Stephen Wan Leung

Dosimetric comparisons of helical tomotherapy and step-and-shoot intensity-modulated radiotherapy in nasopharyngeal carcinoma

PURPOSE The study evaluates and quantifies the potential dosimetric gains of helical tomotherapy (HT) versus step-and-shoot intensity-modulated radiotherapy (SaS-IMRT) for nasopharyngeal carcinoma (NPC). MATERIALS AND METHODS Twenty consecutive NPC patients curatively treated by HT were examined. Each case was planned by HT and SaS-IMRT (ADAC Pinnacle(3)) planning system, respectively. Dose plans were compared using dose volume histograms (DVH), conformity index (CI), homogeneity index (HI), and minimal dose to 1cc (D(min_1cc)) of the planned target volume (PTV) and a comprehensive quality index (CQI) of ten organs at risk (OARs). The prescribed dose/fractionation was 72Gy to the PTV, 64.8Gy to the elective PTV, and 54Gy to the clinically negative neck region. The plan of 54Gy to the PTV (PTV(54)) was used to evaluate the CI and HI in the target. The cumulative doses of the three PTV plans to the OARs were calculated. RESULTS We observed the HT plans significantly improved the CI (improvement ratio: 11.9+/-5.5%) and HI (improvement ratio: 8.8+/-1.5%) of the PTV(54) compared with SaS-IMRT plans. In addition, the mean/maximal dose of most of the OARs except chiasm was significantly reduced in HT plans, with the CQI of 0.92+/-0.08. A negative result of HT in chiasm was observed but only significantly revealed in cases without skull base infiltration. CONCLUSIONS A dosimetric gain in CI and HI of PTV and sparing of OARs was significantly obtained in HT versus SaS-IMRT plans in NPC patients. Whether such dosimetric superiority in HT could transfer into clinical advantages needs further investigation.

Health-related quality of life in 640 head and neck cancer survivors after radiotherapy using EORTC QLQ-C30 and QLQ-H&N35 questionnaires.

BackgroundWith the advances in modern radiotherapy (RT), many patients with head and neck cancer (HNC) can be effectively cured, and their health-related quality of life (HR-QoL) has become an important issue. In this study, we evaluated the prognosticators of HR-QoL in a large cohort of HNC patients, with a focus on the result from technological advances in RT.MethodsA cross-sectional investigation was conducted to assess the HR-QoL of 640 HNC patients with cancer-free survival of more than 2 years. Among them, 371 patients were treated by two-dimensional RT (2DRT), 127 by three-dimensional conformal RT (3DCRT), and 142 by intensity-modulated RT (IMRT). The EORTC QLQ-C30 questionnaire and QLQ-H&N35 module were used. A general linear model multivariate analysis of variance was used to analyze the prognosticators of HR-QoL.ResultsBy multivariate analysis, the variables of gender, annual family income, tumor site, AJCC stage, treatment methods, and RT technique were prognosticators for QLQ-C30 results, so were tumor site and RT technique for H&N35. Significant difference (p < 0.05) of HR-QoL outcome by different RT techniques was observed at 2 of the 15 scales in QLQ-C30 and 10 of the 13 scales in H&N35. Compared with 2DRT, IMRT had significant better outcome in the scales of global QoL, physical functioning, swallowing, senses (taste/smell), speech, social eating, social contact, teeth, opening mouth, dry mouth, sticky saliva, and feeling ill.ConclusionsThe technological advance of RT substantially improves the head-and-neck related symptoms and broad aspects of HR-QoL for HNC survivors.

Using Multivariate Regression Model with Least Absolute Shrinkage and Selection Operator (LASSO) to Predict the Incidence of Xerostomia after Intensity-Modulated Radiotherapy for Head and Neck Cancer

Purpose The aim of this study was to develop a multivariate logistic regression model with least absolute shrinkage and selection operator (LASSO) to make valid predictions about the incidence of moderate-to-severe patient-rated xerostomia among head and neck cancer (HNC) patients treated with IMRT. Methods and Materials Quality of life questionnaire datasets from 206 patients with HNC were analyzed. The European Organization for Research and Treatment of Cancer QLQ-H&N35 and QLQ-C30 questionnaires were used as the endpoint evaluation. The primary endpoint (grade 3+ xerostomia) was defined as moderate-to-severe xerostomia at 3 (XER3m) and 12 months (XER12m) after the completion of IMRT. Normal tissue complication probability (NTCP) models were developed. The optimal and suboptimal numbers of prognostic factors for a multivariate logistic regression model were determined using the LASSO with bootstrapping technique. Statistical analysis was performed using the scaled Brier score, Nagelkerke R2, chi-squared test, Omnibus, Hosmer-Lemeshow test, and the AUC. Results Eight prognostic factors were selected by LASSO for the 3-month time point: Dmean-c, Dmean-i, age, financial status, T stage, AJCC stage, smoking, and education. Nine prognostic factors were selected for the 12-month time point: Dmean-i, education, Dmean-c, smoking, T stage, baseline xerostomia, alcohol abuse, family history, and node classification. In the selection of the suboptimal number of prognostic factors by LASSO, three suboptimal prognostic factors were fine-tuned by Hosmer-Lemeshow test and AUC, i.e., Dmean-c, Dmean-i, and age for the 3-month time point. Five suboptimal prognostic factors were also selected for the 12-month time point, i.e., Dmean-i, education, Dmean-c, smoking, and T stage. The overall performance for both time points of the NTCP model in terms of scaled Brier score, Omnibus, and Nagelkerke R2 was satisfactory and corresponded well with the expected values. Conclusions Multivariate NTCP models with LASSO can be used to predict patient-rated xerostomia after IMRT.

Helical tomotherapy for single and multiple liver tumours.

PurposeDosimetric evaluations of single and multiple liver tumours performed using intensity-modulated helical tomotherapy (HT) were quantitatively investigated. Step-and-shoot intensity-modulated radiotherapy (SaS-IMRT) was used as a benchmark.MethodsSixteen patients separated into two groups with primary hepatocellular carcinomas or metastatic liver tumours previously treated using SaS-IMRT were examined and re-planned by HT. The dosimetric indices used included the conformity index (CI) and homogeneity index (HI) for the planned target volume (PTV), max/mean dose, quality index (QI), normal tissue complication probability (NTCP), V30 Gy, and V50%for the specified organs at risk (OARs). The monitor units per fraction (MU/fr) and delivery time were also analysed.ResultsFor the single tumour group, both planning systems satisfied the required PTV prescription, but no statistical significance was shown by the indexes checking. A shorter delivery time and lower MU/fr value were achieved by the SaS-IMRT. For the group of multiple tumours, the average improvement in CI and HI was 14% and 4% for HT versus SaS-IMRT, respectively. Lower V50%, V30 Gy and QI values were found, indicating a significant dosimetric gain in HT. The NTCP value of the normal liver was 20.27 ± 13.29% for SaS-IMRT and 2.38 ± 2.25% for HT, indicating fewer tissue complications following HT. The latter also required a shorter delivery time.ConclusionsOur study suggests dosimetric benefits of HT over SaS-IMRT plans in the case of multiple liver tumours, especially with regards sparing of OARs. No significant dosimetric difference was revealed in the case of single liver tumour, but SaS-IMRT showed better efficiency in terms of MU/fr and delivery time.

Patient- and therapy-related factors associated with the incidence of xerostomia in nasopharyngeal carcinoma patients receiving parotid-sparing helical tomotherapy

We investigated the incidence of moderate to severe patient-reported xerostomia among nasopharyngeal carcinoma (NPC) patients treated with helical tomotherapy (HT) and identified patient- and therapy-related factors associated with acute and chronic xerostomia toxicity. The least absolute shrinkage and selection operator (LASSO) normal tissue complication probability (NTCP) models were developed using quality-of-life questionnaire datasets from 67 patients with NPC. For acute toxicity, the dosimetric factors of the mean doses to the ipsilateral submandibular gland (Dis) and the contralateral submandibular gland (Dcs) were selected as the first two significant predictors. For chronic toxicity, four predictive factors were selected: age, mean dose to the oral cavity (Doc), education, and T stage. The substantial sparing data can be used to avoid xerostomia toxicity. We suggest that the tolerance values corresponded to a 20% incidence of complications (TD20) for Dis = 39.0 Gy, Dcs = 38.4 Gy, and Doc = 32.5 Gy, respectively, when mean doses to the parotid glands met the QUANTEC 25 Gy sparing guidelines. To avoid patient-reported xerostomia toxicity, the mean doses to the parotid gland, submandibular gland, and oral cavity have to meet the sparing tolerance, although there is also a need to take inherent patient characteristics into consideration.

A decision support model for investment on P2P lending platform

Peer-to-peer (P2P) lending, as a novel economic lending model, has triggered new challenges on making effective investment decisions. In a P2P lending platform, one lender can invest N loans and a loan may be accepted by M investors, thus forming a bipartite graph. Basing on the bipartite graph model, we built an iteration computation model to evaluate the unknown loans. To validate the proposed model, we perform extensive experiments on real-world data from the largest American P2P lending marketplace—Prosper. By comparing our experimental results with those obtained by Bayes and Logistic Regression, we show that our computation model can help borrowers select good loans and help lenders make good investment decisions. Experimental results also show that the Logistic classification model is a good complement to our iterative computation model, which motivates us to integrate the two classification models. The experimental results of the hybrid classification model demonstrate that the logistic classification model and our iteration computation model are complementary to each other. We conclude that the hybrid model (i.e., the integration of iterative computation model and Logistic classification model) is more efficient and stable than the individual model alone.

Quality Assurance Schedule and Practical Experience with Helical Tomotherapy

Purpose: We present a quality assurance (QA) schedule for the Hi-Art Helical Tomo-Therapy unit and share our QA practical experience with this state-of-the-art machine. According to the Ionizing Radiation Protection Act (Article. 17, item 3), the regulation of medical exposure QA in Taiwan has to include daily, monthly, and annual items in the schedule for every treatment machine in a radiation oncology department. The Hi-Art Helical Tomo-Therapy unit was developed at the University of Wisconsin-Madison in 2003. We installed a new system at Yuans General Hospital to take the lead in South- Taiwan in April 2006. In this study, we present the QA schedule that is performed in our department, which follows the principles of AAPM TG-40 but contains some novel components, reflecting the differences between the Hi-Art device and conventional linear accelerators. Materials and Methods: We compared the efficiency of the daily, monthly, and annual QA programs in our department with Hi-Art Helical Tomo-Therapy unit and an Elekta-Precise linear accelerator with a standard QA schedule. We followed the principles of AAPM TG-40. For tomotherapy, the QA program included a series of measurements that were recorded in a specially fabricated, cylindrically symmetric Virtual Water phantom. This was designed specifically for commissioning the Helical Tomo-Therapy unit and QA. The phantom is 30cm in diameter, 18cm long, and is divided into two halves, such that film may be placed between them. To perform the measurements of the dosimetry parameters and correction factors, three EXRADIN-A1SL ion chambers and a Standard Imaging-TomoEletrometer were used for the Helical Tomo-Therapy unit, and a 0.6CC PTW TM30013 Farmer chamber with PTW T0008 Eletrometer was used for the Elekta-Precise linear accelerator. For the beam quality measurements, the dedicated TomoTherapy electrometer measurement system (TEMS) along with a two-dimensional radiation beam analyzer (TomoScanner) and a PTW-Freiburg MP3-S therapy beam analyzer water phantom system were performed the scanning for the beam symmetrical profiles assessment for the corresponding machine respectively. Results: The lengths of time required for daily QA program was almost the same for the two machines. However, the monthly and annual programs were more efficient for the Hi-Art Helical TomoTherapy, saving 2 hours and 10 hours compared to the Elekta-Precise linear accelerator, respectively. The statistical data collected over the past 10 months show that the time spent for the TomoTherapy was less, and the tolerance value was lower than that of the Elekta-Precise linear accelerator; the output error of daily QA was within ±1% for 75% of the data, within ±2% for 18.75% of the data, and within +3% for the remaining 6.25% of the data, and the dose output error value for the monthly QA was less than ±1%. Conclusions： The following conclusions can be drawn from this study. First, the time needed for the QA schedule for the Hi-Art Helical TomoTherapy is less than that required for routine work with a linear accelerator. Due to the TomoTherapy machine intrinsic characteristics, some mechanical items, such as the gantry, the couch angle, the collimator etc., do not need to be checked. Additionally, no electron beam verification is needed but the same beam effect can be formed from the different beamlets of the machine. Nonetheless, Helical TomoTherapy has a relatively short clinical track record and, as further operational experience is gained, it may be found that some QA items will need to be modified and some additional tests may need to be developed for completeness of the QA schedule.

Experience with Quality Assurance Programming for Helical TomoTherapy

In this paper, we present a quality assurance (QA) programming for the Helical TomoTherapy and share the QA practical experiences with this state-of-the-art machine in radiation therapy. According to the Ionizing Radiation Protection Act (Article. 17, item 3), the regulations of medical exposure quality assurance in Taiwan, has to include the items of daily, monthly, and annual schedule for every treatment machine in a department of radiation oncology. We presented the QA programming that is performed in our department, which follows the principle of AAPM TG-40 but contains some novel components, reflecting the differences between the Hi-Art devices and conventional linear accelerators.