Med Phys
-
In simultaneous positron emission tomography/magnetic resonance (PET/MR) imaging, local receiver surface radiofrequency (RF) coils are positioned in the field-of-view (FOV) of the PET detector during PET/MR data acquisition and potentially attenuate the PET signal. For flexible body RF surface coils placed on top of the patient's body, MR-based attenuation correction (AC) is an unsolved problem since the RF coils are not inherently visible in MR images and their individual position in the FOV is patient specific and not known a priori. The aim of this work was to quantify the effect of local body RF coils used in the Biograph mMR hybrid PET/MR system on PET emission data and to present techniques for MR-based position determination of these specific local RF coils. ⋯ Disregarding local coils in PET AC can lead to a bias of the AC PET images that is regional dependent. The closer the analyzed region is located to the coil, the higher the bias. Cod liver oil capsules or the UTE sequence can be used for RF coil position determination. The middle part of the examined RF coil hosting the preamplifiers and electronic components provides the highest attenuating part. Consequently, emphasis should be put on correcting for this portion of the RF coils with the suggested methods.
-
There is a growing need to localize prostate cancers on magnetic resonance imaging (MRI) to facilitate the use of image guided biopsy, focal therapy, and active surveillance follow up. Our goal was to develop a decision support system (DSS) for detecting and localizing peripheral zone prostate cancers by using machine learning approach to calculate a cancer probability map from multiparametric MR images (MP-MRI). ⋯ This DSS provides a cancer probability map for peripheral zone prostate tumors based on endorectal MP-MRI. These cancer probability maps can potentially aid radiologists in accurately localizing peripheral zone prostate cancers for planning targeted biopsies, focal therapy, and follow up for active surveillance.
-
Recent advances in compressed sensing (CS) enable accurate CT image reconstruction from highly undersampled and noisy projection measurements, due to the sparsifiable feature of most CT images using total variation (TV). These novel reconstruction methods have demonstrated advantages in clinical applications where radiation dose reduction is critical, such as onboard cone-beam CT (CBCT) imaging in radiation therapy. The image reconstruction using CS is formulated as either a constrained problem to minimize the TV objective within a small and fixed data fidelity error, or an unconstrained problem to minimize the data fidelity error with TV regularization. However, the conventional solutions to the above two formulations are either computationally inefficient or involved with inconsistent regularization parameter tuning, which significantly limit the clinical use of CS-based iterative reconstruction. In this paper, we propose an optimization algorithm for CS reconstruction which overcomes the above two drawbacks. ⋯ We propose ABOCS for CBCT reconstruction. As compared to other published CS-based algorithms, our method has attractive features of fast convergence and consistent parameter settings for different datasets. These advantages have been demonstrated on phantom studies.
-
To achieve high temporal resolution in CT myocardial perfusion imaging (MPI), images are often reconstructed using filtered backprojection (FBP) algorithms from data acquired within a short-scan angular range. However, the variation in the central angle from one time frame to the next in gated short scans has been shown to create detrimental partial scan artifacts when performing quantitative MPI measurements. This study has two main purposes. (1) To demonstrate the existence of a distinct detrimental effect in short-scan FBP, i.e., the introduction of a nonuniform spatial image noise distribution; this nonuniformity can lead to unexpectedly high image noise and streaking artifacts, which may affect CT MPI quantification. (2) To demonstrate that statistical image reconstruction (SIR) algorithms can be a potential solution to address the nonuniform spatial noise distribution problem and can also lead to radiation dose reduction in the context of CT MPI. ⋯ (1) Images reconstructed using FBP suffered from nonuniform spatial noise levels. This nonuniformity is another manifestation of the detrimental effects caused by short-scan reconstruction in CT MPI. (2) Images reconstructed using SIR had a much lower and more uniform noise level and thus can be used as a potential solution to address the FBP nonuniformity. (3) Given the improvement in the accuracy of the perfusion metrics when using SIR, it may be desirable to use a statistical reconstruction framework to perform low-dose dynamic CT MPI.
-
Craniospinal irradiation were traditionally treated the central nervous system using two or three adjacent field sets. A intensity-modulated radiotherapy (IMRT) plan (Jagged-Junction IMRT) which overcomes problems associated with field junctions and beam edge matching, improves planning and treatment setup efficiencies with homogenous target dose distribution was developed. ⋯ Jagged-Junction IMRT planning provided good dose homogeneity and conformity to the target while maintaining a low dose to the organs at risk. Jagged-Junction IMRT optimization smoothly distributed dose in the junction between field sets. Since there was no beam matching, this treatment technique is less likely to produce hot or cold spots at the junction in contrast to conventional techniques.