Evaluation of metronomic chemotherapy response using diffusion and dynamic contrast-enhanced MRI.

PURPOSE: To investigate the feasibility of using diffusion MRI (dMRI) and dynamic contrast-enhanced (DCE) MRI to evaluate the treatment response of metronomic chemotherapy (MCT) in the 4T1 mammary tumor model of locally advanced breast cancer. METHODS: Twelve Balb/c mice with metastatic breast cancer were divided into treated and untreated (control) groups. The treated group (n = 6) received five treatments of anti-metabolite agent 5-Fluorouracil (5FU) in the span of two weeks. dMRI and DCE-MRI were acquired for both treated and control groups before and after MCT. Immunohistochemically staining and measurements were performed after the post-MRI measurements for comparison. RESULTS: The control mice had significantly (p<0.005) larger tumors than the MCT treated mice. The DCE-MRI analysis showed a decrease in contrast enhancement for the control group, whereas the MCT mice had a more stable enhancement between the pre-chemo and post-chemo time points. This confirms the antiangiogenic effects of 5FU treatment. Comparing amplitude of enhancement revealed a significantly (p<0.05) higher enhancement in the MCT tumors than in the controls. Moreover, the MCT uptake rate was significantly (p<0.001) slower than the controls. dMRI analysis showed the MCT ADC values were significantly larger than the control group at the post-scan time point. CONCLUSION: dMRI and DCE-MRI can be used as potential biomarkers for assessing the treatment response of MCT. The MRI and pathology observations suggested that in addition to the cytotoxic effect of cell kills, the MCT with a cytotoxic drug, 5FU, induced changes in the tumor vasculature similar to the anti-angiogenic effect.

Separation of benign and malignant breast lesions using dynamic contrast enhanced MRI in a biopsy cohort.

PURPOSE: To assess the diagnostic utility of contrast kinetic analysis for breast lesions and background parenchyma of women undergoing MRI-guided biopsies, for whom standard clinical analysis had failed to separate benign and malignant lesions. MATERIALS AND METHODS: This study included 115 women who had indeterminate lesions based on routine diagnostic breast MRI exams and underwent an MRI (3 Tesla) -guided biopsy of one or more lesions suspicious for breast cancer. Breast dynamic contrast-enhanced (DCE)-MRI was performed using a radial stack-of-stars three-dimensional spoiled gradient echo pulse sequence and modified k-space weighted image contrast image reconstruction. Contrast kinetic model analysis was conducted to characterize the contrast enhancement patterns measured in lesions and background parenchyma (BP). The transfer rate (Ktrans ), interstitial volume fraction (ve ), and vascular volume fraction (vp ) estimated from the lesion and BP were used to separate malignant from benign lesions. RESULTS: The patients with malignant lesions had significantly (P < 0.05) higher median lesion-Ktrans (0.081 min-1 ), higher median BP-Ktrans (0.032 min-1 ), and BP-vp (0.020) than those without malignant lesions (0.056 min-1 , 0.017 min-1 and 0.012, respectively). The area under the receiver operating characteristic curve (AUC) of the BP-Ktrans (0.687) was highest among the single parameters and higher than that of the lesion-Ktrans (0.664). The combined logistic regression model of lesion-Ktrans , lesion-ve , BP-Ktrans , BP-ve , and BP-vp had the highest AUC of 0.730. CONCLUSION: Our results suggest that the contrast kinetic analysis of DCE-MRI data can be used to differentiate the malignant lesions from the benign and high-risk lesions among the indeterminate breast lesions recommended for MRI-guided biopsy exams. LEVEL OF EVIDENCE: 3 J. MAGN. RESON. IMAGING 2017;45:1385-1393.

Evaluation of Breast Lipid Composition in Patients with Benign Tissue and Cancer by Using Multiple Gradient-Echo MR Imaging.

Purpose To demonstrate the feasibility of the use of a rapid, noninvasive, in vivo imaging method to measure fatty acid fractions of breast adipose tissue during diagnostic breast magnetic resonance (MR) examinations and to investigate associations between fatty acid fractions in breast adipose tissue and breast cancer status by using this method. Materials and Methods The institutional review board approved this retrospective HIPAA-compliant study and informed consent was waived. Between July 2013 and September 2014, multiple-echo three-dimensional gradient-echo data were acquired for 89 women. Spectra were generated and used to estimate fractions of monounsaturated fatty acid (MUFA), polyunsaturated fatty acid (PUFA), and saturated fatty acid (SFA) in the breast adipose tissue. Analysis of covariance and exact Mann-Whitney tests were used to compare groups and the Spearman rank correlation coefficient was used to characterize the association of each imaging measure with each attribute. Results For postmenopausal women, MUFA was lower (0.38 ± 0.06 vs 0.46 ± 0.10; P < .05) and SFA was higher (0.31 ± 0.07 vs 0.19 ± 0.11; P < .05) for women with invasive ductal carcinoma than for those with benign tissue. No correlation was found between body mass index (BMI) and fatty acid fractions in breast adipose tissue. In women with benign tissue, postmenopausal women had a higher PUFA (0.35 ± 0.06 vs 0.27 ± 0.05; P < .01) and lower SFA (0.19 ± 0.11 vs 0.30 ± 0.12; P < .05) than premenopausal women. Conclusion There is a possible link between the presence of invasive ductal carcinoma and fatty acid fractions in breast adipose tissue for postmenopausal women in whom BMI values are not correlated with the fatty acid fractions. (©) RSNA, 2016 Online supplemental material is available for this article.

Assessment of Aggressiveness of Breast Cancer Using Simultaneous 18F-FDG-PET and DCE-MRI: Preliminary Observation.

PURPOSE: This study aims to investigate the feasibility of using simultaneous breast MRI and PET to assess the synergy of MR pharmacokinetic and fluorine-18 fluorodeoxyglucose (F-FDG) uptake data to characterize tumor aggressiveness in terms of metastatic burden and Ki67 status. METHODS: Twelve consecutive patients underwent breast and whole-body PET/MRI. During the MR scan, PET events were simultaneously accumulated. MR contrast kinetic model parametric maps were computed using the extended Tofts model, including the volume transfer constant between blood plasma and the interstitial space (K), the transfer constant from the interstitial space to the blood plasma (kep), and the plasmatic volume fraction (Vp). RESULTS: Patients with systemic metastases had a significantly lower kep compared to those with local disease (0.45 vs. 0.99 min, P = 0.011). Metastatic burden correlated positively with K and standardized uptake value (SUV), and negatively with kep. Ki67 positive tumors had a significantly greater K compared to Ki67 negative tumors (0.29 vs. 0.45 min, P = 0.03). A negative correlation was found between metabolic tumor volume and transfer constant (K or Kep). CONCLUSION: These preliminary results suggest that MR pharmacokinetic parameters and FDG-PET may aid in the assessment of tumor aggressiveness and metastatic potential. Future studies are warranted with a larger cohort to further assess the role of pharmacokinetic modeling in simultaneous PET/MRI imaging.

Influence of temporal regularization and radial undersampling factor on compressed sensing reconstruction in dynamic contrast enhanced MRI of the breast.

BACKGROUND: To evaluate the influence of temporal sparsity regularization and radial undersampling on compressed sensing reconstruction of dynamic contrast-enhanced (DCE) MRI, using the iterative Golden-angle RAdial Sparse Parallel (iGRASP) MRI technique in the setting of breast cancer evaluation. METHODS: DCE-MRI examinations of the breast (n = 7) were conducted using iGRASP at 3 Tesla. Images were reconstructed with five different radial undersampling schemes corresponding to temporal resolutions between 2 and 13.4 s/frame and with four different weights for temporal sparsity regularization (λ = 0.1, 0.5, 2, and 6 times of noise level). Image similarity to time-averaged reference images was assessed by two breast radiologists and using quantitative metrics. Temporal similarity was measured in terms of wash-in slope and contrast kinetic model parameters. RESULTS: iGRASP images reconstructed with λ = 2 and 5.1 s/frame had significantly (P < 0.05) higher similarity to time-averaged reference images than the images with other reconstruction parameters (mutual information (MI) >5%), in agreement with the assessment of two breast radiologists. Higher undersampling (temporal resolution < 5.1 s/frame) required stronger temporal sparsity regularization (λ ≥ 2) to remove streaking aliasing artifacts (MI > 23% between λ = 2 and 0.5). The difference between the kinetic-model transfer rates of benign and malignant groups decreased as temporal resolution decreased (82% between 2 and 13.4 s/frame). CONCLUSION: This study demonstrates objective spatial and temporal similarity measures can be used to assess the influence of sparsity constraint and undersampling in compressed sensing DCE-MRI and also shows that the iGRASP method provides the flexibility of optimizing these reconstruction parameters in the postprocessing stage using the same acquired data.

Effect of T2* correction on contrast kinetic model analysis using a reference tissue arterial input function at 7 T.

OBJECTIVES: We aimed to investigate the effect of T2* correction on estimation of kinetic parameters from T1-weighted dynamic contrast enhanced (DCE) MRI data when a reference-tissue arterial input function (AIF) is used. MATERIALS AND METHODS: DCE-MRI data were acquired from seven mice with 4T1 mouse mammary tumors using a double gradient echo sequence at 7 T. The AIF was estimated from a region of interest in the muscle. The extended Tofts model was used to estimate pharmacokinetic parameters in the enhancing part of the tumor, with and without T2* correction of the lesion and AIF. The parameters estimated with T2* correction of both the AIF and lesion time-intensity curve were assumed to be the reference standard. RESULTS: For the whole population, there was significant difference (p < 0.05) in transfer constant (K(trans)) between T2* corrected and not corrected methods, but not in interstitial volume fraction (ve). Individually, no significant differences were found in K(trans) and ve of four and six tumors, respectively, between the T2* corrected and not corrected methods. In contrast, K(trans) was significantly underestimated, if the T2* correction was not used, in other tumors for which the median K(trans) was larger than 0.4 min(-1). CONCLUSION: T2* effect on tumors with high K(trans) may not be negligible in kinetic model analysis, even if AIF is estimated from reference tissue where the concentration of contrast agent is relatively low.

Simulation study of the effect of golden-angle KWIC with generalized kinetic model analysis on diagnostic accuracy for lesion discrimination.

PURPOSE: To quantitatively evaluate temporal blurring of dynamic contrast-enhanced MRI data generated using a k-space weighted image contrast (KWIC) image reconstruction technique with golden-angle view-ordering. METHODS: K-space data were simulated using golden-angle view-ordering and reconstructed using a KWIC algorithm with a Fibonacci number of views enforced for each annulus in k-space. Temporal blurring was evaluated by comparing pharmacokinetic model parameters estimated from the simulated data with the true values. Diagnostic accuracy was quantified using receiver operator characteristic curves (ROC) and the area under the ROC curves (AUC). RESULTS: Estimation errors of pharmacokinetic model parameters were dependent on the true curve type and the lesion size. For 10mm benign and malignant lesions, estimated AUC values using the true and estimate AIFs were consistent with the true AUC value. For 5mm benign and 20mm malignant lesions, estimated AUC values using the true and estimated AIFs were 0.906±0.020 and 0.905±0.021, respectively, as compared with the true AUC value of 0.896. CONCLUSIONS: Although the investigated reconstruction algorithm does impose errors in pharmacokinetic model parameter estimation, they are not expected to significantly impact clinical studies of diagnostic accuracy.

Use of computational fluid dynamics in the design of dynamic contrast enhanced imaging phantoms.

Phantoms for dynamic contrast enhanced (DCE) imaging modalities such as DCE computed tomography (DCE-CT) and DCE magnetic resonance imaging (DCE-MRI) are valuable tools for evaluating and comparing imaging systems. It is important for the contrast-agent distribution within the phantom to possess a time dependence that replicates a curve observed clinically, known as the 'tumor-enhancement curve'. It is also important for the concentration field within the lesion to be as uniform as possible. This study demonstrates how computational fluid dynamics (CFD) can be applied to achieve these goals within design constraints. The distribution of the contrast agent within the simulated phantoms was investigated in relation to the influence of three factors of the phantom design. First, the interaction between the inlets and the uniformity of the contrast agent within the phantom was modeled. Second, pumps were programmed using a variety of schemes and the resultant dynamic uptake curves were compared to tumor-enhancement curves obtained from clinical data. Third, the effectiveness of pulsing the inlet flow rate to produce faster equilibration of the contrast-agent distribution was quantified. The models employed a spherical lesion and design constraints (lesion diameter, inlet-tube size and orientation, contrast-agent flow rates and fluid properties) taken from a recently published DCE-MRI phantom study. For DCE-MRI in breast cancer detection, where the target tumor-enhancement curve varies on the scale of hundreds of seconds, optimizing the number of inlet tubes and their orientation was found to be adequate for attaining concentration uniformity and reproducing the target tumor-enhancement curve. For DCE-CT in liver tumor detection, where the tumor-enhancement curve varies on a scale of tens of seconds, the use of an iterated inlet condition (programmed into the pump) enabled the phantom to reproduce the target tumor-enhancement curve within a few per cent beyond about 6 s of wash-in. This time was cut in half by the final CFD-derived strategy of flow pulsing. Driving the pump with a 25% duty cycle pulsatile waveform produced a nearly uniform concentration in the phantom in just a few seconds under typical conditions. Comparisons with published x-ray measurements using tumor-enhancement curves for both benign and malignant breast lesions showed a difference of approximately 4% between the CFD predictions and measurements of the contrast-agent concentration averaged over the lesion volume. The techniques derived using CFD optimization can be used in future phantom designs, including as starting points for future CFD phantom studies employing new lesion geometries and tumor-enhancement curves.

Modified look-locker inversion recovery T1 mapping indices: assessment of accuracy and reproducibility between magnetic resonance scanners.

BACKGROUND: Cardiovascular magnetic resonance (CMR) T1 mapping indices, such as T1 time and partition coefficient (λ), have shown potential to assess diffuse myocardial fibrosis. The purpose of this study was to investigate how scanner and field strength variation affect the accuracy and precision/reproducibility of T1 mapping indices. METHODS: CMR studies were performed on two 1.5T and three 3T scanners. Eight phantoms were made to mimic the T1/T2 of pre- and post-contrast myocardium and blood at 1.5T and 3T. T1 mapping using MOLLI was performed with simulated heart rate of 40-100 bpm. Inversion recovery spin echo (IR-SE) was the reference standard for T1 determination. Accuracy was defined as the percent error between MOLLI and IR-SE, and scan/re-scan reproducibility was defined as the relative percent mean difference between repeat MOLLI scans. Partition coefficient was estimated by ΔR1myocardium phantom/ΔR1blood phantom. Generalized linear mixed model was used to compare the accuracy and precision/reproducibility of T1 and λ across field strength, scanners, and protocols. RESULTS: Field strength significantly affected MOLLI T1 accuracy (6.3% error for 1.5T vs. 10.8% error for 3T, p<0.001) but not λ accuracy (8.8% error for 1.5T vs. 8.0% error for 3T, p=0.11). Partition coefficients of MOLLI were not different between two 1.5T scanners (47.2% vs. 47.9%, p=0.13), and showed only slight variation across three 3T scanners (49.2% vs. 49.8% vs. 49.9%, p=0.016). Partition coefficient also had significantly lower percent error for precision (better scan/re-scan reproducibility) than measurement of individual T1 values (3.6% for λ vs. 4.3%-4.8% for T1 values, approximately, for pre/post blood and myocardium values). CONCLUSION: Based on phantom studies, T1 errors using MOLLI ranged from 6-14% across various MR scanners while errors for partition coefficient were less (6-10%). Compared with absolute T1 times, partition coefficient showed less variability across platforms and field strengths as well as higher precision.

Effect of protocol parameters on contrast agent washout curve separability in breast dynamic contrast enhanced MRI: a simulation study.

Variability in diagnostic performance of breast dynamic contrast-enhanced MRI has highlighted the need for improved standardization. While guidance exists on some aspects of the technique, currently, there is no standardized method for selecting repetition time and flip angle, which are important determinants of image contrast. This study develops a theoretical framework for quantitative optimization of temporal aspects of dynamic contrast-enhanced MRI based on area under the receiver operating curve. Optimizations in simulation demonstrate the potential for increases in area under the receiver operating characteristic curve by up to 0.20 and specificity at a sensitivity of 90% by up to 19%, depending on the protocol. These results suggest that careful selection of repetition time and flip angle can improve diagnostic performance and identify these quantities as potentially important parameters for future standardization.

Development and characterization of a dynamic lesion phantom for the quantitative evaluation of dynamic contrast-enhanced MRI.

PURPOSE: To develop a dynamic lesion phantom that is capable of producing physiological kinetic curves representative of those seen in human dynamic contrast-enhanced MRI (DCE-MRI) data. The objective of this phantom is to provide a platform for the quantitative comparison of DCE-MRI protocols to aid in the standardization and optimization of breast DCE-MRI. METHODS: The dynamic lesion consists of a hollow, plastic mold with inlet and outlet tubes to allow flow of a contrast agent solution through the lesion over time. Border shape of the lesion can be controlled using the lesion mold production method. The configuration of the inlet and outlet tubes was determined using fluid transfer simulations. The total fluid flow rate was determined using x-ray images of the lesion for four different flow rates (0.25, 0.5, 1.0, and 1.5 ml/s) to evaluate the resultant kinetic curve shape and homogeneity of the contrast agent distribution in the dynamic lesion. High spatial and temporal resolution x-ray measurements were used to estimate the true kinetic curve behavior in the dynamic lesion for benign and malignant example curves. DCE-MRI example data were acquired of the dynamic phantom using a clinical protocol. RESULTS: The optimal inlet and outlet tube configuration for the lesion molds was two inlet molds separated by 30° and a single outlet tube directly between the two inlet tubes. X-ray measurements indicated that 1.0 ml/s was an appropriate total fluid flow rate and provided truth for comparison with MRI data of kinetic curves representative of benign and malignant lesions. DCE-MRI data demonstrated the ability of the phantom to produce realistic kinetic curves. CONCLUSIONS: The authors have constructed a dynamic lesion phantom, demonstrated its ability to produce physiological kinetic curves, and provided estimations of its true kinetic curve behavior. This lesion phantom provides a tool for the quantitative evaluation of DCE-MRI protocols, which may lead to improved discrimination of breast cancer lesions.

Oblique incidence effects in direct x-ray detectors: a first-order approximation using a physics-based analytical model.

PURPOSE: The authors describe the modifications to a previously developed analytical model of indirect CsI:Tl-based detector response required for studying oblique x-ray incidence effects in direct semiconductor-based detectors. This first-order approximation analysis allows the authors to describe the associated degradation in resolution in direct detectors and compare the predictions to the published data for indirect detectors. METHODS: The proposed model is based on a physics-based analytical description developed by Freed et al. ["A fast, angle-dependent, analytical model of CsI detector response for optimization of 3D x-ray breast imaging systems," Med. Phys. 37(6), 2593-2605 (2010)] that describes detector response functions for indirect detectors and oblique incident x rays. The model, modified in this work to address direct detector response, describes the dependence of the response with x-ray energy, thickness of the transducer layer, and the depth-dependent blur and collection efficiency. RESULTS: The authors report the detector response functions for indirect and direct detector models for typical thicknesses utilized in clinical systems for full-field digital mammography (150 microm for indirect CsI:Tl and 200 microm for a-Se direct detectors). The results suggest that the oblique incidence effect in a semiconductor detector differs from that in indirect detectors in two ways: The direct detector model produces a sharper overall PRF compared to the response corresponding to the indirect detector model for normal x-ray incidence and a larger relative increase in blur along the x-ray incidence direction compared to that found in indirect detectors with respect to the response at normal incidence angles. CONCLUSIONS: Compared to the effect seen in indirect detectors, the direct detector model exhibits a sharper response at normal x-ray incidence and a larger relative increase in blur along the x-ray incidence direction with respect to the blur in the orthogonal direction. The results suggest that the oblique incidence effect in direct detectors can be considered to be caused mostly by the geometry of the path where the x-ray beam and its secondary particles deposit energy in the semiconductor layer.

X-ray properties of an anthropomorphic breast phantom for MRI and x-ray imaging.

The purpose of this study is to characterize the x-ray properties of a dual-modality, anthropomorphic breast phantom whose MRI properties have been previously evaluated. The goal of this phantom is to provide a platform for optimization and standardization of two- and three-dimensional x-ray and MRI breast imaging modalities for the purpose of lesion detection and discrimination. The phantom is constructed using a mixture of lard and egg whites, resulting in a variable, tissue-mimicking structure with separate adipose- and glandular-mimicking components. The phantom can be produced with either a compressed or uncompressed shape. Mass attenuation coefficients of the phantom materials were estimated using elemental compositions from the USDA National Nutrient Database for Standard Reference and the atomic interaction models from the Monte Carlo code PENELOPE and compared with human values from the literature. The image structure was examined quantitatively by calculating and comparing spatial covariance matrices of the phantom and patient mammography images. Finally, a computerized version of the phantom was created by segmenting a computed tomography scan and used to simulate x-ray scatter of the phantom in a mammography geometry. Mass attenuation coefficients of the phantom materials were within 20% and 15% of the values for adipose and glandular tissues, respectively, which is within the estimation error of these values. Matching was improved at higher energies (>20 keV). Tissue structures in the phantom have a size similar to those in the patient data, but are slightly larger on average. Correlations in the patient data appear to be longer than those in the phantom data in the anterior-posterior direction; however, they are within the error bars of the measurement. Simulated scatter-to-primary ratio values of the phantom images were as high as 85% in some areas and were strongly affected by the heterogeneous nature of the phantom. Key physical x-ray properties of the phantom have been quantitatively evaluated and shown to be comparable to those of breast tissue. Since the MRI properties of the phantom have been previously evaluated, we believe it is a useful tool for quantitative evaluation of two- and three-dimensional x-ray and MRI breast imaging modalities for the purpose of lesion detection and characterization.

An anthropomorphic phantom for quantitative evaluation of breast MRI.

PURPOSE: In this study, the authors aim to develop a physical, tissue-mimicking phantom for quantitative evaluation of breast MRI protocols. The objective of this phantom is to address the need for improved standardization in breast MRI and provide a platform for evaluating the influence of image protocol parameters on lesion detection and discrimination. Quantitative comparisons between patient and phantom image properties are presented. METHODS: The phantom is constructed using a mixture of lard and egg whites, resulting in a random structure with separate adipose- and glandular-mimicking components. T1 and T2 relaxation times of the lard and egg components of the phantom were estimated at 1.5 T from inversion recovery and spin-echo scans, respectively, using maximum-likelihood methods. The image structure was examined quantitatively by calculating and comparing spatial covariance matrices of phantom and patient images. A static, enhancing lesion was introduced by creating a hollow mold with stereolithography and filling it with a gadolinium-doped water solution. RESULTS: Measured phantom relaxation values fall within 2 standard errors of human values from the literature and are reasonably stable over 9 months of testing. Comparison of the covariance matrices of phantom and patient data demonstrates that the phantom and patient data have similar image structure. Their covariance matrices are the same to within error bars in the anterior-posterior direction and to within about two error bars in the right-left direction. The signal from the phantom's adipose-mimicking material can be suppressed using active fat-suppression protocols. A static, enhancing lesion can also be included with the ability to change morphology and contrast agent concentration. CONCLUSIONS: The authors have constructed a phantom and demonstrated its ability to mimic human breast images in terms of key physical properties that are relevant to breast MRI. This phantom provides a platform for the optimization and standardization of breast MRI imaging protocols for lesion detection and characterization.

A fast, angle-dependent, analytical model of CsI detector response for optimization of 3D x-ray breast imaging systems.

PURPOSE: Accurate models of detector blur are crucial for performing meaningful optimizations of three-dimensional (3D) x-ray breast imaging systems as well as for developing reconstruction algorithms that faithfully reproduce the imaged object anatomy. So far, x-ray detector blur has either been ignored or modeled as a shift-invariant symmetric function for these applications. The recent development of a Monte Carlo simulation package called MANTIS has allowed detailed modeling of these detector blur functions and demonstrated the magnitude of the anisotropy for both tomosynthesis and breast CT imaging systems. Despite the detailed results that MANTIS produces, the long simulation times required make inclusion of these results impractical in rigorous optimization and reconstruction algorithms. As a result, there is a need for detector blur models that can be rapidly generated. METHODS: In this study, the authors have derived an analytical model for deterministic detector blur functions, referred to here as point response functions (PRFs), of columnar CsI phosphor screens. The analytical model is x-ray energy and incidence angle dependent and draws on results from MANTIS to indirectly include complicated interactions that are not explicitly included in the mathematical model. Once the mathematical expression is derived, values of the coefficients are determined by a two-dimensional (2D) fit to MANTIS-generated results based on a figure-of-merit (FOM) that measures the normalized differences between the MANTIS and analytical model results averaged over a region of interest. A smaller FOM indicates a better fit. This analysis was performed for a monochromatic x-ray energy of 25 keV, a CsI scintillator thickness of 150 microm, and four incidence angles (0 degrees, 15 degrees, 30 degrees, and 45 degrees). RESULTS: The FOMs comparing the analytical model to MANTIS for these parameters were 0.1951 +/- 0.0011, 0.1915 +/- 0.0014, 0.2266 +/- 0.0021, and 0.2416 +/- 0.0074 for 0 degrees, 15 degrees, 30 degrees, and 45 degrees, respectively. As a comparison, the same FOMs comparing MANTIS to 2D symmetric Gaussian fits to the zero-angle PRF were 0.6234 +/- 0.0020, 0.9058 +/- 0.0029, 1.491 +/- 0.012, and 2.757 +/- 0.039 for the same set of incidence angles. Therefore, the analytical model matches MANTIS results much better than a 2D symmetric Gaussian function. A comparison was also made against experimental data for a 170 microm thick CsI screen and an x-ray energy of 25.6 keV. The corresponding FOMs were 0.3457 +/- 0.0036, 0.3281 +/- 0.0057, 0.3422 +/- 0.0023, and 0.3677 +/- 0.0041 for 0 degrees, 15 degrees, 30 degrees, and 45 degrees, respectively. In a previous study, FOMs comparing the same experimental data to MANTIS PRFs were found to be 0.2944 +/- 0.0027, 0.2387 +/- 0.0039, 0.2816 +/- 0.0025, and 0.2665 +/- 0.0032 for the same set of incidence angles. CONCLUSIONS: The two sets of derived FOMs, comparing MANTIS-generated PRFs and experimental data to the analytical model, demonstrate that the analytical model is able to reproduce experimental data with a FOM of less than two times that comparing MANTIs and experimental data. This performance is achieved in less than one millionth the computation time required to generate a comparable PRF with MANTIS. Such small computation times will allow for the inclusion of detailed detector physics in rigorous optimization and reconstruction algorithms for 3D x-ray breast imaging systems.

Experimental validation of Monte Carlo (MANTIS) simulated x-ray response of columnar CsI scintillator screens.

PURPOSE: MANTIS is a Monte Carlo code developed for the detailed simulation of columnar CsI scintillator screens in x-ray imaging systems. Validation of this code is needed to provide a reliable and valuable tool for system optimization and accurate reconstructions for a variety of x-ray applications. Whereas previous validation efforts have focused on matching of summary statistics, in this work the authors examine the complete point response function (PRF) of the detector system in addition to relative light output values. METHODS: Relative light output values and high-resolution PRFs have been experimentally measured with a custom setup. A corresponding set of simulated light output values and PRFs have also been produced, where detailed knowledge of the experimental setup and CsI:Tl screen structures are accounted for in the simulations. Four different screens were investigated with different thicknesses, column tilt angles, and substrate types. A quantitative comparison between the experimental and simulated PRFs was performed for four different incidence angles (0 degrees, 15 degrees, 30 degrees, and 45 degrees) and two different x-ray spectra (40 and 70 kVp). The figure of merit (FOM) used measures the normalized differences between the simulated and experimental data averaged over a region of interest. RESULTS: Experimental relative light output values ranged from 1.456 to 1.650 and were in approximate agreement for aluminum substrates, but poor agreement for graphite substrates. The FOMs for all screen types, incidence angles, and energies ranged from 0.1929 to 0.4775. To put these FOMs in context, the same FOM was computed for 2D symmetric Gaussians fit to the same experimental data. These FOMs ranged from 0.2068 to 0.8029. Our analysis demonstrates that MANTIS reproduces experimental PRFs with higher accuracy than a symmetric 2D Gaussian fit to the experimental data in the majority of cases. Examination of the spatial distribution of differences between the PRFs shows that the main reason for errors between MANTIS and the experimental data is that MANTIS-generated PRFs are sharper than the experimental PRFs. CONCLUSIONS: The experimental validation of MANTIS performed in this study demonstrates that MANTIS is able to reliably predict experimental PRFs, especially for thinner screens, and can reproduce the highly asymmetric shape seen in the experimental data. As a result, optimizations and reconstructions carried out using MANTIS should yield results indicative of actual detector performance. Better characterization of screen properties is necessary to reconcile the simulated light output values with experimental data.

Effect of oblique X-ray incidence in flat-panel computed tomography of the breast.

We quantify the variation in resolution due to anisotropy caused by oblique X-ray incidence in indirect flat-panel detectors for computed tomography breast imaging systems. We consider a geometry and detector type utilized in breast computed tomography (CT) systems currently being developed. Our methods rely on mantis, a combined X-ray, electron, and optical Monte Carlo transport open source code. The physics models are the most accurate available in general-purpose Monte Carlo packages in the diagnostic energy range. We consider maximum-obliquity angles of 10 ( degrees ) and 13 ( degrees ) at the centers of the 30 and 40 cm detector edges, respectively, and 16 ( degrees ) at the corner of the detector. Our results indicate that blur is asymmetric and that the resolution properties vary significantly with the angle (or location) of incidence. Our results suggest that the asymmetry can be as high as a factor of 2.6 between orthogonal directions. Anisotropy maps predicted by mantis provide an understanding of the effect that such variations have on the imaging system and allow more accurate modeling and optimization of breast CT systems. These maps of anisotropy across the detector could lead to improved reconstruction and help motivate physics-based strategies for computer detection of breast lesions.

Adaptive SPECT.

Adaptive imaging systems alter their data-acquisition configuration or protocol in response to the image information received. An adaptive pinhole single-photon emission computed tomography (SPECT) system might acquire an initial scout image to obtain preliminary information about the radiotracer distribution and then adjust the configuration or sizes of the pinholes, the magnifications, or the projection angles in order to improve performance. This paper briefly describes two small-animal SPECT systems that allow this flexibility and then presents a framework for evaluating adaptive systems in general, and adaptive SPECT systems in particular. The evaluation is in terms of the performance of linear observers on detection or estimation tasks. Expressions are derived for the ideal linear (Hotelling) observer and the ideal linear (Wiener) estimator with adaptive imaging. Detailed expressions for the performance figures of merit are given, and possible adaptation rules are discussed.

A prototype instrument for single pinhole small animal adaptive SPECT imaging.

The authors have designed and constructed a small-animal adaptive SPECT imaging system as a prototype for quantifying the potential benefit of adaptive SPECT imaging over the traditional fixed geometry approach. The optical design of the system is based on filling the detector with the region of interest for each viewing angle, maximizing the sensitivity, and optimizing the resolution in the projection images. Additional feedback rules for determining the optimal geometry of the system can be easily added to the existing control software. Preliminary data have been taken of a phantom with a small, hot, offset lesion in a flat background in both adaptive and fixed geometry modes. Comparison of the predicted system behavior with the actual system behavior is presented, along with recommendations for system improvements.

Adaptive SPECT for Tumor Necrosis Detection.

In this paper, we consider a prototype of an adaptive SPECT system, and we use simulation to objectively assess the system's performance with respect to a conventional, non-adaptive SPECT system. Objective performance assessment is investigated for a clinically relevant task: the detection of tumor necrosis at a known location and in a random lumpy background. The iterative maximum-likelihood expectation-maximization (MLEM) algorithm is used to perform image reconstruction. We carried out human observer studies on the reconstructed images and compared the probability of correct detection when the data are generated with the adaptive system as opposed to the non-adaptive system. Task performance is also assessed by using a channelized Hotelling observer, and the area under the receiver operating characteristic curve is the figure of merit for the detection task. Our results show a large performance improvement of adaptive systems versus non-adaptive systems and motivate further research in adaptive medical imaging.