scholarly journals A novel specific grading standard study of auto-segmentation of organs at risk in thorax: subjective–objective-combined grading standard

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Yanchen Ying ◽  
Hao Wang ◽  
Hua Chen ◽  
Jianfan Cheng ◽  
Hengle Gu ◽  
...  
Keyword(s):  
At Risk ◽  
Hausdorff Distance ◽  
Evaluation Method ◽  
Organs At Risk ◽  
Subjective Evaluation ◽  
The Other ◽  
Dice Similarity Coefficient ◽  
Evaluation Standard ◽  
Segmentation Accuracy ◽  
The Difference

Abstract Background To develop a novel subjective–objective-combined (SOC) grading standard for auto-segmentation for each organ at risk (OAR) in the thorax. Methods A radiation oncologist manually delineated 13 thoracic OARs from computed tomography (CT) images of 40 patients. OAR auto-segmentation accuracy was graded by five geometric objective indexes, including the Dice similarity coefficient (DSC), the difference of the Euclidean distance between centers of mass (ΔCMD), the difference of volume (ΔV), maximum Hausdorff distance (MHD), and average Hausdorff distance (AHD). The grading results were compared with those of the corresponding geometric indexes obtained by geometric objective methods in the other two centers. OAR auto-segmentation accuracy was also graded by our subjective evaluation standard. These grading results were compared with those of DSC. Based on the subjective evaluation standard and the five geometric indexes, the correspondence between the subjective evaluation level and the geometric index range was established for each OAR. Results For ΔCMD, ΔV, and MHD, the grading results of the geometric objective evaluation methods at our center and the other two centers were inconsistent. For DSC and AHD, the grading results of three centers were consistent. Seven OARs’ grading results in the subjective evaluation standard were inconsistent with those of DSC. Six OARs’ grading results in the subjective evaluation standard were consistent with those of DSC. Finally, we proposed a new evaluation method that combined the subjective evaluation level of those OARs with the range of corresponding DSC to determine the grading standard. If the DSC ranges between the adjacent levels did not overlap, the DSC range was used as the grading standard. Otherwise, the mean value of DSC was used as the grading standard. Conclusions A novel OAR-specific SOC grading standard in thorax was developed. The SOC grading standard provides a possible alternative for evaluation of the auto-segmentation accuracy for thoracic OARs.

scholarly journals Automatic Planning for Nasopharyngeal Carcinoma Based on Progressive Optimization in RayStation Treatment Planning System

2020 ◽  
Vol 19 ◽  
pp. 153303382091571
Author(s):  
Yiwei Yang ◽  
Kainan Shao ◽  
Jie Zhang ◽  
Ming Chen ◽  
Yuanyuan Chen ◽  
...  
Keyword(s):  
At Risk ◽  
Nasopharyngeal Carcinoma ◽  
Organs At Risk ◽  
Planning System ◽  
Treatment Planning System ◽  
Conformity Index ◽  
Homogeneity Index ◽  
Automatic Planning ◽  
The Difference ◽  
Better Than

Objective: To evaluate and quantify the planning performance of automatic planning (AP) with manual planning (MP) for nasopharyngeal carcinoma in the RayStation treatment planning system (TPS). Methods: A progressive and effective design method for AP of nasopharyngeal carcinoma was realized through automated scripts in this study. A total of 30 patients with nasopharyngeal carcinoma with initial treatment was enrolled. The target coverage, conformity index (CI), homogeneity index (HI), organs at risk sparing, and the efficiency of design and execution were compared between automatic and manual volumetric modulated arc therapy (VMAT) plans. Results: The results of the 2 design methods met the clinical dose requirement. The differences in D95 between the 2 groups in PTV1 and PTV2 showed statistical significance, and the MPs are higher than APs, but the difference in absolute dose was only 0.21% and 0.16%. The results showed that the conformity index of planning target volumes (PTV1, PTV2, PTVnd and PGTVnx+rpn [PGTVnx and PGTVrpn]), homogeneity index of PGTVnx+rpn, and HI of PTVnd in APs are better than that in MPs. For organs at risk, the APs are lower than the MPs, and the difference was statistically significant ( P < .05). The manual operation time in APs was 83.21% less than that in MPs, and the computer processing time was 34.22% more. Conclusion: IronPython language designed by RayStation TPS has clinical application value in the design of automatic radiotherapy plan for nasopharyngeal carcinoma. The dose distribution of tumor target and organs at risk in the APs was similar or better than those in the MPs. The time of manual operation in the plan design showed a sharp reduction, thus significantly improving the work efficiency in clinical application.

Children and the Experience of Violence: Contrasting Cultures of Punishment in Northern Nigeria

Africa ◽  
2000 ◽  
Vol 70 (3) ◽  
pp. 359-393 ◽  
Author(s):  
Murray Last
Keyword(s):  
At Risk ◽  
Corporal Punishment ◽  
Self Control ◽  
The Other ◽  
Northern Nigeria ◽  
Children At Risk ◽  
Muslim Society ◽  
Large Society ◽  
Rights Of The Child ◽  
The Difference

AbstractArising out of debates over ‘children at risk’ and the ‘rights of the child’, the article compares two contrasting childhoods within a single large society—the Hausa‐speaking peoples of northern Nigeria. One segment of this society—the non‐Muslim Maguzawa—refuse to allow their children to be beaten; the other segment, the Muslim Hausa, tolerate corporal punishment both at home and especially in Qur'anic schools. Why the difference? Economic as well as political reasons are offered as reasons for the rejection of corporal punishment while it is argued that, in the eyes of Muslim society in the cities, the threat of punishment is essential for both educating and ‘civilising’ the young by imposing the necessary degree of discipline and self‐control that are considered the hallmark of a good Muslim. In short, ‘cultures of punishment’ arise out of specific historical conditions, with wide variations in the degree and frequency with which children actually suffer punishment, and at whose hands. Finally the question is raised whether the violence experienced in schooling has sanctioned in the community at large a greater tolerance of violence‐as‐‘punishment’.

scholarly journals Analysis Of Dose At 3D-Crt And Imrt Techniques In Left Breast Cancer Case With Hypofractionation Using Deep Inspiration Breath-Hold (Dibh)

2021 ◽  
Author(s):  
Samsun - ◽  
Muhammad Arif Arif ◽  
Gregorius Septayudha Septayudha
Keyword(s):  
Breast Cancer ◽  
At Risk ◽  
Organs At Risk ◽  
Left Breast ◽  
Breath Hold ◽  
Tolerance Limits ◽  
Deep Inspiration Breath Hold ◽  
Organ At Risk ◽  
The Difference ◽  
3D Crt

Abstract In terms of breast cancer radiation treatment, it has radiation using the 3D-Conformal Radiotherapy (3D-CRT) technique and the continuation of the 3D-CRT technique, namely the Intensity Modulated Radiation Therapy (IMRT) technique. This study aims to evaluate the dosage aspects of PTV and OAR between the 3D-CRT and IMRT techniques in cases of left breast cancer with hypofractionation using the Deep Inspiration Breath Hold (DIBH) method using the Conformity Index (CI) and Homogeneity Index (H.I.) and H.I. organ at risk uses tolerance limits. This type of research is comparative quantitative with ten samples with primary data conducted at Siloam T.B. Hospital. Simatupang from November 2019 to April 2020. The research was carried out in the form of radiation planning with 3D-CRT techniques and IMRT techniques, and the results of planning both techniques were evaluated between 3D-CRT techniques and IMRT techniques through PTV evaluations using CI and H.I. values. Furthermore, the organs at risk use tolerance limits on each organ. The results showed the assessment between 3D-CRT and IMRT on PTV and organs at risk received different doses. The PTV shows the CI value, which is almost the same as the difference of 0.034, and there is a slight difference in H.I. with an average value in the IMRT technique of 0.07 and 3D-CRT of 0.11, and it can be seen that the IMRT is slightly superior because the excellent H.I. value is the closest to 0. Then at the dose of organ at risk received by the sample, the 3D-CRT technique is slightly superior by obtaining a lower dose that obtains the difference in the heart by 0.53%, lung by 3.46%, spinal cord by 6.51 Gy, esophagus at 4.5 Gy, and larynx at 5.18 Gy.

scholarly journals Clinical Validation and Treatment Plan Evaluation Based on Auto-Delineation of the Clinical Target Volume for Prostate Cancer Radiotherapy

2022 ◽  
Author(s):  
Jing Shen ◽  
Yinjie TAO ◽  
Hui GUAN ◽  
Hongnan ZHEN ◽  
Lei HE ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
At Risk ◽  
Organs At Risk ◽  
Treatment Plan ◽  
Statistical Significance ◽  
Locally Advanced ◽  
Target Volume ◽  
Ct Scans ◽  
Dice Similarity Coefficient ◽  
Treatment Plans

Abstract Purpose Clinical target volumes (CTV) and organs at risk (OAR) could be auto-contoured to save workload. The goal of this study was to assess a convolutional neural network (CNN) for totally automatic and accurate CTV and OAR in prostate cancer, while also comparing anticipated treatment plans based on auto-contouring CTV to clinical plans. Methods From January 2013 to January 2019, 217 computed tomography (CT) scans of patients with locally advanced prostate cancer treated at our hospital were collected and analyzed. CTV and OAR were delineated with a deep learning based method, which named CUNet. The performance of this strategy was evaluated using the mean Dice similarity coefficient (DSC), 95th percentile Hausdorff distance (95HD), and subjective evaluation. Treatment plans were graded using predetermined evaluation criteria, and % errors for clinical doses to the planned target volume (PTV) and organs at risk(OARs) were calculated. Results The defined CTVs had mean DSC and 95HD values of 0.84 and 5.04 mm, respectively. For one patient's CT scans, the average delineation time was less than 15 seconds. When CTV outlines from CUNetwere blindly chosen and compared to GT, the overall positive rate in clinicians A and B was 53.15% vs 46.85%, and 54.05% vs 45.95%, respectively (P>0.05), demonstrating that our deep machine learning model performed as good as or better than human demarcation Furthermore, 8 testing patients were chosen at random to design the predicted plan based on the auto-courtoring CTV and OAR, demonstrating acceptable agreement with the clinical plan: average absolute dose differences of D2, D50, D98, Dmean for PTV are within 0.74%, and average absolute volume differences of V45, V50 for OARs are within 3.4%. Without statistical significance (p>0.05), the projected findings are comparable to clinical truth. Conclusion The experimental results show that the CTV and OARs defined by CUNet for prostate cancer were quite close to the ground reality.CUNet has the potential to cut radiation oncologists' contouring time in half. When compared to clinical plans, the differences between estimated doses to CTV and OAR based on auto-courtoring were small, with no statistical significance, indicating that treatment planning for prostate cancer based on auto-courtoring has potential.

scholarly journals The Dosimetric Impact of Deep Learning-Based Auto-Segmentation of Organs at Risk on Nasopharyngeal and Rectal Cancer

2021 ◽  
Author(s):  
Hongbo Guo ◽  
Jiazhou Wang ◽  
Xiang Xia ◽  
Yang Zhong ◽  
Jiayuan Peng ◽  
...  
Keyword(s):  
At Risk ◽  
Rectal Cancer ◽  
Deep Learning ◽  
Organs At Risk ◽  
Dice Similarity Coefficient ◽  
Pass Rates ◽  
Temporal Lobes ◽  
Dose Volume ◽  
Treatment Plans ◽  
Dosimetric Analysis

Abstract PurposeTo investigate the dosimetric impact of deep learning-based auto-segmentation of organs at risk (OARs) on nasopharyngeal and rectal cancer.Methods and MaterialsTwenty patients, including ten nasopharyngeal carcinoma (NPC) patients and ten rectal cancer patients, who received radiotherapy in our department were enrolled in this study. Two deep learning-based auto-segmentation systems, including an in-house developed system (FD) and a commercial product (UIH), were used to generate two auto-segmented OARs sets (OAR_FD and OAR_UIH). Treatment plans based on auto-segmented OARs and following our clinical requirements were generated for each patient on each OARs set (Plan_FD and Plan_UIH). Geometric metrics (Hausdorff distance (HD), mean distance to agreement (MDA), the Dice similarity coefficient (DICE) and the Jaccard index) were calculated for geometric evaluation. The dosimetric impact was evaluated by comparing Plan_FD and Plan_UIH to original clinically approved plans (Plan_Manual) with dose-volume indices and 3D gamma pass rates. Spearman’s correlation analysis was performed to investigate the correlation between dosimetric deviation and geometric metrics.ResultsFD and UIH could provide similar geometric performance in parotids, temporal lobes, lens, and eyes (DICE, p > 0.05). OAR_FD had better geometric performance in the optic nerves, oral cavity, larynx, and femoral heads (DICE, p < 0.05). OAR_UIH had better geometric performance in the bladder (DICE, p < 0.05). In dosimetric analysis, both Plan_FD and Plan_UIH had nonsignificant dosimetric differences compared to Plan_Manual for most PTV and OARs dose-volume indices. The only significant dosimetric difference was the Dmax of the left temporal lobe for Plan_FD vs. Plan_Manual (p = 0.05). Only one significant correlation was found between the mean dose of the femoral head and its HD index (R = 0.4, p = 0.01).ConclusionsDeep learning-based OARs auto-segmentation for NPC and rectal cancer has a nonsignificant impact on most PTV and OARs dose-volume indices. Correlations between the auto-segmentation geometric metric and dosimetric difference were not observed for most OARs.

scholarly journals Clinical Enhancement in AI-Based Post-processed Fast-Scan Low-Dose CBCT for Head and Neck Adaptive Radiotherapy

2021 ◽  
Vol 3 ◽  
Author(s):  
Wen Chen ◽  
Yimin Li ◽  
Nimu Yuan ◽  
Jinyi Qi ◽  
Brandon A. Dyer ◽  
...  
Keyword(s):  
At Risk ◽  
Head And Neck Cancer ◽  
Head And Neck ◽  
Neck Cancer ◽  
Low Dose ◽  
Organs At Risk ◽  
Similarity Index ◽  
Adaptive Radiotherapy ◽  
Qualitative Assessment ◽  
Dice Similarity Coefficient

Purpose: To assess image quality and uncertainty in organ-at-risk segmentation on cone beam computed tomography (CBCT) enhanced by deep-learning convolutional neural network (DCNN) for head and neck cancer.Methods: An in-house DCNN was trained using forty post-operative head and neck cancer patients with their planning CT and first-fraction CBCT images. Additional fifteen patients with repeat simulation CT (rCT) and CBCT scan taken on the same day (oCBCT) were used for validation and clinical utility assessment. Enhanced CBCT (eCBCT) images were generated from the oCBCT using the in-house DCNN. Quantitative imaging quality improvement was evaluated using HU accuracy, signal-to-noise-ratio (SNR), and structural similarity index measure (SSIM). Organs-at-risk (OARs) were delineated on o/eCBCT and compared with manual structures on the same day rCT. Contour accuracy was assessed using dice similarity coefficient (DSC), Hausdorff distance (HD), and center of mass (COM) displacement. Qualitative assessment of users’ confidence in manual segmenting OARs was performed on both eCBCT and oCBCT by visual scoring.Results: eCBCT organs-at-risk had significant improvement on mean pixel values, SNR (p &lt; 0.05), and SSIM (p &lt; 0.05) compared to oCBCT images. Mean DSC of eCBCT-to-rCT (0.83 ± 0.06) was higher than oCBCT-to-rCT (0.70 ± 0.13). Improvement was observed for mean HD of eCBCT-to-rCT (0.42 ± 0.13 cm) vs. oCBCT-to-rCT (0.72 ± 0.25 cm). Mean COM was less for eCBCT-to-rCT (0.28 ± 0.19 cm) comparing to oCBCT-to-rCT (0.44 ± 0.22 cm). Visual scores showed OAR segmentation was more accessible on eCBCT than oCBCT images.Conclusion: DCNN improved fast-scan low-dose CBCT in terms of the HU accuracy, image contrast, and OAR delineation accuracy, presenting potential of eCBCT for adaptive radiotherapy.

scholarly journals Clinical implementation of PLANET®Dose for dosimetric assessment after [177Lu]Lu-DOTA-TATE : comparison with Dosimetry Toolkit® and OLINDA/EXM® V1.0

2020 ◽  
Author(s):  
Lore Santoro ◽  
Laurine Pitalot ◽  
Dorian Trauchessec ◽  
Erick Mora-Ramirez ◽  
Pierre-Olivier Kotzki ◽  
...  
Keyword(s):  
At Risk ◽  
Organs At Risk ◽  
Absorbed Dose ◽  
Peptide Receptor Radionuclide Therapy ◽  
Slight Variation ◽  
Clinical Implementation ◽  
Absorbed Doses ◽  
Plot Analysis ◽  
The Difference ◽  
Over Time

Abstract Background: The aim of this study was to compare a commercial dosimetry workstation (PLANET®Dose) and the dosimetry approach (GE Dosimetry Toolkit® and OLINDA/EXM® V1.0) currently used in our department for quantification of the absorbed dose in organs at risk after peptide receptor radionuclide therapy with [177Lu]Lu-DOTA-TATE. Methods: An evaluation on phantom was performed to determine the SPECT calibration factor variations over time and to compare the Time Integrated Activity Coefficients (TIACs) and absorbed doses obtained with the two tools. Then, the two tools were used for dosimetry evaluation in 21 patients with neuroendocrine tumours after the first and second injection of 7.2 ± 0.2 GBq of [177Lu]Lu-DOTA-TATE (40 dosimetry analyses with each software). SPECT/CT images were acquired at 4h, 24h, 72h and 192h after [177Lu]Lu-DOTA-TATE injection and were reconstructed using the Xeleris software (General Electric). The liver, spleen and kidney masses, TIACs and absorbed doses were calculated using i) GE Dosimetry Toolkit® (DTK) and OLINDA/EXM® V1.0 and ii) the Local Deposition Method (LDM) or Dose voxel-Kernel convolution (DK) on PLANET®Dose. Results: With the phantom, the 3D calibration factors showed a slight variation (0.8% and 3.3%) over time and TIACs of 225.19h and 217.52h were obtained with DTK and PLANET®Dose, respectively. In patients, the root mean square deviation value was 8.9% for the organ masses, 8.1% for the TIACs, and 9.1 and 7.8% for the absorbed doses with LDM and DK, respectively. The Lin’s concordance correlation coefficient was 0.99 and the Bland-Altman plot analysis estimated that the difference of absorbed dose values between methods ranged from -0.75 Gy to 0.49 Gy, from -0.20 Gy to 0.64 Gy and from -0.43 to 1.03 Gy for approximately 95% of the 40 liver, kidneys and spleen dosimetry analyses. A difference of 2.2% was obtained between the absorbed doses to organs at risk calculated with LDM and DK. Conclusions: The absorbed doses to organs at risk obtained with the new workstation are concordant with those calculated with the currently used software and in agreement with the literature. These results validate the use of PLANET®Dose in clinical routine for patient dosimetry after targeted radiotherapy with [177Lu]Lu-DOTA-TATE.

scholarly journals A slice classification model-facilitated 3D encoder–decoder network for segmenting organs at risk in head and neck cancer

2020 ◽  
Vol 62 (1) ◽  
pp. 94-103
Author(s):  
Shuming Zhang ◽  
Hao Wang ◽  
Suqing Tian ◽  
Xuyang Zhang ◽  
Jiaqi Li ◽  
...  
Keyword(s):  
At Risk ◽  
Optic Nerve ◽  
Head And Neck ◽  
Temporomandibular Joint ◽  
Temporal Lobe ◽  
Organs At Risk ◽  
Ct Images ◽  
Classification Model ◽  
Superior Performance ◽  
Dice Similarity Coefficient

Abstract For deep learning networks used to segment organs at risk (OARs) in head and neck (H&N) cancers, the class-imbalance problem between small volume OARs and whole computed tomography (CT) images results in delineation with serious false-positives on irrelevant slices and unnecessary time-consuming calculations. To alleviate this problem, a slice classification model-facilitated 3D encoder–decoder network was developed and validated. In the developed two-step segmentation model, a slice classification model was firstly utilized to classify CT slices into six categories in the craniocaudal direction. Then the target categories for different OARs were pushed to the different 3D encoder–decoder segmentation networks, respectively. All the patients were divided into training (n = 120), validation (n = 30) and testing (n = 20) datasets. The average accuracy of the slice classification model was 95.99%. The Dice similarity coefficient and 95% Hausdorff distance, respectively, for each OAR were as follows: right eye (0.88 ± 0.03 and 1.57 ± 0.92 mm), left eye (0.89 ± 0.03 and 1.35 ± 0.43 mm), right optic nerve (0.72 ± 0.09 and 1.79 ± 1.01 mm), left optic nerve (0.73 ± 0.09 and 1.60 ± 0.71 mm), brainstem (0.87 ± 0.04 and 2.28 ± 0.99 mm), right temporal lobe (0.81 ± 0.12 and 3.28 ± 2.27 mm), left temporal lobe (0.82 ± 0.09 and 3.73 ± 2.08 mm), right temporomandibular joint (0.70 ± 0.13 and 1.79 ± 0.79 mm), left temporomandibular joint (0.70 ± 0.16 and 1.98 ± 1.48 mm), mandible (0.89 ± 0.02 and 1.66 ± 0.51 mm), right parotid (0.77 ± 0.07 and 7.30 ± 4.19 mm) and left parotid (0.71 ± 0.12 and 8.41 ± 4.84 mm). The total segmentation time was 40.13 s. The 3D encoder–decoder network facilitated by the slice classification model demonstrated superior performance in accuracy and efficiency in segmenting OARs in H&N CT images. This may significantly reduce the workload for radiation oncologists.

scholarly journals Comparison Of Risk Organ Distribution With Target Volume Size Variations Using Rapid ARC And IMRT Techniques For Case Of Lung Cancer

2018 ◽  
Vol 9 (1) ◽  
pp. 64-71
Author(s):  
Eny Supriyaningsih ◽  
Guntur Winarno ◽  
Trisno Firmansyah
Keyword(s):  
At Risk ◽  
Maximum Dose ◽  
Organs At Risk ◽  
Target Volume ◽  
Organ Distribution ◽  
Know How ◽  
Result Show ◽  
The Difference ◽  
Higher Doses ◽  
Volume Size

This study aims to know how big the difference between dose distribution Rapid Arc and IMRT technique and gains on PTV dose 95%. This research is a descriptive qualitative research data obtained from Phantom to take three the size of the volume of the tumor is seen from the organs at risk of Medulla spinalis, heart, healthy and the lung from the results of the data processing and then analyzed the distribution of the received dose organs at risk. Data analysis is done using the Software eclipse. The result show received dose between flashes IMRT technique and Rapid arc technique on the size of the volume of cancer 250 cm3, 500 cm3, 750 cm3 on the part of the heart and the lungs, Rapid arc provides better radiation dose compared with IMRT but only the medulla spinalis get higher doses but still below the maximum dose organ and gains received on PTV dose 95% with the technique of Rapid Arc higher than IMRT technique.

scholarly journals Tumor Control Probability (TCP) and Normal Tissue Complication Probability (NTCP) in Mono and Dual-isocentric Techniques of Breast Cancer Radiation Therapy

2021 ◽  
pp. 192-202
Author(s):  
Kaveh Shirani Tak Abi ◽  
Sediqeh Habibian ◽  
Marzieh Salimi ◽  
Ahmad Shakeri ◽  
Mohammad Mehdi Mojahed ◽  
...  
Keyword(s):  
Breast Cancer ◽  
At Risk ◽  
Radiation Therapy ◽  
Normal Tissue ◽  
Maximum Dose ◽  
Organs At Risk ◽  
Normal Tissue Complication Probability ◽  
The Other ◽  
Tumor Control ◽  
Tumor Control Probability

Background: Nowadays, radiation therapy plays an important role in the treatment of breast cancer. The important point is the optimal control of the tumor along with the protection of organs at risk. This study aims to investigate and compare the radiobiological factors of the tumor and organs at risk in two different radiation therapy techniques of breast cancer.Methods: Ten left-sided breast cancer patients with breast-conservative surgery were selected for this study. Three-dimensional treatment planning was performed using CT scan images of the patients using PCRT 3D software. Two different tangential external beam techniques were compared: first, dual-isocentric technique (DIT) with two isocentre, one on the breast tissue, and the other one on the supraclavicular lymph nodes and second, a mono-isocentric technique (MIT) with one isocentre at the intersection of the tangential and the supraclavicular field. The total prescribed dose was 5000 cGy per 25 fractions. Dose-volume histograms (DVHs), Tumor control probability (TCP), and normal tissue complication probability (NTCP) curves were used to compare the dosimetric and radiobiological parameters of the tissues in the prementioned techniques. Results: The results showed that the maximum doses in planning target volume (PTV) with mean values of 109% and 110% in the SI and DIT were not significantly different in both techniques and that they were indeed at the optimum level based on the RTOG 1005 protocol. The dose homogeneity index in MMIT was more than that in DIT, while the conformity index and the mean TCP did not show a significant difference in the two techniques. Furthermore, minimum, mean, and maximum dose in the lung and the probability of pneumonitis decreased in MIT. On the other hand, the maximum dose, the dose of 33%, 66%, and 100% of the heart, and the probability of pericarditis in MIT were lower than the figure in DIT. Conclusion: Due to the absence of hot spots at the intersection of tangential and supraclavicular fields and the reduction of mechanical movements of the coach and collimator in MIT, the superiority of this method was confirmed.

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