SHOULD PATIENT SETUP IN LUNG CANCER BE BASED ON THE PRIMARY TUMOR? AN ANALYSIS OF TUMOR COVERAGE AND NORMAL TISSUE DOSE USING REPEATED POSITRON EMISSION TOMOGRAPHY/COMPUTED TOMOGRAPHY IMAGING

PURPOSE: Evaluation of the dose distribution for lung cancer patients using a patient set-up procedure based on the bony anatomy or the primary tumor. METHODS AND MATERIALS: For 39 (non-)small cell lung cancer patients the planning FDG-PET/CT scan was registered to a repeated FDG-PET/CT scan made in the second week of treatment. Two patient set-up methods were analyzed: bony anatomy or primary tumor set-up. The original treatment plan was copied to the repeated scan, and target and normal tissue structures were delineated. Dose distributions were analyzed using dose-volume histograms for the primary tumor, lymph nodes, lungs and spinal cord. RESULTS: One patient showed decreased dose coverage of the primary tumor due to progressive disease and required re-planning to achieve adequate coverage. For the other patients, the minimum dose to the primary tumor did not significantly deviate from the planned dose: −0.2±1.7% (p=0.71) and −0.1±1.7% (p=0.85) for the bony anatomy and primary tumor set-up, respectively. For patients (N=31) with nodal involvement, 10% showed a decrease in minimum dose larger than 5% for the bony-anatomy set-up and 13% for the primary tumor based set-up. Mean lung dose exceeded the maximum allowed 20 Gy in 21% of the patients for the bony-anatomy and in 13% for the primary tumor set-up, whereas for the spinal cord this occurred in 10% and 13% of the patients, respectively. CONCLUSIONS: In 10% and 13% of patients with nodal involvement, set-up based on bony anatomy or primary tumor, respectively, lead to important dose deviations in nodal target volumes. Overdosage of critical structures occurred in 10-20% of the patients. In case of progressive disease, repeated imaging revealed underdosage of the primary tumor. Development of practical ways for set-up procedures based on repeated high-quality imaging of all tumor sites during radiotherapy should therefore be an important research focus

Assessment of bias in scoring of AI-based radiotherapy segmentation and planning studies using modified TRIPOD and PROBAST guidelines as an example

BACKGROUND AND PURPOSE Studies investigating the application of Artificial Intelligence (AI) in the field of radiotherapy exhibit substantial variations in terms of quality. The goal of this study was to assess the amount of transparency and bias in scoring articles with a specific focus on AI based segmentation and treatment planning, using modified PROBAST and TRIPOD checklists, in order to provide recommendations for future guideline developers and reviewers. MATERIALS AND METHODS The TRIPOD and PROBAST checklist items were discussed and modified using a Delphi process. After consensus was reached, 2 groups of 3 co-authors scored 2 articles to evaluate usability and further optimize the adapted checklists. Finally, 10 articles were scored by all co-authors. Fleiss' kappa was calculated to assess the reliability of agreement between observers. RESULTS Three of the 37 TRIPOD items and 5 of the 32 PROBAST items were deemed irrelevant. General terminology in the items (e.g., multivariable prediction model, predictors) was modified to align with AI-specific terms. After the first scoring round, further improvements of the items were formulated, e.g., by preventing the use of sub-questions or subjective words and adding clarifications on how to score an item. Using the final consensus list to score the 10 articles, only 2 out of the 61 items resulted in a statistically significant kappa of 0.4 or more demonstrating substantial agreement. For 41 items no statistically significant kappa was obtained indicating that the level of agreement among multiple observers is due to chance alone. CONCLUSION Our study showed low reliability scores with the adapted TRIPOD and PROBAST checklists. Although such checklists have shown great value during development and reporting, this raises concerns about the applicability of such checklists to objectively score scientific articles for AI applications. When developing or revising guidelines, it is essential to consider their applicability to score articles without introducing bias

Evaluating Tumor Response of Non-Small Cell Lung Cancer Patients With F-18-Fludeoxyglucose Positron Emission Tomography: Potential for Treatment Individualization

Objective: To assess early tumor responsiveness and the corresponding effective radiosensitivity for individual patients with non-small cell lung cancer (NSCLC) based on 2 successive F-18-fludeoxyglucose positron emission tomography (FDG-PET) scans. Methods and Materials: Twenty-six NSCLC patients treated in Maastricht were included in the study. Fifteen patients underwent sequential chemoradiation therapy, and 11 patients received concomitant chemoradiation therapy. All patients were imaged with FDG before the start and during the second week of radiation therapy. The sequential images were analyzed in relation to the dose delivered until the second image. An operational quantity, effective radiosensitivity, alpha(eff), was determined at the voxel level. Correlations were sought between the average aeff or the fraction of negative aeff values and the overall survival at 2 years. Separate analyses were performed for the primary gross target volume (GTV), the lymph node GTV, and the clinical target volumes (CTVs). Results: Patients receiving sequential treatment could be divided into responders and nonresponders, using a threshold for the average alpha(eff) of 0.003 Gy(-1) in the primary GTV, with a sensitivity of 75% and a specificity of 100% (

Image quality evaluation of a new high-performance ring-gantry cone-beam computed tomography imager

Objective. Newer cone-beam computed tomography (CBCT) imaging systems offer reconstruction algorithms including metal artifact reduction (MAR) and extended field-of-view (eFoV) techniques to improve image quality. In this study a new CBCT imager, the new Varian HyperSight CBCT, is compared to fan-beam CT and two CBCT imagers installed in a ring-gantry and C-arm linear accelerator, respectively. Approach. The image quality was assessed for HyperSight CBCT which uses new hardware, including a large-size flat panel detector, and improved image reconstruction algorithms. The decrease of metal artifacts was quantified (structural similarity index measure (SSIM) and root-mean-squared error (RMSE)) when applying MAR reconstruction and iterative reconstruction for a dental and spine region using a head-and-neck phantom. The geometry and CT number accuracy of the eFoV reconstruction was evaluated outside the standard field-of-view (sFoV) on a large 3D-printed chest phantom. Phantom size dependency of CT numbers was evaluated on three cylindrical phantoms of increasing diameter. Signal-to-noise and contrast-to-noise were quantified on an abdominal phantom. Main results. In phantoms with streak artifacts, MAR showed comparable results for HyperSight CBCT and CT, with MAR increasing the SSIM (0.97-0.99) and decreasing the RMSE (62-55 HU) compared to iterative reconstruction without MAR. In addition, HyperSight CBCT showed better geometrical accuracy in the eFoV than CT (Jaccard Conformity Index increase of 0.02-0.03). However, the CT number accuracy outside the sFoV was lower than for CT. The maximum CT number variation between different phantom sizes was lower for the HyperSight CBCT imager (∼100 HU) compared to the two other CBCT imagers (∼200 HU), but not fully comparable to CT (∼50 HU). Significance. This study demonstrated the imaging performance of the new HyperSight CBCT imager and the potential of applying this CBCT system in more advanced scenarios by comparing the quality against fan-beam CT.</p

Image quality evaluation of a new high-performance ring-gantry cone-beam computed tomography imager

Objective. Newer cone-beam computed tomography (CBCT) imaging systems offer reconstruction algorithms including metal artifact reduction (MAR) and extended field-of-view (eFoV) techniques to improve image quality. In this study a new CBCT imager, the new Varian HyperSight CBCT, is compared to fan-beam CT and two CBCT imagers installed in a ring-gantry and C-arm linear accelerator, respectively. Approach. The image quality was assessed for HyperSight CBCT which uses new hardware, including a large-size flat panel detector, and improved image reconstruction algorithms. The decrease of metal artifacts was quantified (structural similarity index measure (SSIM) and root-mean-squared error (RMSE)) when applying MAR reconstruction and iterative reconstruction for a dental and spine region using a head-and-neck phantom. The geometry and CT number accuracy of the eFoV reconstruction was evaluated outside the standard field-of-view (sFoV) on a large 3D-printed chest phantom. Phantom size dependency of CT numbers was evaluated on three cylindrical phantoms of increasing diameter. Signal-to-noise and contrast-to-noise were quantified on an abdominal phantom. Main results. In phantoms with streak artifacts, MAR showed comparable results for HyperSight CBCT and CT, with MAR increasing the SSIM (0.97-0.99) and decreasing the RMSE (62-55 HU) compared to iterative reconstruction without MAR. In addition, HyperSight CBCT showed better geometrical accuracy in the eFoV than CT (Jaccard Conformity Index increase of 0.02-0.03). However, the CT number accuracy outside the sFoV was lower than for CT. The maximum CT number variation between different phantom sizes was lower for the HyperSight CBCT imager (∼100 HU) compared to the two other CBCT imagers (∼200 HU), but not fully comparable to CT (∼50 HU). Significance. This study demonstrated the imaging performance of the new HyperSight CBCT imager and the potential of applying this CBCT system in more advanced scenarios by comparing the quality against fan-beam CT.</p

An investigation into the risk of population bias in deep learning autocontouring

Background and Purpose: To date, data used in the development of Deep Learning-based automatic contouring (DLC) algorithms have been largely sourced from single geographic populations. This study aimed to evaluate the risk of population-based bias by determining whether the performance of an autocontouring system is impacted by geographic population.Materials and methods: 80 Head Neck CT deidentified scans were collected from four clinics in Europe (n = 2) and Asia (n = 2). A single observer manually delineated 16 organs-at-risk in each. Subsequently, the data was contoured using a DLC solution, and trained using single institution (European) data. Autocontours were compared to manual delineations using quantitative measures. A Kruskal-Wallis test was used to test for any difference between populations. Clinical acceptability of automatic and manual contours to observers from each participating institution was assessed using a blinded subjective evaluation.Results: Seven organs showed a significant difference in volume between groups. Four organs showed statistical differences in quantitative similarity measures. The qualitative test showed greater variation in acceptance of contouring between observers than between data from different origins, with greater acceptance by the South Korean observers.Conclusion: Much of the statistical difference in quantitative performance could be explained by the difference in organ volume impacting the contour similarity measures and the small sample size. However, the qualitative assessment suggests that observer perception bias has a greater impact on the apparent clinical acceptability than quantitatively observed differences. This investigation of potential geographic bias should extend to more patients, populations, and anatomical regions in the future.</p

Early CT and FDG-metabolic tumour volume changes show a significant correlation with survival in stage I-III small cell lung cancer: A hypothesis generating study

BACKGROUND: Many patients with stage I–III small cell lung cancer (SCLC) experience disease progression short after the completion of concurrent chemoradiotherapy (CRT). The purpose of the current study was to evaluate whether CT or FDG metabolic response early after the start of chemotherapy, but before the beginning of chest RT, is predictive for survival in SCLC. METHODS: Fifteen stage I–III SCLC patients treated with concurrent CRT with an FDG-PET and CT scan available before the start of chemotherapy and after or during the first cycle of chemotherapy, but before the start of radiotherapy, were selected. The metabolic volume (MV) was defined both within the primary tumour and in the involved nodal stations using the 40% (MV40) and 50% (MV50) threshold of the maximum SUV. Metabolic and CT response was assessed by the relative change in MV and CT volume, respectively, between both time points. The association between response and overall survival (OS) was analysed by univariate cox regression analysis. The minimum follow-up was 18 months. RESULTS: Reductions in MV40 and MV50 were −36 ± 38% (126.4 to 68.7 cm(3)) and −44 ± 38% (90.2 to 27.8 cm(3)), respectively. The median CT volume reduction was −40 ± 64% (190.6 to 113.8 cm(3)). MV40 and MV50 changes showed a significant association with survival (HR = 1.02, 95% CI: 1.00–1.04 (p = 0.042); HR = 1.02, 95% CI: 1.00–1.04 (p = 0.048), respectively), indicating a 2% increase in survival probability for 1% reduction in metabolic volume. The CT volume change was also significantly correlated with survival (HR = 1.01, 95% CI: 1.00–1.03, p = 0.007). CONCLUSIONS: This hypothesis generating study shows that both the early CT and the MV changes show a significant correlation with survival in SCLC. A prospective study is planned in a larger patient cohort to allow multivariate analysis, with the final aim to select patients early during treatment that could benefit from dose intensification or alternative treatment