Med Phys
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As cone-beam CT (CBCT) systems dedicated to various imaging specialties proliferate, technical assessment grounded in imaging physics is important to ensuring that image quality and radiation dose are quantified, understood, and justified. This paper involves technical assessment of a new CBCT scanner (CS 9300, Carestream Health, Rochester, NY) dedicated to imaging of the ear and sinuses for applications in otolaryngology-head and neck surgery (OHNS). The results guided evaluation of technique protocols to minimize radiation dose in a manner sufficient for OHNS imaging tasks. ⋯ The CBCT scanner provided spatial and contrast resolution suitable to visualization of high-contrast morphology in sinus, maxillofacial, and otologic imaging applications. Rigorous technical assessment guided revision of technique protocols to reduce radiation dose while maintaining image quality sufficient for pertinent imaging tasks. The scanner appears well suited to high-contrast sinus and temporal bone imaging at doses comparable to or less than that reported for conventional diagnostic CT of the head.
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Beam angle optimization (BAO) by far remains an important and challenging problem in external beam radiation therapy treatment planning. Conventional BAO algorithms discussed in previous studies all focused on photon-based therapies. Impact of BAO on proton therapy is important while proton therapy increasingly receives great interests. This study focuses on potential benefits of BAO on intensity-modulated proton therapy (IMPT) that recently began available to clinical cancer treatment. ⋯ Uncertainty incorporated BAO may introduce pronounced improvement of IMPT plan quality including dosimetric benefits and robustness over uncertainties, based on the five clinical studies in this paper. In addition, local search algorithms may be more efficient in finding optimal beam angles than global optimization approaches for IMPT BAO.
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Low-dose CT has attracted increasing attention due to growing concerns about radiation exposure in medical scans. However, the frugal use of x-ray radiation inevitably reduces the quality of the CT images, introducing artifacts such as noise and streaks which make the reconstructed images difficult to read in clinical routine. For follow-up CT exams a prior scan is often available. It typically contains the same anatomical structures, just somewhat deformed and not aligned. This work describes a two-step technique that utilizes this prior scan to achieve high-quality low-dose CT imaging, overcoming difficulties arising from noise artifacts and misalignment. We specifically focus on reducing the dose by lowering the number of projections. This gives rise to severe streak artifacts which possibly lower the readability of CT images to a larger extent than the fine-grained noise that results from lowering the mA or kV settings. ⋯ The reduced-projection low-dose image reconstruction algorithm we present outperforms traditional image restoration algorithms when a prior scan is available. Our method is quite efficient and as such it is well suited for fast-paced clinical applications such as image-assisted interventions, orthopedic alignment scans, and follow-ups.
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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.
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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.