Sensitivity and specificity of Monte Carlo based independent secondary dose computation for detecting modulation-related dose errors in intensity modulated radiotherapy

BACKGROUND

The recent availability of Monte Carlo based independent secondary dose calculation (ISDC) for patient-specific quality assurance (QA) of modulated radiotherapy requires the definition of appropriate, more sensitive action levels, since contemporary recommendations were defined for less accurate ISDC dose algorithms.

PURPOSE

The objective is to establish an optimum action level and measure the efficacy of a Monte Carlo ISDC software for pre-treatment QA of intensity modulated radiotherapy treatments.

METHODS

The treatment planning system and the ISDC were commissioned by their vendors from independent base data sets, replicating a typical real-world scenario. In order to apply Receiver-Operator-Characteristics (ROC), a set of treatment plans for various case classes was created that consisted of 190 clinical treatment plans and 190 manipulated treatment plans with dose errors in the range of 1.5-2.5%. All 380 treatment plans were evaluated with ISDC in the patient geometry. ROC analysis was performed for a number of Gamma (dose-difference/distance-to-agreement) criteria. QA methods were ranked according to Area under the ROC curve (AUC) and optimum action levels were derived via Youden's J statistics.

RESULTS

Overall, for original treatment plans, the mean Gamma pass rate (GPR) for Gamma(1%, 1 mm) was close to 90%, although with some variation across case classes. The best QA criterion was Gamma(2%, 1 mm) with GPR > 90% and an AUC of 0.928. Gamma criteria with small distance-to-agreement had consistently higher AUC. GPR of original treatment plans depended on their modulation degree. An action level in terms of Gamma(1%, 1 mm) GPR that decreases with modulation degree was the most efficient criterion with sensitivity = 0.91 and specificity = 0.95, compared with Gamma(3%, 3 mm) GPR > 99%, sensitivity = 0.73 and specificity = 0.91 as a commonly used action level.

CONCLUSIONS

ISDC with Monte Carlo proves highly efficient to catch errors in the treatment planning process. For a Monte Carlo based TPS, dose-difference criteria of 2% or less, and distance-to-agreement criteria of 1 mm, achieve the largest AUC in ROC analysis.

Sarcopenic Obesity Is a Risk Factor for Worse Oncological Long-Term Outcome in Locally Advanced Rectal Cancer Patients: A Retrospective Single-Center Cohort Study

BACKGROUND

Malnutrition and skeletal muscle waste (sarcopenia) are known as predictive factors for a poor postoperative outcome. Paradoxically, obesity seems to be associated with a survival advantage in wasting diseases such as cancer. Thus, the interpretation of body composition indices and their impact on rectal cancer therapy has become more and more complex. The aim of this study was to evaluate body composition indices in locally advanced rectal cancer patients prior to therapy and their impact on short- and long-term outcomes.

METHODS

Between 2008 and 2018, 96 patients were included in this study. Pre-therapeutic CT scans were used to evaluate visceral and subcutaneous fat mass, as well as muscle mass. Body composition indices were compared to body mass index, morbidity, anastomotic leakage rate, local recurrency rate, and oncological long-term outcomes.

RESULTS

Increased visceral fat (p < 0.01), subcutaneous fat (p < 0.01), and total fat mass (p = 0.001) were associated with overweight. Skeletal muscle waste (sarcopenia) (p = 0.045), age (p = 0.004), comorbidities (p < 0.01), and sarcopenic obesity (p = 0.02) were significantly associated with increased overall morbidity. The anastomotic leakage rate was significantly influenced when comorbidities were present (p = 0.006). Patients with sarcopenic obesity showed significantly worse disease-free (p = 0.04) and overall survival (p = 0.0019). The local recurrency rate was not influenced by body composition indices.

CONCLUSION

Muscle waste, older age, and comorbidities were demonstrated as strong risk factors for increased overall morbidity. Sarcopenic obesity was associated with worse DFS and OS. This study underlines the role of nutrition and appropriate physical activity prior to therapy.

Evaluation of 4-Hz log files and secondary Monte Carlo dose calculation as patient-specific quality assurance for VMAT prostate plans

Purpose

In this study, 4‐Hz log files were evaluated with an independent secondary Monte Carlo dose calculation algorithm to reduce the workload for patient‐specific quality assurance (QA) in clinical routine.

Materials and Methods

A total of 30 randomly selected clinical prostate VMAT plans were included. The used treatment planning system (TPS) was Monaco (Elekta, Crawley), and the secondary dose calculation software was SciMoCa (Scientific‐RT, Munich). Monaco and SciMoCa work with a Monte Carlo algorithm. A plausibility check of Monaco and SciMoCa was performed using an ionization chamber in the BodyPhantom (BP). First, the original Monaco RT plans were verified with SciMoCa (pretreatment QA). Second, the corresponding 4‐Hz log files were converted into RT log file plans and sent to SciMoCa as on‐treatment QA. MLC shift errors were introduced for one prostate plan to determine the sensitivity of on‐treatment QA. For pretreatment and on‐treatment QA, a gamma analysis (2%/1mm/20%) was performed and dosimetric values of PTV and OARs were ascertained in SciMoCa.

Results

Plausibility check of TPS Monaco vs. BP measurement and SciMoCa vs. BP measurement showed valid accuracy for clinical VMAT QA. Using SciMoCa, there was no significant difference in PTV Dmean between RT plan and RT log file plan. Between pretreatment and on‐treatment QA, PTV metrics, femur right and left showed no significant dosimetric differences as opposed to OARs rectum and bladder. The overall gamma passing rate (GPR) ranged from 96.10% to 100% in pretreatment QA and from 93.50% to 99.80% in on‐treatment QA. MLC shift errors were identified for deviations larger than −0.50 mm and +0.75 mm using overall gamma criterion and PTV Dmean.

Conclusion

SciMoCa calculations of Monaco RT plans and RT log file plans are in excellent agreement to each other. Therefore, 4‐Hz log files and SciMoCa can replace labor‐intensive phantom‐based measurements as patient‐specific QA.

Error sensitivity of a log file analysis tool compared with a helical diode array dosimeter for VMAT delivery quality assurance

PURPOSE

Integrating log file analysis with LINACWatch® (LW) into clinical routine as part of the quality assurance (QA) process could be a time-saving strategy that does not compromise on quality. The purpose is to determine the error sensitivity of log file analysis using LINACWatch® compared with a measurement device (ArcCHECK®, AC) for VMAT delivery QA.

MATERIALS AND METHODS

Multi-leaf collimator (MLC) errors, collimator angle errors, MLC shift errors and dose errors were inserted to analyze error detection sensitivity. A total of 36 plans were manipulated with different magnitudes of errors. The gamma index protocols for AC were 3%/3 mm/Global and 2%/2 mm/Global, as well as 2%/2 mm/Global, and 1.5%/1.5 mm/Global for LW. Additionally, deviations of the collimator and monitor units between TPS and log file were calculated as RMS values. A 0.125 cm³ ionization chamber was used to independently examine the effect on dose.

RESULTS

The sensitivity for AC was 20.4% and 49.6% vs 63.0% and 86.5% for LW, depending on the analysis protocol. For MLC opening and closing errors, the detection rate was 19.0% and 47.7% for AC vs 50.5% and 75.5% for LW. For MLC shift errors, it was 29.6% and 66.7% for AC vs 66.7% and 83.3% for LW. AC could detect 25.0% and 44.4% of all collimator errors. Log file analysis detected all collimator errors using 1° detection level. 13.2% and 42.4% of all dose errors were detected by AC vs 59.0% and 92.4% for LW using gamma analysis. Using RMS value, all dose errors were detected by LW (1% detection level).

CONCLUSION

The results of this study clearly show that log file analysis is an excellent complement to phantom-based delivery QA of VMAT plans. We recommend a 1.5%/1.5 mm/Global criteria for log file-based gamma calculations. Log file analysis was implemented successfully in our clinical routine for VMAT delivery QA.