Radiomics studies require many patients in order to power them, thus patients are often combined from different institutions and using different imaging protocols. Various studies have shown that imaging protocols affect radiomics feature values. We examined whether using data from cohorts with controlled imaging protocols improved patient outcome models. We retrospectively reviewed 726 CT and 686 PET images from head and neck cancer patients, who were divided into training or independent testing cohorts. For each patient, radiomics features with different preprocessing were calculated and two clinical variables—HPV status and tumor volume—were also included. A Cox proportional hazards model was built on the training data by using bootstrapped Lasso regression to predict overall survival. The effect of controlled imaging protocols on model performance was evaluated by subsetting the original training and independent testing cohorts to include only patients whose images were obtained using the same imaging protocol and vendor. Tumor volume, HPV status, and two radiomics covariates were selected for the CT model, resulting in an AUC of 0.72. However, volume alone produced a higher AUC, whereas adding radiomics features reduced the AUC. HPV status and one radiomics feature were selected as covariates for the PET model, resulting in an AUC of 0.59, but neither covariate was significantly associated with survival. Limiting the training and independent testing to patients with the same imaging protocol reduced the AUC for CT patients to 0.55, and no covariates were selected for PET patients. Radiomics features were not consistently associated with survival in CT or PET images of head and neck patients, even within patients with the same imaging protocol.

Age and sex-related variations in sternum morphology may affect the thoracic injury tolerance. Male and female sternum size and shape variation was characterized for ages 0-100 from landmarks collected from 330 computed tomography scans. Homologous landmarks were analyzed using Procrustes superimposition to produce age and sex-specific functions of 3D-sternum morphology representing the combined size and shape variation and the isolated shape variation. Significant changes in the combined size and shape variation and isolated shape variation of the sternum were found to occur with age in both sexes. Sternal size increased from birth through age 30 and retained a similar size for ages 30-100. The manubrium expanded laterally from birth through age 30, becoming wider in relation to the sternal body. In infancy, the manubrium was 1.1-1.2 times the width of the sternal body and this width ratio increased to 1.6-1.8 for adults. The manubrium transformed from a circular shape in infancy to an oval shape in early childhood. The distal sternal body became wider in relation to the proximal sternal body from birth through age 30 and retained this characteristic throughout adulthood. The most dramatic changes in sternum morphology occur in childhood and young adulthood when the sternum is undergoing ossification. The lesser degree of ossification in the pediatric sternum may be partly responsible for the prevalence of thoracic organ injuries as opposed to thoracic skeletal injuries in pediatrics. Sternum fractures make up a larger portion of thoracic injury patterns in adults with fully ossified sternums. The lack of substantial size or shape changes in the sternum from age 30-100 suggests that the increased incidence of sternal fracture seen in the elderly may be due to cortical thickness or bone mineral density changes in the sternum as opposed to morphological changes.

Developers and users of artificial-intelligence-based tools for automatic contouring and treatment planning in radiotherapy are expected to assess clinical acceptability of these tools. However, what is ‘clinical acceptability’? Quantitative and qualitative approaches have been used to assess this ill-defined concept, all of which have advantages and disadvantages or limitations. The approach chosen may depend on the goal of the study as well as on available resources. In this paper, we discuss various aspects of ‘clinical acceptability’ and how they can move us toward a standard for defining clinical acceptability of new autocontouring and planning tools.

BackgroundUnscheduled accelerator downtime can negatively impact the quality of life of patients during their struggle against cancer. Currently digital data accumulated in the accelerator system is not being exploited in a systematic manner to assist in more efficient deployment of service engineering resources. The purpose of this study is to develop an effective process for detecting unexpected deviations in accelerator system operating parameters and/or performance that predicts component failure or system dysfunction and allows maintenance to be performed prior to the actuation of interlocks.MethodsThe proposed predictive maintenance (PdM) model is as follows: 1) deliver a daily quality assurance (QA) treatment; 2) automatically transfer and interrogate the resulting log files; 3) once baselines are established, subject daily operating and performance values to statistical process control (SPC) analysis; 4) determine if any alarms have been triggered; and 5) alert facility and system service engineers. A robust volumetric modulated arc QA treatment is delivered to establish mean operating values and perform continuous sampling and monitoring using SPC methodology. Chart limits are calculated using a hybrid technique that includes the use of the standard SPC 3σ limits and an empirical factor based on the parameter/system specification.ResultsThere are 7 accelerators currently under active surveillance. Currently 45 parameters plus each MLC leaf (120) are analyzed using Individual and Moving Range (I/MR) charts. The initial warning and alarm rule is as follows: warning (2 out of 3 consecutive values ≥ 2σ hybrid) and alarm (2 out of 3 consecutive values or 3 out of 5 consecutive values ≥ 3σ hybrid). A customized graphical user interface provides a means to review the SPC charts for each parameter and a visual color code to alert the reviewer of parameter status. Forty-five synthetic errors/changes were introduced to test the effectiveness of our initial chart limits. Forty-three of the forty-five errors (95.6 %) were detected in either the I or MR chart for each of the subsystems monitored.ConclusionOur PdM model shows promise in providing a means for reducing unscheduled downtime. Long term monitoring will be required to establish the effectiveness of the model.

Reduced weight bearing, and to a lesser extent radiation, during spaceflight have been shown as potential hazards to astronaut joint health. These hazards combined effect to the knee and hip joints are not well defined, particularly with low-dose exposure to radiation. In this study, we examined the individual and combined effects of varying low-dose radiation (1 Gy) and reduced weight bearing on the cartilage of the knee and hip joints. C57BL/6J mice (n ¼ 80) were either tail suspended via hindlimb unloading (HLU) or remained full-weight bearing (ground). On day 6, each group was divided and irradiated with 0 Gy (sham), 0.1 Gy, 0.5 Gy or 1.0 Gy (n ¼ 10/group), yielding eight groups: ground-sham; ground-0.1 Gy; ground-0.5 Gy; ground-1.0 Gy; HLU-sham; HLU-0.1 Gy; HLU-0.5 Gy; and HLU-1.0 Gy. On day 30, the hindlimbs, hip cartilage and serum were collected from the mice. Significant differences were identified statistically between treatment groups and the ground-sham control group, but no significant differences were observed between HLU and/or radiation groups. Contrast-enhanced micro-computed tomography (micro-CECT) demonstrated decrease in volume and thickness at the weight-bearing femoral-tibial cartilage-cartilage contact point in all treatment groups compared to groundsham. Lower collagen was observed in all groups compared to ground-sham. Circulating serum cartilage oligomeric matrix protein (sCOMP), a biomarker for ongoing cartilage degradation, was increased in all of the irradiated groups compared to ground-sham, regardless of unloading. Mass spectrometry of the cartilage lining the femoral head and subsequent Ingenuity Pathway Analysis (IPA) identified a decrease in cartilage compositional proteins indicative of osteoarthritis. Our findings demonstrate that both individually and combined, HLU and exposure to spaceflight-relevant radiation doses lead to cartilage degradation of the knee and hip with expression of an arthritic phenotype. Moreover, early administration of low-dose irradiation (0.1, 0.5 or 1.0 Gy) causes an active catabolic response in cartilage 24 days postirradiation. Further research is warranted with a focus on the prevention of cartilage degradation from long-term periods of reduced weight bearing and spaceflight-relevant low doses and qualities of radiation.