METHODS AND MATERIALS: This retrospective study used data from 5 consecutive patients with NPC who were treated with bolus for large neck nodes using IMRT from November 2011-January 2012 in our institute. All these patients were treated radically with IMRT according to our institution's protocol. Re-planning with IMRT without bolus for these patients with exactly the same target volumes were done for comparison. Comparison of the plans was done by comparing the V70 of PTV70-N, V66.5 of PTV70-N, V65.1 of PTV70-N and the surface dose of the PTV70-N.
RESULTS: The mean size of the largest diameter of the enlarged lymph nodes for the 5 patients was 3.9 cm. The mean distance of the GTV-N to the skin surface was 0.6 cm. The mean V70 of PTV70-N for the 5 patients showed an absolute advantage of 10.8% (92.4% vs. 81.6%) for the plan with bolus while the V66.5 of PTV70-N had an advantage of 8.1% (97.0% vs. 88.9%). The mean V65.1 also had an advantage of 7.1% (97.6% vs. 90.5%). The mean surface dose for the PTV70-N was also much higher at 61.1 Gy for the plans with bolus compared to only 23.5 Gy for the plans without bolus.
CONCLUSION: Neck node bolus technique should be strongly considered in the treatment of NPC with enlarged lymph nodes treated with IMRT. It yields a superior dosimetry compared to non-bolus plans with acceptable skin toxicity.
MATERIALS/METHODS: A total of 10 patients with synchronous bilateral breast cancer who were treated with VMAT at our institution were retrospectively analyzed. Clinical target volume (CTV) included chest wall and regional nodes (supraclavicular fossa and internal mammary chain) and prescription dose was 40.05 Gy in 15 daily fractions. HT and IMPT plans were generated for each patient. Dose-volume statistics, including planning target volume (PTV) coverage and dose to OAR: lungs, heart, thyroid, spinal cord, brachial plexus and esophagus, were compared between modalities using a paired T-test.
RESULTS: Mean age of patients was 61 years (43-84). Majority of the patients (80%) were ER+ PR+ and HER2-. 40% of patients underwent breast reconstruction following surgery. All 3 techniques provided adequate target volume distribution and OAR sparing. Compared to VMAT and HT plans, IMPT had better heart and lung sparing effects, resulting in lower mean and V25 Gy heart dose; mean, V20 Gy and V5 Gy lung dose (p<0.0001). There was no significant difference in VMAT and HT plans for mean heart and lung dose. VMAT plans showed significantly lower V25 Gy heart dose on average (p = 0.04). V5 Gy lung dose was slightly lower in HT compared to VMAT plans, approaching statistical significance (p = 0.08). PTV coverage was adequate for all 3 techniques. All techniques fulfilled cord, esophagus, thyroid and brachial plexus constraints.
CONCLUSION: IMPT plans showed significantly better OAR sparing compared to photon techniques. All 3 techniques met OAR constraints, and resulted in adequate target volume coverage. As IMPT is significantly more costly than VMAT or HT techniques, appropriate patient selection is important to deliver treatment in the most resource-effective manner for patients who would derive the most benefit, for example those with young age or existing heart or lung comorbidities.
METHODS: ARCHERY is a non-randomised prospective study to evaluate the quality and economic impact of AI-based automated radiotherapy treatment planning for cervical, head and neck, and prostate cancers, which are endemic in LMICs, and for which radiotherapy is the primary curative treatment modality. The sample size of 990 patients (330 for each cancer type) has been calculated based on an estimated 95% treatment plan acceptability rate. Time and cost savings will be analysed as secondary outcome measures using the time-driven activity-based costing model. The 48-month study will take place in six public sector cancer hospitals in India (n=2), Jordan (n=1), Malaysia (n=1) and South Africa (n=2) to support implementation of the software in LMICs.
ETHICS AND DISSEMINATION: The study has received ethical approval from University College London (UCL) and each of the six study sites. If the study objectives are met, the AI-based software will be offered as a not-for-profit web service to public sector state hospitals in LMICs to support expansion of high quality radiotherapy capacity, improving access to and affordability of this key modality of cancer cure and control. Public and policy engagement plans will involve patients as key partners.
METHOD: The model was formulated by integrating the Caputo fractional derivative with the previous cancer treatment model. Thereafter, the linear-quadratic with the repopulation model was coupled into the model to account for the cells' population decay due to radiation. The treatment process was then simulated with numerical variables, numerical parameters, and radiation parameters. The numerical parameters which included the proliferation coefficients of the cells, competition coefficients of the cells, and the perturbation constant of the normal cells were obtained from previous literature. The radiation and numerical parameters were obtained from reported clinical data of six patients treated with radiotherapy. The patients had tumor volumes of 24.1cm3, 17.4cm3, 28.4cm3, 18.8cm3, 30.6cm3, and 12.6cm3 with fractionated doses of 2 Gy for the first two patients and 1.8 Gy for the other four. The initial tumor volumes were used to obtain initial populations of cells after which the treatment process was simulated in MATLAB. Subsequently, a global sensitivity analysis was done to corroborate the model with clinical data. Finally, 96 radiation protocols were simulated by using the biologically effective dose formula. These protocols were used to obtain a regression equation connecting the value of the Caputo fractional derivative with the fractionated dose.
RESULTS: The final tumor volumes, from the results of the simulations, were 3.58cm3, 8.61cm3, 5.68cm3, 4.36cm3, 5.75cm3, and 6.12cm3, while those of the normal cells were 23.87cm3, 17.29cm3, 28.17cm3, 18.68cm3, 30.33cm3, and 12.55cm3. The sensitivity analysis showed that the most sensitive model factors were the value of the Caputo fractional derivative and the proliferation coefficient of the cancer cells. Lastly, the obtained regression equation accounted for 99.14% of the prediction.
CONCLUSION: The model can simulate a cancer treatment process and predict the results of other radiation protocols.
MATERIALS AND METHODS: Ninety-seven ROs were randomly assigned to either manual or AI-assisted contouring of eight OARs for two head-and-neck cancer cases with an in-between teaching session on contouring guidelines. Thereby, the effect of teaching (yes/no) and AI-assisted contouring (yes/no) was quantified. Second, ROs completed short-term and long-term follow-up cases all using AI assistance. Contour quality was quantified with Dice Similarity Coefficient (DSC) between ROs' contours and expert consensus contours. Groups were compared using absolute differences in medians with 95% CIs.
RESULTS: AI-assisted contouring without previous teaching increased absolute DSC for optic nerve (by 0.05 [0.01; 0.10]), oral cavity (0.10 [0.06; 0.13]), parotid (0.07 [0.05; 0.12]), spinal cord (0.04 [0.01; 0.06]), and mandible (0.02 [0.01; 0.03]). Contouring time decreased for brain stem (-1.41 [-2.44; -0.25]), mandible (-6.60 [-8.09; -3.35]), optic nerve (-0.19 [-0.47; -0.02]), parotid (-1.80 [-2.66; -0.32]), and thyroid (-1.03 [-2.18; -0.05]). Without AI-assisted contouring, teaching increased DSC for oral cavity (0.05 [0.01; 0.09]) and thyroid (0.04 [0.02; 0.07]), and contouring time increased for mandible (2.36 [-0.51; 5.14]), oral cavity (1.42 [-0.08; 4.14]), and thyroid (1.60 [-0.04; 2.22]).
CONCLUSION: The study suggested that AI-assisted contouring is safe and beneficial to ROs working in LMICs. Prospective clinical trials on AI-assisted contouring should, however, be conducted upon clinical implementation to confirm the effects.
METHODS: A survey on medical physics aspects of IMRT is conducted on radiotherapy departments across Malaysia to assess the usage, experience and QA in IMRT, which is done for the first time in this country. A set of questionnaires was designed and sent to the physicist in charge for their responses. The questionnaire consisted of four sections; (i) Experience and qualification of medical physicists, (ii) CT simulation techniques (iii) Treatment planning and treatment unit, (iv) IMRT process, delivery and QA procedure.
RESULTS: A total of 26 responses were collected, representing 26 departments out of 33 radiotherapy departments in operation across Malaysia (79% response rate). Results showed that the medical physics aspects of IMRT practice in Malaysia are homogenous, with some variations in certain areas of practices. Thirteen centres (52%) performed measurement-based QA using 2D array detector and analysed using gamma index criteria of 3%, 3 mm with variation confidence range. In relation to the IMRT delivery, 44% of Malaysia's physicist takes more than 8 h to plan a head and neck case compared to the UK study possibly due to the lack of professional training.
CONCLUSIONS: This survey provides a picture of medical physics aspects of IMRT in Malaysia where the results/data can be used by radiotherapy departments to benchmark their local policies and practice.