT and clinical procedures were evaluated to determine best practices for this quantitative technique. Twenty patients of varying COPD status with paired volumetric inspiration and expiration CT scans of the lungs were identified from the baseline COPDGene cohort. The impact of CT scanner manufacturer and reconstruction kernels were evaluated as potential sources of variability in PRM measurements along with simulations to quantify the impact of inspiration/expiration lung volume levels, misregistration, and image spacing on PRM measurements. Negligible variation in PRM metrics was observed when CT scanner type and reconstruction were consistent and inspiration/expiration lung volume levels were near target volumes. CT scanner Hounsfield unit drift occurred but remained difficult to ameliorate. Increasing levels of image misregistration and CT slice spacing were found to have a minor effect on PRM measurements. PRM-derived values were found to be most sensitive to lung volume levels and mismatched reconstruction kernels. As with other quantitative imaging techniques, reliable PRM measurements are attainable when consistent clinical and CT protocols are implemented. Full article

The goal of this work was to demonstrate the utility of Bayesian probability theory-based model selection for choosing the optimal mathematical model from among 4 competing models of renal dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data. DCE-MRI data were collected on 21 mice with high (n = 7), low (n = 7), or normal (n = 7) renal blood flow (RBF). Model parameters and posterior probabilities of 4 renal DCE-MRI models were estimated using Bayesian-based methods. Models investigated included (1) an empirical model that contained a monoexponential decay (washout) term and a constant offset, (2) an empirical model with a biexponential decay term (empirical/biexponential model), (3) the Patlak–Rutland model, and (4) the 2-compartment kidney model. Joint Bayesian model selection/parameter estimation demonstrated that the empirical/biexponential model was strongly favored for all 3 cohorts, the modeled DCE signals that characterized each of the 3 cohorts were distinctly different, and individual empirical/biexponential model parameter values clearly distinguished cohorts of low and high RBF from one another. The Bayesian methods can be readily extended to a variety of model analyses, making it a versatile and valuable tool for model selection and parameter estimation. Full article

Prior reports have suggested that delayed ¹⁸F-fluorodeoxyglucose positron emission tomography (FDG-PET) oncology imaging can improve the contrast-to-noise ratio (CNR) for known lesions. Our goal was to estimate realistic bounds for lesion detectability for static measurements within 1 to 4 hours between FDG injection and image acquisition. Tumor and normal tissue kinetic model parameters were estimated from dynamic PET studies of patients with early-stage breast cancer. These parameters were used to generate time-activity curves (TACs) for up to 4 hours, for which we assumed both nonreversible and reversible models with different rates of FDG dephosphorylation (k₄). For each pair of tumor and normal tissue TACs, 600 PET sinogram realizations were generated, and images were reconstructed using the ordered subsets expectation maximization reconstruction algorithm. Test statistics for each tumor and normal tissue region of interest were output from the computer model observers and evaluated using a receiver operating characteristic analysis, with the calculated area under the curve (AUC) providing a measure of lesion detectability. For the nonreversible model (k₄ = 0), the AUC increased in 11 of 23 (48%) patients for 1 to 2 hours after the current standard postradiotracer injection imaging window of 1 hour. This improvement was driven by increased tumor/normal tissue contrast before the impact of increased noise that resulted from radiotracer decay began to dominate the imaging signal. As k₄ was increased from 0 to 0.01 min⁻¹, the time of maximum detectability shifted earlier, due to decreasing FDG concentration in the tumor lowering the CNR. These results imply that delayed PET imaging may reveal inconspicuous lesions that otherwise would have gone undetected. Full article

Quantitative magnetic resonance imaging (MRI)-based biomarkers, which capture physiological and functional tumor processes, were evaluated as imaging surrogates of early tumor response following chemoradiotherapy in glioma patients. A multiparametric extension of a voxel-based analysis, referred as the parametric response map (PRM), was applied to quantitative MRI maps to test the predictive potential of this metric for detecting response. Fifty-six subjects with newly diagnosed high-grade gliomas treated with radiation and concurrent temozolomide were enrolled in a single-site prospective institutional review board-approved MRI study. Apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) maps were acquired before therapy and 3 weeks after therapy was initiated. Multiparametric PRM (mPRM) was applied to both physiological MRI maps and evaluated as an imaging biomarker of patient survival. For comparison, single-biomarker PRMs were also evaluated in this study. The simultaneous analysis of ADC and rCBV by the mPRM approach was found to improve the predictive potential for patient survival over single PRM measures. With an array of quantitative imaging parameters being evaluated as biomarkers of therapeutic response, mPRM shows promise as a new methodology for consolidating physiologically distinct imaging parameters into a single interpretable and quantitative metric. Full article

The standard of care for newly diagnosed glioblastoma (GBM) is surgery first, radiotherapy (RT) with concurrent temozolomide (TMZ) second, and adjuvant TMZ last. We hypothesized patients with low diffusivity measured using apparent diffusion coefficient (ADC) histogram analysis evaluated after RT + TMZ and before adjuvant TMZ would have a significantly shorter progression-free survival (PFS) and overall survival (OS). To test this hypothesis, we evaluated 120 patients with newly diagnosed GBM receiving RT + TMZ followed by adjuvant TMZ. Magnetic resonance imaging was performed after completing RT + TMZ and before initiating adjuvant TMZ. A double Gaussian mixed model was used to describe the ADC histograms within the enhancing tumor, where ADC_L and ADC_H were defined as the mean ADC value of the lower and higher Gaussian distribution, respectively. An ADC_L value of 1.0 μm²/ms and ADC_H value of 1.6 μm²/ms were used to stratify patients into high- and low-risk categories. Results suggested that patients with a low ADC_L had a significantly shorter PFS (Cox hazard ratio = 0.12, P = 0.0006). OS was significantly shorter with low ADC_L tumors, showing a median OS of 407 versus 644 days (Cox hazard ratio = 0.31, P = 0.047). ADC_H did not predict PFS or OS when accounting for age and ADC_L. In summary, after completing RT + TMZ, newly diagnosed glioblastoma patients with a low ADC_L are likely to progress and die earlier than patients with a higher ADC_L. ADC histogram analysis may be useful for patient-risk stratification after completing RT + TMZ. Full article

We report the application of our newly developed fluorescent probe 3-(benzylamino)-4,4-difluoro-5-(4-propyl-1H-1,2,3-triazol-1-yl)-8-(4-(2-hydroxyacetamido)phen-yl)-4-bora-3a,4a-diaza-s-indacene (NeuO) to label and image live neurons in zebrafish. Immersing zebrafish embryos in NeuO or injecting NeuO into zebrafish brain ventricles results in nontoxic in vivo neuronal labeling. We demonstrate the applicability of NeuO and envisage the potential of this compound as a rapid and simple labeling reagent for studying neuron development and degeneration. Full article

Pulmonary arterial hypertension (PAH) is characterized by elevated pulmonary artery pressure (PAP), altered pulmonary artery (PA) hemodynamics, and vessel wall characteristics that affect the right ventricular (RV) function. Magnetic resonance imaging (MRI) has recently been considered in PAH and has shown promising results for estimating PAP, measuring PA hemodynamic parameters, assessing PA vessel wall stiffness, and evaluating RV global and regional functions. In this article, we review various MRI techniques and image analysis methods for evaluating PAH, with an emphasis on the resulting images and how they are interpreted for both qualitatively and quantitatively assessing the PA and RV conditions. Full article

Prostate cancer is a prevalent public health problem worldwide. Over the past decade, there has been tremendous research activity in the potential use of positron emission tomography with a number of radiotracers targeted to various biological aspects of this complex tumor. Systematic reviews and meta-analyses are important contributions to the relevant literature that summarize the evidence while reducing the effect of various sources of bias in the published data. The accumulation of relevant data in this clinical setting has recently provided the opportunity for systematic reviews. In this brief article, I summarize the published systematic reviews and meta-analyses of positron emission tomography in prostate cancer. Most robust evidence suggests a probable role for first-line use of positron emission tomography with radiolabeled choline in restating patients with biochemical relapse of prostate cancer with the diagnostic performance that seems to be positively associated with the serum prostate-specific antigen level and velocity. Future systematic reviews will be needed for other emerging radiotracers such as those based on the prostate-specific membrane antigen and gastrin-releasing peptide receptor. Full article

Quantitative susceptibility mapping (QSM) is a recently developed magnetic resonance imaging (MRI) technique for quantifying the spatial distribution of magnetic susceptibility within biological tissues. It first uses the frequency shift in the MRI signal to map the magnetic field profile within the tissue. The resulting field map is then used to determine the spatial distribution of the underlying magnetic susceptibility by solving an inverse problem. The solution is achieved by deconvolving the field map with a dipole field, under the assumption that the magnetic field results from a superposition of the dipole fields generated by all voxels and that each voxel has its own unique magnetic susceptibility. QSM provides an improved contrast-to-noise ratio for certain tissues and structures compared with its magnitude counterpart. More importantly, magnetic susceptibility directly reflects the molecular composition and cellular architecture of the tissue. Consequently, by quantifying magnetic susceptibility, QSM is becoming a quantitative imaging approach for characterizing normal and pathological tissue properties. This article reviews the mechanism that generates susceptibility contrast within tissues and some associated applications. Full article