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Background The aim of the current study was to explore the changing interrelationships among clinical variables through the stages of schizophrenia in order to assemble a comprehensive and meaningful disease model. Methods Twenty-nine centers from 25 countries participated and included 2358 patients aged 37.21 ±Â 11.87 years with schizophrenia. Multiple linear regression analysis and visual inspection of plots were performed. Results The results suggest that with progression stages, there are changing correlations among Positive and Negative Syndrome Scale factors at each stage and each factor correlates with all the others in that particular stage, in which this factor is dominant. This internal structure further supports the validity of an already proposed four stages model, with positive symptoms dominating the first stage, excitement/hostility the second, depression the third, and neurocognitive decline the last stage. Conclusions The current study investigated the mental organization and functioning in patients with schizophrenia in relation to different stages of illness progression. It revealed two distinct cores of schizophrenia, the Positive and the Negative, while neurocognitive decline escalates during the later stages. Future research should focus on the therapeutic implications of such a model. Stopping the progress of the illness could demand to stop the succession of stages. This could be achieved not only by both halting the triggering effect of positive and negative symptoms, but also by stopping the sensitization effect on the neural pathways responsible for the development of hostility, excitement, anxiety, and depression as well as the deleterious effect on neural networks responsible for neurocognition. © 2021 Cambridge University Press. All rights reserved.

Purpose: Dual-energy (DE) imaging is a method that suppresses bony anatomy on planar kV images while enhancing soft tissue contrast. This technique has been used specifically in the chest to improve the visualization of small lung tumors. However, DE imaging may also provide quantitative information that has not been previously investigated. In this study, the aim was to establish a theoretical relationship between DE image contrast and tumor thickness and to observe this trend in phantom experiments. Methods: A phantom consisting cork (used to simulate lung), tissue-equivalent material, and pork ribs was constructed to test for a relationship between DE image contrast and simulated tumor thickness. Fifteen phantom setups were used with various thicknesses of cork and tissue-equivalent material. For each setup, high (120 kVp) and low (60 kVp) energy planar images were acquired and DE images were produced. The image contrast between the simulated tumor and surrounding tissue was then plotted against the known thicknesses and a linear regression was performed. Results: A linear regression of the contrast data vs simulated tumor thickness resulted in a slope of −0.0454 with an R 2 = 0.9904. The expected uncertainty in the thickness measurements using the regression parameters and DE contrast standard deviation was 0.13 cm. Conclusions: Phantom data exhibited a linear relationship between DE image contrast and simulated tumor thickness. Future studies will investigate patient-specific parameters so that this method can be used clinically to evaluate tumor thickness from planar kV images. Such an approach may have benefits for both adaptive and heavy ion therapies.

Purpose: To evaluate the efficacy of dual-energy (DE) vs single-energy (SE) fluoroscopic imaging of lung tumors using a markerless template-based tracking algorithm. Methods: Ten representative patient breathing patterns were programmed into a Quasar™ motion phantom. The phantom was modified by affixing pork ribs to the surface, and a cedar insert with a small spherical volume was used to simulate lung and tumor, respectively. Sequential 60 kVp (6 mA) and 120 kVp (1.5 mA) fluoroscopic sequences were acquired. Frame-by-frame weighted logarithmic subtraction was performed resulting in a DE fluoroscopic sequence. A template-based algorithm was then used to track tumor motion throughout the DE and SE fluoroscopy sequences. Tracking coordinates were evaluated against ground-truth tumor locations. Fluoroscopic images were also acquired for two lung cancer patients, neither of which had implanted fiducials. Results: For phantom imaging, a total of 1925 frames were analyzed. The algorithm successfully tracked the target on 99.9% (1923/1925) of DE frames vs 90.7% (1745/1925) SE images (p 5 mm displacements from the ground truth vs 0% for DE fluoroscopy. Conclusions: This work indicates the potential for markerless tumor tracking utilizing DE fluoroscopy. With DE imaging, the algorithm showed improved detectability vs SE fluoroscopy and was able to accurately track the tumor in nearly all cases.

The purpose of this study was to survey current departmental policies on treatment couch overrides and the values of table tolerances used clinically. A 25‐question electronic survey on couch overrides and tolerances was sent to full members of the American Association of Physicists in Medicine (AAPM). The first part of the survey asked participants if table overrides were allowed at their institution, who was allowed to perform these overrides, and if imaging was required with overrides. The second part of the survey asked individuals to provide table tolerance data for the following treatment sites: brain/head and neck (H&N), lung, breast, abdomen/pelvis and prostate. Each site was further divided into IMRT/VMAT and 3D conformal techniques. Spaces for free‐text were provided, allowing respondents to enter any table tolerance data they were unable to specify under the treatment sites listed. A total of 361 individuals responded, of which approximately half participated in the couch tolerances portion of the survey. Overall, 86% of respondents’ institutions allow couch tolerance overrides at treatment. Therapists were the most common staff members permitted to perform overrides, followed by physicists, dosimetrists, and physicians, respectively. Of the institutions allowing overrides, 34% reported overriding daily. More than half of the centers document the override and/or require a setup image to radiographically verify the treatment site. With respect to table tolerances, SRS/SBRT table tolerances were the tightest, while clinical setup table tolerances were the largest. There were minimal statistically significant differences between IMRT/VMAT and 3D conformal table tolerances. Our results demonstrated that table overrides are relatively common in radiotherapy despite being a potential safety concern. Institutions should review their override policy and table tolerance values in light of the practices of other institutions. Careful attention to these matters is crucial in ensuring the safe and accurate delivery of radiotherapy. PACS number(s): 87.55.N‐, 87.55.Qr, 87.55.T‐

Purpose: Table overrides are relatively common in radiotherapy, yet are a potential safety concern. The goal of this study was to survey current departmental policies on treatment couch overrides and table tolerance values used clinically. Methods: A 25 question electronic survey on couch overrides and tolerances was sent to full members of the AAPM. In the first part of the survey, participants were asked: if table overrides were allowed at their institution, who was allowed to perform these overrides, and if imaging was required with overrides. In the second part of the survey, individuals were asked to provide table tolerance data for the following sites: brain/head & neck, lung, breast, abdomen/pelvis and prostate. Each site was further divided into IMRT/VMAT and 3D conformal techniques. Free-text spaces were provided, allowing respondents to enter any table tolerance data they were unable to specify under the treatment sites listed. Results: A total of 361 individuals responded, of which approximately half participated in the couch tolerances portion of the survey. Overall, 86% of respondents’ institutions allow couch tolerance overrides at treatment. Therapists were the most common staff members permitted to perform overrides, followed by physicists, dosimetrists, and physicians, respectively. Of the institutions allowing overrides, 34% reported overriding daily. More than half of the centers require documentation of the override and/or a setup image (acquired after override) to radiographically verify the treatment site. With respect to table tolerances, groups resulting from the free-text responses were at the two extremes; SRS/SBRT were the tightest, while clinical setup/mets/extremities were the most generous. There was no qualitative difference between IMRT/VMAT and 3D conformal table tolerances. Conclusion: This work is intended to stimulate a discussion within the radiotherapy community. This discussion, supplemented by the survey results provides an opportunity for institutions to enhance patient safety during daily treatment delivery.

Purpose: To evaluate the efficacy of dual energy (DE) vs. single energy (SE) fluoroscopic imaging in lung tumors using a markerless template-based tracking algorithm. Methods: Ten representative patient breathing patterns were programmed into a Quasar™ motion phantom. The phantom was modified by affixing pork ribs to the surface, and a cedar insert with a small spherical volume was used to simulate lung and tumor, respectively. Gated 60kVp(6mA) and 120kVp(1.5mA) fluoroscopic sequences were acquired using the Varian TrueBeam Integrated Imaging Solution. These high and low energy frames were subsequently aligned by phase and amplitude. Frame-by-frame weighted logarithmic subtraction was performed resulting in a DE fluoroscopic image sequence that highlighted soft tissue structures. A template-based algorithm was then used to track tumor motion throughout the sequence for DE and SE images (120kVp). Tracking coordinates were evaluated against ground truth tumor locations as identified by a physician. A displacement of greater than 3 mm was considered a non-successful track. The same process was also repeated for images obtained from 3 SBRT lung patients, none of which had implanted fiducials. Results: For phantom imaging, a total of 1925 frames were analyzed. The algorithm successfully tracked the target on 91.6%(1763/1925) of DE frames vs. 74.9%(1441/1923) SE images (p

Purpose: To compare markerless template-based tracking of lung tumors using dual energy (DE) cone-beam computed tomography (CBCT) projections versus single energy (SE) CBCT projections. Methods: A RANDO chest phantom with a simulated tumor in the upper right lung was used to investigate the effectiveness of tumor tracking using DE and SE CBCT projections. Planar kV projections from CBCT acquisitions were captured at 60 kVp (4 mAs) and 120 kVp (1 mAs) using the Varian TrueBeam and non-commercial iTools Capture software. Projections were taken at approximately every 0.53° while the gantry rotated. Due to limitations of the phantom, angles for which the shoulders blocked the tumor were excluded from tracking analysis. DE images were constructed using a weighted logarithmic subtraction that removed bony anatomy while preserving soft tissue structures. The tumors were tracked separately on DE and SE (120 kVp) images using a template-based tracking algorithm. The tracking results were compared to ground truth coordinates designated by a physician. Matches with a distance of greater than 3 mm from ground truth were designated as failing to track. Results: 363 frames were analyzed. The algorithm successfully tracked the tumor on 89.8% (326/363) of DE frames compared to 54.3% (197/363) of SE frames (p