Knowledge-based radiation therapy (KBRT) treatment planning versus planning by experts: validation of a KBRT algorithm for prostate cancer treatment planning

Background: A knowledge-based radiation therapy (KBRT) treatment planning algorithm was recently developed. The purpose of this work is to investigate how plans that are generated with the objective KBRT approach compare to those that rely on the judgment of the experienced planner. Methods: Thirty volumetric modulated arc therapy plans were randomly selected from a database of prostate plans that were generated by experienced planners (expert plans). The anatomical data (CT scan and delineation of organs) of these patients and the KBRT algorithm were given to a novice with no prior treatment planning experience. The inexperienced planner used the knowledge-based algorithm to predict the dose that the OARs receive based on their proximity to the treated volume. The population-based OAR constraints were changed to the predicted doses. A KBRT plan was subsequently generated. The KBRT and expert plans were compared for the achieved target coverage and OAR sparing. The target coverages were compared using the Uniformity Index (UI), while 5 dose-volume points (D10, D30, D50, D70 and D90) were used to compare the OARs (bladder and rectum) doses. Wilcoxon matched-pairs signed rank test was used to check for significant differences (p < 0.05) between both datasets. Results: The KBRT and expert plans achieved mean UI values of 1.10 ± 0.03 and 1.10 ± 0.04, respectively. The Wilcoxon test showed no statistically significant difference between both results. The D90, D70, D50, D30 and D10 values of the two planning strategies, and the Wilcoxon test results suggests that the KBRT plans achieved a statistically significant lower bladder dose (at D30), while the expert plans achieved a statistically significant lower rectal dose (at D10 and D30). Conclusions: The results of this study show that the KBRT treatment planning approach is a promising method to objectively incorporate patient anatomical variations in radiotherapy treatment planning

1011-116 Myocardial Rb Extraction Fraction: Determination in Humans

Ouantitation of myocardial blood flow (MBF) with diffusion-limited radiotracers as 82Rb and positron emission tomography (PET) requires knowledge of flow dependence of myocardial 82Rb extraction fraction. To determine this dependence we evaluated 7 patients (mean age (61.0±9.7) years, 4 males, 3 females) who had undergone coronary angiography with exclusion of relevant coronary stenoses and normal left ventricular function. 82Rb-PET clearance was simultaneously assessed with global MBF by the argon (Ar) inert gas method. 82Rb clearance was dynamically measured by a CTI-Siemens ECAT 931-08-12 scanner after i.v. injection of 1–1.2 GBq 82Rb. Ar gas desaturation was obtained by simultaneous arterial and coronary sinus blood sampling. Measurements were performed at rest and during vasodilatation induced by i.v. dipyridamole (0.7mg/kg/4min). Mean 82Rb clearance and Ar flow values were (0.39±0,03)ml/g/min and (0.69±0.14)ml/g/min at rest, respectively, and (0.47±0.09)ml/g/min and (1.48±0.49)ml/g/min during hyperemia. A fit with a two compartment model yielded E=PS/(PS+MBF) with PS=(0.82±0.09)ml/g/min (PS: permeability surface area product). These data (figure) provide for the best of our knowledge the first measured 82Rb extraction fraction in humans and may form the basis for more accurate quantitation of myocardial blood flow with 82Rb-PET

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Quantitative analysis of regional distribution of tau pathology with 11C-PBB3-PET in a clinical setting.

PURPOSE The recent developments of tau-positron emission tomography (tau-PET) enable in vivo assessment of neuropathological tau aggregates. Among the tau-specific tracers, the application of 11C-pyridinyl-butadienyl-benzothiazole 3 (11C-PBB3) in PET shows high sensitivity to Alzheimer disease (AD)-related tau deposition. The current study investigates the regional tau load in patients within the AD continuum, biomarker-negative individuals (BN) and patients with suspected non-AD pathophysiology (SNAP) using 11C-PBB3-PET. MATERIALS AND METHODS A total of 23 memory clinic outpatients with recent decline of episodic memory were examined using 11C-PBB3-PET. Pittsburg compound B (11C-PIB) PET was available for 17, 18F-flurodeoxyglucose (18F-FDG) PET for 16, and cerebrospinal fluid (CSF) protein levels for 11 patients. CSF biomarkers were considered abnormal based on Aβ42 ( 450 ng/L). The PET biomarkers were classified as positive or negative using statistical parametric mapping (SPM) analysis and visual assessment. Using the amyloid/tau/neurodegeneration (A/T/N) scheme, patients were grouped as within the AD continuum, SNAP, and BN based on amyloid and neurodegeneration status. The 11C-PBB3 load detected by PET was compared among the groups using both atlas-based and voxel-wise analyses. RESULTS Seven patients were identified as within the AD continuum, 10 SNAP and 6 BN. In voxel-wise analysis, significantly higher 11C-PBB3 binding was observed in the AD continuum group compared to the BN patients in the cingulate gyrus, tempo-parieto-occipital junction and frontal lobe. Compared to the SNAP group, patients within the AD continuum had a considerably increased 11C-PBB3 uptake in the posterior cingulate cortex. There was no significant difference between SNAP and BN groups. The atlas-based analysis supported the outcome of the voxel-wise quantification analysis. CONCLUSION Our results suggest that 11C-PBB3-PET can effectively analyze regional tau load and has the potential to differentiate patients in the AD continuum group from the BN and SNAP group

Quantum Optimization and Quantum Machine Learning for Phase Unwrapping in SAR Interferometry

Phase unwrapping is the reconstruction of a phase given its values mod 2 pi. It is an important image processing technique used in synthetic aperture radar interferometry, e.g., in the context of topography and ground deformation. In light of recent quantum algorithm developments for mathematical optimization problems, we explore the usage of gate-based quantum computers and hybrid quantum algorithms to create novel phase unwrapping approaches

A Cognitive SAR Concept for Ship Detection using Support Vector Machines

Cognitive radar is a new acquisition technique that forms a closed loop between radar receiver, radar transmitter and environment, similar to the perception-action cycle in human cognition. The continuous adaptation of the acquisition parameters based on previously acquired information also harbours great potential for future SAR missions. As an example, this paper presents a spaceborne cognitive SAR concept for ship detection. The concept foresees a two-stage process to improve the overall ship detection probability compared to conventional approaches. First, a wide-swath mode with coarse resolution is utilized to cover a large maritime area. From these SAR data, the positions of potential ships shall be detected, however, due to the low signal-to-clutter ratio, with a high false alarm rate. In the second step, a high-gain mode with fine resolution is used to look at the presumed ship positions and either confirm or reject the presence of ships with high fidelity. This radar concept could be realized on a single platform using a hybrid mode. In the context of this investigation, the cognitive functionality is distributed on two separate SAR satellites operated in a convoy configuration, where the leading satellite performs the first coarse-detection step and the companion satellite implements the high-fidelity detection step including intelligent digital beamforming of one or more spotlight beams accessible via phased array antennas