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Abstract Introduction Growth differentiation factor 15 (GDF15) is a cytokine of the TGFβ family. Here, we analyzed GDF15 levels in patients with locally advanced non-small cell lung cancer (LA-NSCLC) who participated in OCOG-ALMERA (NCT02115464), a phase II randomized clinical trial, that investigated metformin in combination with standard of care concurrent chemoradiotherapy (cCRT). OCOG-ALMERA was not able to demonstrate benefit in the metformin arm. Therefore, biomarker studies are needed to better define stratification parameters for future trials. Methods Patients were randomized to treatment with platinum-based chemotherapy and concurrent chest radiotherapy (60–66 Gy), with or without metformin (2000 mg/d). The trial collected tumor volume parameters, survival outcomes, and patient blood plasma at baseline, during (weeks 1 and 6) and 6 months after cCRT. Plasma GDF15 levels were assayed with the ELISA method. Statistical analyses explored associations between GDF15, survival outcomes, and radiotherapy tumor volumes. Results Baseline plasma levels of GDF15 were elevated in study patients, they increased during cCRT (p

Purpose: To report on the Stereotactic Body Radiation Therapy (SBRT) credentialing experience during the Phase III Ontario Clinical Oncology Group (OCOG) LUSTRE trial for stage I non-small cell lung cancer. Methods: Three credentialing requirements were required in this process: (a) An institutional technical survey; (b) IROC (Imaging and Radiation Oncology Core) thoracic phantom end-to-end test; and (c) Contouring and completion of standardized test cases using SBRT for one central and one peripheral lung cancer, compared against the host institution as the standard. The main hypotheses were that unacceptable variation would exist particularly in OAR definition across all centres, and that institutions with limited experience in SBRT would be more likely to violate per-protocol guidelines. Results: Fifteen Canadian centres participated of which 8 were new, and 7 were previously established (≥2 years SBRT experience), and all successfully completed surveys and IROC phantom testing. Of 30 SBRT test plans, 10 required replanning due to major deviations, with no differences in violations between new and established centres (p = 0.61). Mean contouring errors were highest for brachial plexus in the central (C) case (12.55 ± 6.62 mm), and vessels in the peripheral (P) case (13.01 ± 12.55 mm), with the proximal bronchial tree (PBT) (2.82 ± 0.78 C, 3.27 ± 1.06 P) as another variable structure. Mean dice coefficients were lowest for plexus (0.37 ± 0.2 C, 0.37 ± 0.14 P), PBT (0.77 ± 0.06 C, 0.75 ± 0.09 P), vessels (0.69 ± 0.29 C, 0.64 ± 0.31 P), and esophagus (0.74 ± 0.04 C, 0.76 ± 0.04 P). All plans passed per-protocol planning target volume (PTV) coverage and maximum/volumetric organs-at-risk constraints, although variations existed in dose gradients within and outside the target. Conclusions: Clear differences exist in both contouring and planning with lung SBRT, regardless of centre experience. Such an exercise is important for studies that rely on high precision radiotherapy, and to ensure that implications on trial quality and outcomes are as optimal as possible.

Three-dimensional visualization for planning and guidance is still not routinely available for minimally invasive cardiac surgery (MICS). This can be addressed by providing the surgeon with subject-specific geometric models derived from 3D preoperative images for planning of port locations or to rehearse the procedure. For guidance purposes, these models can also be registered to the subject using intraoperative images. In this paper, we present a method for extracting subject-specific heart geometry from preoperative MR images. The main obstacle we face is the low quality of clinical data in terms of resolution, signal-to-noise ratio, and presence of artefacts. Instead of using these images directly, we approach the problem in three steps: (1) generate a high quality template model, (2) register the template with the preoperative data, and (3) animate the result over the cardiac cycle. Validation of this approach showed that dynamic subject-specific models can be generated with a mean error of 3.6 ± 1.1 mm from low resolution target images (6 mm slices). Thus, the models are sufficiently accurate for MICS training and procedure planning. In terms of guidance, we also demonstrate how the resulting models may be adapted to the operating room using intraoperative ultrasound imaging. [ABSTRACT FROM AUTHOR]