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.

Incorporating axillary-lateral thoracic vessel juncture dosimetric variables improves model for predicting lymphedema in patients with breast cancer: A validation analysis.

Background: A relationship between the axillary-lateral thoracic vessel juncture (ALTJ) dose and lymphedema rate has been reported in patients with breast cancer. The purpose of this study was to validate this relationship and explore whether incorporation of the ALTJ dose-distribution parameters improves the prediction model's accuracy. Methods: A total of 1,449 women with breast cancer who were treated with multimodal therapies from two institutions were analyzed. We categorized regional nodal irradiation (RNI) as limited RNI, which excluded level I/II, vs extensive RNI, which included level I/II. The ALTJ was delineated retrospectively, and dosimetric and clinical parameters were analyzed to determine the accuracy of predicting the development of lymphedema. Decision tree and random forest algorithms were used to construct the prediction models of the obtained dataset. We used Harrell's C-index to assess discrimination. Results: The median follow-up time was 77.3 months, and the 5-year lymphedema rate was 6.8 %. According to the decision tree analysis, the lowest lymphedema rate (5-year, 1.2 %) was observed in patients with ≤ six removed lymph nodes and ≤ 66 % ALTJ V35Gy. The highest lymphedema rate was observed in patients with > 15 removed lymph nodes and an ALTJ maximum dose (Dmax) of > 53 Gy (5-year, 71.4 %). Patients with > 15 removed lymph nodes and an ALTJ Dmax ≤ 53 Gy had the second highest rate (5-year, 21.5 %). All other patients had relatively minor differences, with a rate of 9.5 % at 5 years. Random forest analysis revealed that the model's C-index increased from 0.84 to 0.90 if dosimetric parameters were included instead of RNI (P <.001). Conclusion: The prognostic value of ALTJ for lymphedema was externally validated. The estimation of lymphedema risk based on individual dose-distribution parameters of the ALTJ seemed more reliable than that based on the conventional RNI field design.

Abdominal synthetic CT reconstruction with intensity projection prior for MRI-only adaptive radiotherapy.

Objective. Owing to the superior soft tissue contrast of MRI, MRI-guided adaptive radiotherapy (ART) is well-suited to managing interfractional changes in anatomy. An MRI-only workflow is desirable, but producing synthetic CT (sCT) data through paired data-driven deep learning (DL) for abdominal dose calculations remains a challenge due to the highly variable presence of intestinal gas. We present the preliminary dosimetric evaluation of our novel approach to sCT reconstruction that is well suited to handling intestinal gas in abdominal MRI-only ART.Approach. We utilize a paired data DL approach enabled by the intensity projection prior, in which well-matching training pairs are created by propagating air from MRI to corresponding CT scans. Evaluations focus on two classes: patients with (1) little involvement of intestinal gas, and (2) notable differences in intestinal gas presence between corresponding scans. Comparisons between sCT-based plans and CT-based clinical plans for both classes are made at the first treatment fraction to highlight the dosimetric impact of the variable presence of intestinal gas.Main results. Class 1 patients (n= 13) demonstrate differences in prescribed dose coverage of the PTV of 1.3 ± 2.1% between clinical plans and sCT-based plans. Mean DVH differences in all structures for Class 1 patients are found to be statistically insignificant. In Class 2 (n= 20), target coverage is 13.3 ± 11.0% higher in the clinical plans and mean DVH differences are found to be statistically significant.Significance. Significant deviations in calculated doses arising from the variable presence of intestinal gas in corresponding CT and MRI scans result in uncertainty in high-dose regions that may limit the effectiveness of adaptive dose escalation efforts. We have proposed a paired data-driven DL approach to sCT reconstruction for accurate dose calculations in abdominal ART enabled by the creation of a clinically unavailable training data set with well-matching representations of intestinal gas.

Cumulative dose on fractional delivery of tomotherapy to periodically moving organ: a phantom QA suggestion.

This study was conducted to evaluate the cumulative dosimetric error that occurs in both target and surrounding normal tissues when treating a moving target in multifractional treatment with tomotherapy. An experiment was devised to measure cumulative error in multifractional treatments delivered to a horseshoe-shaped clinical target volume (CTV) surrounding a cylinder shape of organ at risk (OAR). Treatments differed in jaw size (1.05 vs 2.5cm), pitch (0.287 vs 0.660), and modulation factor (1.5 vs 2.5), and tumor motion characteristics differing in amplitude (1 to 3cm), period (3 to 5 second), and regularity (sinusoidal vs irregular) were tested. Treatment plans were delivered to a moving phantom up to 5-times exposure. Dose distribution on central coronal plane from 1 to 5 times exposure was measured with GAFCHROMIC EBT film. Dose differences occurring across 1 to 5 times exposure of treatment and between treatment plans were evaluated by analyzing measurements of gamma index, gamma index histogram, histogram changes, and dose at the center of the OAR. The experiment showed dose distortion due to organ motion increased between multiexposure 1 to 3 times but plateaued and remained constant after 3-times exposure. In addition, although larger motion amplitude and a longer period of motion both increased dosimetric error, the dose at the OAR was more significantly affected by motion amplitude rather than motion period. Irregularity of motion did not contribute significantly to dosimetric error when compared with other motion parameters. Restriction of organ motion to have small amplitude and short motion period together with larger jaw size and small modulation factor (with small pitch) is effective in reducing dosimetric error. Pretreatment measurements for 3-times exposure of treatment to a moving phantom with patient-specific tumor motion would provide a good estimation of the delivered dose distribution.

Synthesis and cytotoxicity of 1-substituted 2-methyl-1H-imidazo[4,5-g]phthalazine-4,9-dione derivatives.

A series of 1-substituted 2-methyl-1H-imidazo[4,5-g]phthalazine-4,9-dione derivatives 8 was synthesized from 6,7-dichlorophthalazine-5,8-dione 5 and evaluated for in vitro cytotoxicity against several human tumor cell lines. Most of the tested compounds showed potential cytotoxic activity considerably higher than that of the reference compounds, ellipticine and doxorubicin.