Joint Optimization of Collimator and Reconstruction Parameters in X-Ray Fluorescence Computed Tomography Using Analytical Point Spread Function and Model Observer

OBJECTIVE

To jointly optimize collimator design and image reconstruction algorithm in X-ray Fluorescence Computed Tomography (XFCT) for imaging low concentrations of high atomic number (Z) elements in small animal models.

METHODS

Single pinhole (SPH) collimator and three types of multi-pinhole (MPH) collimators were evaluated. MPH collimators with 5, 7, and 9 pinholes using lead, stainless steel and brass were considered. A digital cylindrical phantom (0.5 mm3 voxels) of 25 mm diameter and 25 mm height with a central 5 mm diameter and 12.5 mm height cylindrical insert containing gold nanoparticles (2:1 insert: background concentration) was modeled. A 125 kVp, 2 mm Sn filtered x-ray spectrum (0.5 cGy/projection) for gold K-shell XFCT was considered. System matrices were implemented using analytical point spread functions (PSF) for each pinhole collimator. Poisson noise was added to the projection data (16 equiangular views) before image reconstruction using Maximum-Likelihood Expectation-Maximization (ML-EM) algorithm. Signal-present and signal-absent images were generated for the detection task performed by a channelized Hotelling observer (CHO) with 10 Dense Difference-of-Gaussian channels. The area under the curve (AUC) in receiver operating characteristic was used as the image quality metric.

RESULTS

A stainless steel focusing type MPH with 7 pinholes and 20 iterations of ML-EM provided the highest AUC.

CONCLUSION

MPH collimators outperformed SPH collimators for XFCT and consistently high AUCs were observed with focusing type MPH designs with 7 pinholes.

SIGNIFICANCE

The combinations of collimator design and image reconstruction parameters that maximized AUC were identified, which could improve the performance of XFCT.

Inter-laboratory comparison of channelized hotelling observer computation

PURPOSE

The task-based assessment of image quality using model observers is increasingly used for the assessment of different imaging modalities. However, the performance computation of model observers needs standardization as well as a well-established trust in its implementation methodology and uncertainty estimation. The purpose of this work was to determine the degree of equivalence of the channelized Hotelling observer performance and uncertainty estimation using an intercomparison exercise.

MATERIALS AND METHODS

Image samples to estimate model observer performance for detection tasks were generated from two-dimensional CT image slices of a uniform water phantom. A common set of images was sent to participating laboratories to perform and document the following tasks: (a) estimate the detectability index of a well-defined CHO and its uncertainty in three conditions involving different sized targets all at the same dose, and (b) apply this CHO to an image set where ground truth was unknown to participants (lower image dose). In addition, and on an optional basis, we asked the participating laboratories to (c) estimate the performance of real human observers from a psychophysical experiment of their choice. Each of the 13 participating laboratories was confidentially assigned a participant number and image sets could be downloaded through a secure server. Results were distributed with each participant recognizable by its number and then each laboratory was able to modify their results with justification as model observer calculation are not yet a routine and potentially error prone.

RESULTS

Detectability index increased with signal size for all participants and was very consistent for 6 mm sized target while showing higher variability for 8 and 10 mm sized target. There was one order of magnitude between the lowest and the largest uncertainty estimation.

CONCLUSIONS

This intercomparison helped define the state of the art of model observer performance computation and with thirteen participants, reflects openness and trust within the medical imaging community. The performance of a CHO with explicitly defined channels and a relatively large number of test images was consistently estimated by all participants. In contrast, the paper demonstrates that there is no agreement on estimating the variance of detectability in the training and testing setting.

Objective comparison of lesion detectability in low and medium-energy collimator iodine-123 mIBG images using a channelized Hotelling observer

Iodine-123 mIBG imaging is widely regarded as a gold standard for diagnostic studies of neuroblastoma and adult neuroendocrine cancer although the optimal collimator for tumour imaging remains undetermined. Low-energy (LE) high-resolution (HR) collimators provide superior spatial resolution. However due to septal penetration of high-energy photons these provide poorer contrast than medium-energy (ME) general-purpose (GP) collimators. LEGP collimators improve count sensitivity. The aim of this study was to objectively compare the lesion detection efficiency of each collimator to determine the optimal collimator for diagnostic imaging. The septal penetration and sensitivity of each collimator was assessed. Planar images of the patient abdomen were simulated with static scans of a Liqui-Phil™ anthropomorphic phantom with lesion-shaped inserts, acquired with LE and ME collimators on 3 different manufacturers' gamma camera systems (Skylight (Philips), Intevo (Siemens) and Discovery (GE)). Two-hundred normal and 200 single-lesion abnormal images were created for each collimator. A channelized Hotelling observer (CHO) was developed and validated to score the images for the likelihood of an abnormality. The areas under receiver-operator characteristic (ROC) curves, Az, created from the scores were used to quantify lesion detectability. The CHO ROC curves for the LEHR collimators were inferior to the GP curves for all cameras. The LEHR collimators resulted in statistically significantly smaller Azs (p  <  0.05), of on average 0.891  ±  0.004, than for the MEGP collimators, 0.933  ±  0.004. In conclusion, the reduced background provided by MEGP collimators improved 123I mIBG image lesion detectability over LEHR collimators that provided better spatial resolution.

Correlation between model observer and human observer performance in CT imaging when lesion location is uncertain

PURPOSE

The purpose of this study was to investigate the correlation between model observer and human observer performance in CT imaging for the task of lesion detection and localization when the lesion location is uncertain.

METHODS

Two cylindrical rods (3-mm and 5-mm diameters) were placed in a 35×26 cm torso-shaped water phantom to simulate lesions with -15 HU contrast at 120 kV. The phantom was scanned 100 times on a 128-slice CT scanner at each of four dose levels (CTDIvol=5.7, 11.4, 17.1, and 22.8 mGy). Regions of interest (ROIs) around each lesion were extracted to generate images with signal-present, with each ROI containing 128×128 pixels. Corresponding ROIs of signal-absent images were generated from images without lesion mimicking rods. The location of the lesion (rod) in each ROI was randomly distributed by moving the ROIs around each lesion. Human observer studies were performed by having three trained observers identify the presence or absence of lesions, indicating the lesion location in each image and scoring confidence for the detection task on a 6-point scale. The same image data were analyzed using a channelized Hotelling model observer (CHO) with Gabor channels. Internal noise was added to the decision variables for the model observer study. Area under the curve (AUC) of ROC and localization ROC (LROC) curves were calculated using a nonparametric approach. The Spearman's rank order correlation between the average performance of the human observers and the model observer performance was calculated for the AUC of both ROC and LROC curves for both the 3- and 5-mm diameter lesions.

RESULTS

In both ROC and LROC analyses, AUC values for the model observer agreed well with the average values across the three human observers. The Spearman's rank order correlation values for both ROC and LROC analyses for both the 3- and 5-mm diameter lesions were all 1.0, indicating perfect rank ordering agreement of the figures of merit (AUC) between the average performance of the human observers and the model observer performance.

CONCLUSIONS

In CT imaging of different sizes of low-contrast lesions (-15 HU), the performance of CHO with Gabor channels was highly correlated with human observer performance for the detection and localization tasks with uncertain lesion location in CT imaging at four clinically relevant dose levels. This suggests the ability of Gabor CHO model observers to meaningfully assess CT image quality for the purpose of optimizing scan protocols and radiation dose levels in detection and localization tasks for low-contrast lesions.

Comparison of photoacoustic image reconstruction algorithms using the channelized Hotelling observer

We demonstrate the use of task-based image-quality metrics to compare various photoacoustic image-reconstruction algorithms, including a method based on the pseudoinverse of the system matrix, simple backprojection, filtered backprojection, and a method based on the Fourier transform. We use a three-dimensional forward model with a linear transducer array to simulate a photoacoustic imaging system. The reconstructed images correspond with two-dimensional slices of the object and are 128×128 pixels. In order to compare the algorithms, we use channelized Hotelling observers that predict the detection ability of human observers. We use two sets of channels: constant Q and difference of Gaussian spatial frequency channels. We look at three tasks, identification of a point source in a uniform background, identification of a 0.5-mm cube in a uniform background, and identification of a point source in a lumpy background. For the lumpy background task, which is the most realistic of the tasks, the method based on the pseudoinverse performs best according to both sets of channels.