Anando Sen

Accounting for anatomical noise in search-capable model observers for planar nuclear imaging

Abstract. Model observers intended to predict the diagnostic performance of human observers should account for the effects of both quantum and anatomical noise. We compared the abilities of several visual-search (VS) and scanning Hotelling-type models to account for anatomical noise in a localization receiver operating characteristic (LROC) study involving simulated nuclear medicine images. Our VS observer invoked a two-stage process of search and analysis. The images featured lesions in the prostate and pelvic lymph nodes. Lesion contrast and the geometric resolution and sensitivity of the imaging collimator were the study variables. A set of anthropomorphic mathematical phantoms was imaged with an analytic projector based on eight parallel-hole collimators with different sensitivity and resolution properties. The LROC study was conducted with human observers and the channelized nonprewhitening, channelized Hotelling (CH) and VS model observers. The CH observer was applied in a “background-known-statistically” protocol while the VS observer performed a quasi-background-known-exactly task. Both of these models were applied with and without internal noise in the decision variables. A perceptual search threshold was also tested with the VS observer. The model observers without inefficiencies failed to mimic the average performance trend for the humans. The CH and VS observers with internal noise matched the humans primarily at low collimator sensitivities. With both internal noise and the search threshold, the VS observer attained quantitative agreement with the human observers. Computational efficiency is an important advantage of the VS observer.

Assessment of prostate cancer detection with a visual-search human model observer

Early staging of prostate cancer (PC) is a significant challenge, in part because of the small tumor sizes in- volved. Our long-term goal is to determine realistic diagnostic task performance benchmarks for standard PC imaging with single photon emission computed tomography (SPECT). This paper reports on a localization receiver operator characteristic (LROC) validation study comparing human and model observers. The study made use of a digital anthropomorphic phantom and one-cm tumors within the prostate and pelvic lymph nodes. Uptake values were consistent with data obtained from clinical In-111 ProstaScint scans. The SPECT simulation modeled a parallel-hole imaging geometry with medium-energy collimators. Nonuniform attenua- tion and distance-dependent detector response were accounted for both in the imaging and the ordered-subset expectation-maximization (OSEM) iterative reconstruction. The observer study made use of 2D slices extracted from reconstructed volumes. All observers were informed about the prostate and nodal locations in an image. Iteration number and the level of postreconstruction smoothing were study parameters. The results show that a visual-search (VS) model observer correlates better with the average detection performance of human observers than does a scanning channelized nonprewhitening (CNPW) model observer.

Impact of anatomical noise on model observers for prostate SPECT

Scanning observers have been proposed for detection-localization tasks in medical imaging, but handling anatomical noise with these observers can be challenging. We have introduced visual-search (VS) observers as an alternative. The VS observer is a two-step process which mimics human perception through an initial search before a more detailed candidate analysis. Both the scanning and VS observers often outperform humans. In this paper, we analyze the performance of a VS observer with various inefficiency models as a means of matching human-observer performance. The observers were applied to prostate SPECT (single photon emission computed tomography) images. Prostate imaging protocols with In-111 and medium energy, parallel hole (MEPH) collimators were simulated. This was followed by a detailed localization receiver operator characteristic (LROC) study with human and model observers. Area under the LROC curve was used for observer performance evaluation. Results indicate that the VS observer applied with a combination of perceptual inefficiencies can quantitatively match human performance.

Practical Nuclear Medicine and Utility of Phantoms for Internal Dosimetry: XCAT Compared with Zubal

Purpose The absorbed doses for two radioisotopes, 99mTc and 131I, between previously validated Zubal phantom and the recently developed XCAT phantom were compared. Materials and methods GATE Monte Carlo code was used to simulate the statistical process of radiation. A XCAT phantom with voxel and matrix sizes similar to a standard Zubal phantom was generated. According to Medical International Radiation Dose formalism, specific absorbed fraction (SAF) values for photons and S-factors for beta particles were tabulated. The amounts of absorbed doses were calculated and compared in different organs. Results The differences of gamma radiation doses, SAFs, between Zubal and XCAT are >50% in adrenal from adrenal, pancreas from pancreas and thyroid from thyroid, in lung from kidney, kidneys from lungs and in kidneys from thyroid and thyroid from kidneys. The beta radiation doses differences between Zubal and XCAT are >50% in thyroid from thyroid, bladder from bladder, kidney from kidney, liver from bladder, thyroid from bladder and kidney from thyroid. The size and distances of the organs were different between XCAT and Zubal phantoms. Denoted differences of SAF and S-factors correspond to the different organ geometries in phantoms. Conclusion The results of absorbed doses in Zubal and XCAT phantoms are different. The variations prohibit easy comparison or interchangeability of dosimetry between these phantoms.

SVM-based visual-search model observers for PET tumor detection

Many search-capable model observers follow task paradigms that specify clinically unrealistic prior knowledge about the anatomical backgrounds in study images. Visual-search (VS) observers, which implement distinct, feature-based candidate search and analysis stages, may provide a means of avoiding such paradigms. However, VS observers that conduct single-feature analysis have not been reliable in the absence of any background information. We investigated whether a VS observer based on multifeature analysis can overcome this background dependence. The testbed was a localization ROC (LROC) study with simulated whole-body PET images. Four target-dependent morphological features were defined in terms of 2D cross-correlations involving a known tumor profile and the test image. The feature values at the candidate locations in a set of training images were fed to a support-vector machine (SVM) to compute a linear discriminant that classified locations as tumor-present or tumor-absent. The LROC performance of this SVM-based VS observer was compared against the performances of human observers and a pair of existing model observers.

Observer assessment of multi-pinhole SPECT geometries for prostate cancer imaging, a simulation study

SPECT imaging using In-111 ProstaScint is an FDA-approved method for diagnosing prostate cancer metastases within the pelvis. However, conventional medium-energy parallel-hole (MEPAR) collimators produce poor image quality and we are investigating the use of multipinhole (MPH) imaging as an alternative. This paper presents a method for evaluating MPH designs that makes use of sampling-sensitive (SS) mathematical model observers for tumor detectionlocalization tasks. Key to our approach is the redefinition of a normal (or background) reference image that is used with scanning model observers. We used this approach to compare different MPH configurations for the task of small-tumor detection in the prostate and surrounding lymph nodes. Four configurations used 10, 20, 30, and 60 pinholes evenly spaced over a complete circular orbit. A fixed-count acquisition protocol was assumed. Spherical tumors were placed within a digital anthropomorphic phantom having a realistic Prostascint biodistribution. Imaging data sets were generated with an analytical projector and reconstructed volumes were obtained with the OSEM algorithm. The MPH configurations were compared in a localization ROC (LROC) study with 2D pelvic images and both human and model observers. Regular and SS versions of the scanning channelized nonprewhitening (CNPW) and visual-search (VS) model observers were applied. The SS models demonstrated the highest correlations with the average human-observer results

Ideal and visual-search observers: accounting for anatomical noise in search tasks with planar nuclear imaging

Model observers have frequently been used for hardware optimization of imaging systems. For model observers to reliably mimic human performance it is important to account for the sources of variations in the images. Detection-localization tasks are complicated by anatomical noise present in the images. Several scanning observers have been proposed for such tasks. The most popular of these, the channelized Hotelling observer (CHO) incorporates anatomical variations through covariance matrices. We propose the visual-search (VS) observer as an alternative to the CHO to account for anatomical noise. The VS observer is a two-step process which first identifies suspicious tumor candidates and then performs a detailed analysis on them. The identification of suspicious candidates (search) implicitly accounts for anatomical noise. In this study we present a comparison of these two observers with human observers. The application considered is collimator optimization for planar nuclear imaging. Both observers show similar trends in performance with the VS observer slightly closer to human performance.

Quantitative assessment of induced errors in attenuation corrected myocardial SPECT images due to misregistration

Accurate attenuation correction can significantly improve the diagnostic accuracy of SPECT images. However, misregistration between the emission and attenuation maps can cause alignment induced artifacts in the attenuation corrected images. In this study we present a quantitative assessment of such errors in myocardial perfusion SPECT. A family of XCAT phantoms were imaged using the SIMIND Monte Carlo projector. To study the effects of misregistration, patient motion and respiratory motion were simulated. The differences between the test image and a reference image (perfectly aligned attenuation corrected image) were analyzed. The types of errors considered were lesion location errors, pixel density errors and change in contrast. Results indicate that horizontal translation causes the highest quantitative error and lesions in the lateral wall are most sensitive to misregistration induced errors.