IMAR correction algorithm could be readily implemented in an existing clinical workflow upon commercial release. While residual errors still exist in IMAR corrected images, these images present with better overall conspicuity of the patient/phantom geometry and offer more accurate CT numbers for improved local dosimetry. The variety of different scenarios included herein attest to the utility of the evaluated IMAR for a wide range of radiotherapy clinical scenarios.

Radioluminescence microscopy is a new method for imaging radionuclide uptake by single live cells with a fluorescence microscope. Here, we report a particle-counting scheme that improves spatial resolution by overcoming the b-range limit. Methods: Short frames (10 ms21 s) were acquired using a high-gain camera coupled to a microscope to capture individual ionization tracks. Optical reconstruction of the b-ionization track (ORBIT) was performed to localize individual b decays, which were aggregated into a composite image. The new approach was evaluated by imaging the uptake of 18 F-FDG in nonconfluent breast cancer cells. Results: After image reconstruction, ORBIT resulted in better definition of individual cells. This effect was particularly noticeable in small clusters (2-4 cells), which occur naturally even for nonconfluent cell cultures. The annihilation and Bremsstrahlung photon background signal was markedly lower. Single-cell measurements of 18 F-FDG uptake that were computed from ORBIT images more closely matched the uptake of the fluorescent glucose analog (Pearson correlation coefficient, 0.54 vs. 0.44, respectively). Conclusion: ORBIT can image the uptake of a radiotracer in living cells with spatial resolution better than the b range. In principle, ORBIT may also allow for greater quantitative accuracy because the decay rate is measured more directly, with no dependency on the b-particle energy.Key Words: radionuclide imaging instrumentation; single-cell analysis; microscopy; autoradiography Nucl Med 2013; 54:1841 54: -1846 54: DOI: 10.2967 Aut oradiography is a well-established method for high-resolution imaging of radionuclide probes in tissues. Film and emulsion methods have the highest spatial resolution but poor sensitivity, dynamic range, and quantitative accuracy and require tedious sample preparation (1,2). Other autoradiography methods (e.g., storage phosphor (3), solid-state detection (4,5), gaseous detectors (6), and thin phosphor (7)) have higher sensitivity and dynamic range but spatial resolution worse than 50 mm. Only a few methods have demonstrated the ability to visualize the uptake of radionuclide probes with single-cell resolution. One of these methods uses a bsensitive avalanche photodiode to measure radionuclide uptake in small groups of cells, cultured in 16 microfluidic chambers (8). An experiment showed that the avalanche photodiode could measure signal from a single cell in the chamber. Another device, the MicroImager, achieved 15-mm spatial resolution for 35 S, which was used to detect in situ hybridization in single neurons (9). A third device, the radioluminescence microscope, was developed to visualize radionuclide uptake in live cells during fluorescence microscopy (10). Radioluminescence microscopy can be used to measure fluorescent and radionuclide signals emanating from a collection of living cells, in a relatively short time. Here we propose a new particlecounting scheme for radioluminescence microscopy with higher spatial resolution and, in principle, quantitative ...

Purpose: Gadolinium-based contrast agents (GBCAs) are widely administrated in MR imaging for diagnostic studies and treatment planning. Although GBCAs are generally thought to be safe, various health and environmental concerns have been raised recently about their use in MR imaging. The purpose of this work is to derive synthetic contrast enhance MR images from unenhanced counterpart images, thereby eliminating the need for GBCAs, using a cascade deep learning workflow that incorporates contour information into the network. Methods and materials: The proposed workflow consists of two sequential networks: (1) a retina U-Net, which is first trained to derive semantic features from the non-contrast MR images in representing the tumor regions; and (2) a synthesis module, which is trained after the retina U-Net to take the concatenation of the semantic feature maps and non-contrast MR image as input and to generate the synthetic contrast enhanced MR images. After network training, only the non-contrast enhanced MR images are required for the input in the proposed workflow. The MR images of 369 patients from the multimodal brain tumor segmentation challenge 2020 (BraTS2020) dataset were used in this study to evaluate the proposed workflow for synthesizing contrast enhanced MR images (200 patients for five-fold cross-validation and 169 patients for holdout test). Quantitative evaluations were conducted by calculating the normalized mean absolute error (NMAE), structural similarity index measurement (SSIM), and Pearson correlation coefficient (PCC). The original contrast enhanced MR images were considered as the ground truth in this analysis. Results: The proposed cascade deep learning workflow synthesized contrast enhanced MR images that are not visually differentiable from the ground truth with and without supervision of the tumor contours during the network training. Difference images and profiles of the synthetic contrast enhanced MR images revealed that intensity differences could be observed in the tumor region if the contour information was not incorporated in network training. Among the holdout test patients, mean values and standard deviations of the NMAE, SSIM, and PCC were 0.063±0.022, 0.991±0.007 and 0.995±0.006, respectively, for the whole brain; and were 0.050±0.025, 0.993±0.008 and 0.999±0.003, respectively, for the tumor contour regions. Quantitative evaluations with five-fold crossvalidation and hold-out test showed that the calculated metrics can be significantly enhanced (p-values ≤ 0.002) with the tumor contour supervision in network training. Conclusion:The proposed workflow was able to generate synthetic contrast enhanced MR images that closely resemble the ground truth images from non-contrast enhanced MR images when the network training included tumor 3278

Purpose: To investigate the effect of interplay between spot-scanning proton beams and respiration-induced tumor motion on internal target volume coverage for pediatric patients. Materials and Methods: Photon treatments for 10 children with representative tumor motions (1–13 mm superior-inferior) were replanned to simulate single-field uniform dose- optimized proton therapy. Static plans were designed by using average computed tomography (CT) data sets created from 4D CT data to obtain nominal dose distributions. The motion interplay effect was simulated by assigning each spot in the static plan delivery sequence to 1 of 10 respiratory-phase CTs, using the actual patient breathing trace and specifications of a synchrotron-based proton system. Dose distributions for individual phases were deformed onto the space of the average CT and summed to produce the accumulated dose distribution, whose dose-volume histogram was compared with the one from the static plan. Results: Tumor motion had minimal impact on the internal target volume hot spot (D2), which deviated by <3% from the nominal values of the static plans. The cold spot (D98) was also minimally affected, except in 2 patients with diaphragmatic tumor motion exceeding 10 mm. The impact on tumor coverage was more pronounced with respect to the V99 rather than the V95. Decreases of 10% to 49% in the V99 occurred in multiple patients for whom the beam paths traversed the lung-diaphragm interface and were, therefore, more sensitive to respiration-induced changes in the water equivalent path length. Fractionation alone apparently did not mitigate the interplay effect beyond 6 fractions. Conclusion: The interplay effect is not a concern when delivering scanning proton beams to younger pediatric patients with tumors located in the retroperitoneal space and tumor motion of <5 mm. Children and adolescents with diaphragmatic tumor motion exceeding 10 mm require special attention, because significant declines in target coverage and dose homogeneity were seen in simulated treatments of such patients.

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