Publications by authors named "Aihui Feng"

15 Publications

  • Page 1 of 1

Isotoxic investigation of F-FDG PET/CT-guided dose escalation with intensity-modulated radiotherapy for LA-NSCLC.

Int J Radiat Biol 2021 Oct 1:1-24. Epub 2021 Oct 1.

Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.

Purpose: This research compared differences of dosimetric and biological parameters between PET/CT-guided isotoxic SIB-IMRT plans and conventional radiotherapy plans for patients with LA-NSCLC, and it also evaluated the factors that affect dose escalation.

Materials And Methods: This study consisted of a retrospective cohort of thirty patients with IIIA-IIIB NSCLC. SIB-IMRT (Plan_iso) and conventional radiotherapy (Plan_primary) plans were generated using auto-planning. Dosimetric parameters such as mean lung dose (MLD) and other indicators were compared. Tumor control probability (TCP) of PTV and normal tissue complication probability (NTCP) of total lung, heart, esophagus and spinal cord were calculated. The relationships between dose escalation and 3D length of PTV and other factors were analyzed. Paired-samples t-test, Mann-Whitney U test, and Chi-Square test were performed for comparisons between datasets. A P < 0.05 was considered statistically significant.

Results: The dosimetric parameters of PTV in Plan_iso were higher than those of PTV in Plan_primary, and there were significant differences (p < 0.05). Compared with Plan_primary, Plan_iso slightly increased dosimetric parameters of total lung, heart, spinal cord, esophagus and MUs. The absolute differences were small. TCPs of PTV in Plan_iso were significantly higher than those in Plan_primary. NTCPs of total lung, esophagus and spinal cord in Plan_iso were higher than those in Plan_primary. There were significant differences, but the absolute differences were small. NTCP of heart in Plan_iso was slightly higher than that in Plan_primary, but there was no statistical difference.

Conclusions: For LA-NSCLC, the SIB based on isotoxic radiotherapy can significantly increase TCP under the premise that the toxicity of OARs is comparable.
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http://dx.doi.org/10.1080/09553002.2021.1987557DOI Listing
October 2021

A 2D-3D hybrid convolutional neural network for lung lobe auto-segmentation on standard slice thickness computed tomography of patients receiving radiotherapy.

Biomed Eng Online 2021 Sep 23;20(1):94. Epub 2021 Sep 23.

Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.

Background: Accurate segmentation of lung lobe on routine computed tomography (CT) images of locally advanced stage lung cancer patients undergoing radiotherapy can help radiation oncologists to implement lobar-level treatment planning, dose assessment and efficacy prediction. We aim to establish a novel 2D-3D hybrid convolutional neural network (CNN) to provide reliable lung lobe auto-segmentation results in the clinical setting.

Methods: We retrospectively collected and evaluated thorax CT scans of 105 locally advanced non-small-cell lung cancer (NSCLC) patients treated at our institution from June 2019 to August 2020. The CT images were acquired with 5 mm slice thickness. Two CNNs were used for lung lobe segmentation, a 3D CNN for extracting 3D contextual information and a 2D CNN for extracting texture information. Contouring quality was evaluated using six quantitative metrics and visual evaluation was performed to assess the clinical acceptability.

Results: For the 35 cases in the test group, Dice Similarity Coefficient (DSC) of all lung lobes contours exceeded 0.75, which met the pass criteria of the segmentation result. Our model achieved high performances with DSC as high as 0.9579, 0.9479, 0.9507, 0.9484, and 0.9003 for left upper lobe (LUL), left lower lobe (LLL), right upper lobe (RUL), right lower lobe (RLL), and right middle lobe (RML), respectively. The proposed model resulted in accuracy, sensitivity, and specificity of 99.57, 98.23, 99.65 for LUL; 99.6, 96.14, 99.76 for LLL; 99.67, 96.13, 99.81 for RUL; 99.72, 92.38, 99.83 for RML; 99.58, 96.03, 99.78 for RLL, respectively. Clinician's visual assessment showed that 164/175 lobe contours met the requirements for clinical use, only 11 contours need manual correction.

Conclusions: Our 2D-3D hybrid CNN model achieved accurate automatic segmentation of lung lobes on conventional slice-thickness CT of locally advanced lung cancer patients, and has good clinical practicability.
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http://dx.doi.org/10.1186/s12938-021-00932-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8461922PMC
September 2021

Dosimetric effect of intensity-modulated radiation therapy for postoperative non-small cell lung cancer with and without air cavity in the planning target volume.

Med Dosim 2021 Sep 19. Epub 2021 Sep 19.

Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China. Electronic address:

To evaluate the dosimetric effect of intensity-modulated radiation therapy (IMRT) for postoperative non-small cell lung cancer (NSCLC), with and without the air cavity in the planning target volume (PTV). Two kinds of IMRT plans were made for 21 postoperative NSCLC patients. In Plan-0: PTV included the tracheal air cavity, and in Plan-1: the air cavity was subtracted from the PTV. For PTV, the dosimetric parameters, including D, D, D, D, D, conformity index (CI), and homogeneity index (HI) were evaluated. For organs at risk (OARs), the evaluation indexes, included the V, V and the mean lung dose (MLD) of total lung, the V, V, and the mean heart dose (MHD) of heart, the spinal cord D, and the V and the mean esophageal dose (MED) of esophagus. The number of segments and MUs were also recorded. Additionally, the correlation between the Plan-1 dosimetric change value relative to Plan-0, the size of air cavity, and the volume proportion of the cavity in the PTV was also analyzed. The D of PTV, D, D, HI and CI in Plan-1 decreased compared with those in Plan-0. For OARs, the V, MHD, and MED also decreased. The CI change value of Plan-1 relative to Plan-0 had a significantly negative correlation with the size and the volume proportion of air cavity, and the MED change value also had a significantly negative correlation with the air cavity size. The IMRT plans for patients with postoperative NSCLC can achieve a better target dose distribution and offer an improved sparing of the heart and esophagus by removing the PTV air cavity, while reducing the target conformity. The change value of CI and MED had a significantly negative correlation with the air cavity size.
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http://dx.doi.org/10.1016/j.meddos.2021.07.005DOI Listing
September 2021

Dosimetric Comparison, Treatment Efficiency Estimation, and Biological Evaluation of Popular Stereotactic Radiosurgery Options in Treating Single Small Brain Metastasis.

Front Oncol 2021 5;11:716152. Epub 2021 Aug 5.

Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.

Objectives: This study aimed to show the advantages of each stereotactic radiosurgery (SRS) treatment option for single small brain metastasis among Gamma Knife (GK), Cone-based VMAT (Cone-VMAT), and MLC-based CRT (MLC-CRT) plans.

Materials And Methods: GK, Cone-VMAT, and MLC-CRT SRS plans were retrospectively generated for 11 patients with single small brain metastasis whose volume of gross tumor volume (GTV) ranged from 0.18 to 0.76 cc (median volume 0.60 cc). Dosimetric parameters, treatment efficiency, and biological parameters of the three techniques were compared and evaluated. The metric variation with the planning target volume (PTV) was also studied.

Results: The conformity index (CI) was similar in GK and MLC-CRT plans, higher than Cone-VMAT. Cone-VMAT achieved comparable volume covered by 12 Gy (V12) and gradient index (GI) as GK, lower than MLC-CRT. The heterogeneity index (HI) of GK, Cone-VMAT, and MLC-CRT decreased sequentially. GK gave the lowest volume covered by 3 Gy (V3) and 6 Gy (V6), while MLC-CRT got the highest. The beam-on time and treatment time of GK, Cone-VMAT, and MLC-CRT decreased in turn. Tumor control probability (TCP) of all three SRS plans was greater than 98%, and normal tissue complication probability (NTCP) of all organs at risk (OARs) was below 0.01%. GK and Cone-VMAT resulted in superior TCP and NTCP of the normal brain tissue than MLC-CRT. The relative value of Cone-VMAT and GK for all metrics hardly changed with the target volume. Except for the unchanged HI and TCP, the other results of MLC-CRT with respect to GK improved as the target volume increased. MLC-CRT could produce higher CI than GK and Cone-VMAT when the target volume increased above 2 and 1.44 cc, respectively.

Conclusion: For single small brain metastases, Cone-VMAT may be used as an alternative to GK-free centers. In addition to the advantage of short treatment time, MLC-CRT showed superiority in CI as the target volume increased. Treatment centers can choose appropriate SRS technique on a case-by-case basis according to institutional conditions and patients' individual needs.
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http://dx.doi.org/10.3389/fonc.2021.716152DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8447903PMC
August 2021

Dosimetric comparison and biological evaluation of fixed-jaw intensity-modulated radiation therapy for T-shaped esophageal cancer.

Radiat Oncol 2021 Aug 19;16(1):158. Epub 2021 Aug 19.

Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, No. 241 West Huaihai Road, Xuhui District, Shanghai, 200030, China.

Background: To evaluate the dosimetric and biological benefits of the fixed-jaw (FJ) intensity-modulated radiation therapy (IMRT) technique for patients with T-shaped esophageal cancer.

Methods: FJ IMRT plans were generated for thirty-five patients and compared with jaw tracking (JT) IMRT, static jaw (SJ) IMRT and JT volumetric modulated arc therapy (VMAT). Dosimetric parameters, tumor control probability (TCP) and normal tissue complication probability (NTCP), monitor units (MUs), delivery time and gamma passing rate, as a measure of dosimetric verification, were compared. The correlation between the length of PTV-C below the upper boundary of lung tissue (PTV-C) and dosimetric parameters and NTCP of the lung tissue were analyzed.

Results: The homogeneity and conformity of the target in the four plans were basically equivalent. When compared to the JT IMRT and SJ IMRT plans, FJ IMRT plan led to a statistically significant improvement in the NTCP and low-middle dosimetric parameters of the lung, and the improvement had a moderately positive correlation with the length of PTV-C, with a correlation coefficient ranging from 0.523 to 0.797; the FJ IMRT plan exhibited better lung sparing in low-dose volumes than the JT VMAT plan. The FJ IMRT plan had similar MUs (888 ± 99) and delivery times (516.1 ± 54.7 s) as the JT IMRT plan (937 ± 194, 522 ± 5.6 s) but higher than SJ IMRT (713 ± 137, 488.8 ± 45.2 s) and JT VMAT plan (517 ± 59, 263.7 ± 43.3 s).

Conclusions: The FJ IMRT technique is superior in reducing the low-dose volumes of lung tissues for patients with T-shaped esophageal cancer.
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http://dx.doi.org/10.1186/s13014-021-01882-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8375041PMC
August 2021

Geometric and Dosimetric Changes in Tumor and Lung Tissue During Radiotherapy for Lung Cancer With Atelectasis.

Front Oncol 2021 22;11:690278. Epub 2021 Jul 22.

Shanghai Chest Hospital, Shanghai Jiaotong University, Shanghai, China.

Background And Purpose: This article retrospectively characterized the geometric and dosimetric changes in target and normal tissues during radiotherapy for lung cancer patients with atelectasis.

Materials And Methods: A total of 270 cone beam computed tomography (CBCT) scans of 18 lung patients with atelectasis were collected. The degree and time of resolution or expansion of the atelectasis were recorded. The geometric, dosimetric, and biological changes in the target and lung tissue were also quantified.

Results: There were two patients with expansion, four patients with complete regression, six patients with partial regression, and six patients with no change. The time of resolution or expansion varied. The tumor volume increased by 3.8% in the first seven fractions, then decreased from the 9th fraction, and by 33.4% at the last CBCT. In the LR direction, the average center of mass (COM), boundaries of the tumors gradually shifted mediastinally. In the AP direction, the COM of the tumors was shifted slightly in the posterior direction and then gradually shifted to the anterior direction; the boundaries of the tumors all moved mediastinally. In the SI direction, the COM of the tumors on the right side of the body was substantially shifted toward the head direction. The boundaries of the tumors varied greatly. D, D, D, V, V, and TCP of the PTV were reduced during radiotherapy and were reduced to their lowest values during the last two fractions. The volume of the ipsilateral lung tended to increase gradually. The V, V, V, V, V, and NTCP of the total lung gradually increased with the fraction.

Conclusions: For most patients, regression of the atelectasis occurred, and the volume of the ipsilateral lung tended to increase while the tumor volume decreased, and the COM and boundary of the tumors shifted toward mediastinum, which caused an insufficient dose to the target and an overdose to the lungs. Regression or expansion may occur for any fraction, and it is therefore recommended that CBCT be performed at least every other day.
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http://dx.doi.org/10.3389/fonc.2021.690278DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8339992PMC
July 2021

Virtual Patient-Specific Quality Assurance of IMRT Using UNet++: Classification, Gamma Passing Rates Prediction, and Dose Difference Prediction.

Front Oncol 2021 20;11:700343. Epub 2021 Jul 20.

Shanghai Chest Hospital, Shanghai Jiaotong University, Shanghai, China.

The dose verification in radiotherapy quality assurance (QA) is time-consuming and places a heavy workload on medical physicists. To provide a clinical tool to perform patient specific QA accurately, the UNet++ is investigated to classify failed or pass fields (the GPR lower than 85% is considered "failed" while the GPR higher than 85% is considered "pass"), predict gamma passing rates (GPR) for different gamma criteria, and predict dose difference from virtual patient-specific quality assurance in radiotherapy. UNet++ was trained and validated with 473 fields and tested with 95 fields. All plans used Portal Dosimetry for dose verification pre-treatment. Planar dose distribution of each field was used as the input for UNet++, with QA classification results, gamma passing rates of different gamma criteria, and dose difference were used as the output. In the test set, the accuracy of the classification model was 95.79%. The mean absolute error (MAE) were 0.82, 0.88, 2.11, 2.52, and the root mean squared error (RMSE) were 1.38, 1.57, 3.33, 3.72 for 3%/3mm, 3%/2 mm, 2%/3 mm, 2%/2 mm, respectively. The trend and position of the predicted dose difference were consistent with the measured dose difference. In conclusion, the Virtual QA based on UNet++ can be used to classify the field passed or not, predict gamma pass rate for different gamma criteria, and predict dose difference. The results show that UNet++ based Virtual QA is promising in quality assurance for radiotherapy.
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http://dx.doi.org/10.3389/fonc.2021.700343DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8330420PMC
July 2021

A novel lung-avoidance planning strategy based on 4DCT ventilation imaging and CT density characteristics for stage III non-small-cell lung cancer patients.

Strahlenther Onkol 2021 Aug 5. Epub 2021 Aug 5.

Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, NO.241 West Huaihai Road, Xuhui District, 20030, Shanghai, China.

Background: Functional planning based merely on 4DCT ventilation imaging has limitations. In this study, we proposed a radiotherapy planning strategy based on 4DCT ventilation imaging and CT density characteristics.

Materials And Methods: For 20 stage III non-small-cell lung cancer (NSCLC) patients, clinical plans and lung-avoidance plans were generated. Through deformable image registration (DIR) and quantitative image analysis, a 4DCT ventilation map was calculated. High-, medium-, and low-ventilation regions of the lung were defined based on the ventilation value. In addition, the total lung was also divided into high-, medium-, and low-density areas according to the HU threshold. The lung-avoidance plan aimed to reduce the dose to functional and high-density lungs while meeting standard target and critical structure constraints. Standard and dose-function metrics were compared between the clinical and lung-avoidance plans.

Results: Lung avoidance plans led to significant reductions in high-function and high-density lung doses, without significantly increasing other organ at risk (OAR) doses, but at the expense of a significantly degraded homogeneity index (HI) and conformity index (CI; p < 0.05) of the planning target volume (PTV) and a slight increase in monitor units (MU) as well as in the number of segments (p > 0.05). Compared with the clinical plan, the mean lung dose (MLD) in the high-function and high-density areas was reduced by 0.59 Gy and 0.57 Gy, respectively.

Conclusion: A lung-avoidance plan based on 4DCT ventilation imaging and CT density characteristics is feasible and implementable, with potential clinical benefits. Clinical trials will be crucial to show the clinical relevance of this lung-avoidance planning strategy.
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http://dx.doi.org/10.1007/s00066-021-01821-1DOI Listing
August 2021

Automatic segmentation of lung tumors on CT images based on a 2D & 3D hybrid convolutional neural network.

Br J Radiol 2021 Oct 4;94(1126):20210038. Epub 2021 Aug 4.

Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.

Objective: A stable and accurate automatic tumor delineation method has been developed to facilitate the intelligent design of lung cancer radiotherapy process. The purpose of this paper is to introduce an automatic tumor segmentation network for lung cancer on CT images based on deep learning.

Methods: In this paper, a hybrid convolution neural network (CNN) combining 2D CNN and 3D CNN was implemented for the automatic lung tumor delineation using CT images. 3D CNN used V-Net model for the extraction of tumor context information from CT sequence images. 2D CNN used an encoder-decoder structure based on dense connection scheme, which could expand information flow and promote feature propagation. Next, 2D features and 3D features were fused through a hybrid module. Meanwhile, the hybrid CNN was compared with the individual 3D CNN and 2D CNN, and three evaluation metrics, Dice, Jaccard and Hausdorff distance (HD), were used for quantitative evaluation. The relationship between the segmentation performance of hybrid network and the GTV volume size was also explored.

Results: The newly introduced hybrid CNN was trained and tested on a dataset of 260 cases, and could achieve a median value of 0.73, with mean and stand deviation of 0.72 ± 0.10 for the Dice metric, 0.58 ± 0.13 and 21.73 ± 13.30 mm for the Jaccard and HD metrics, respectively. The hybrid network significantly outperformed the individual 3D CNN and 2D CNN in the three examined evaluation metrics ( < 0.001). A larger GTV present a higher value for the Dice metric, but its delineation at the tumor boundary is unstable.

Conclusions: The implemented hybrid CNN was able to achieve good lung tumor segmentation performance on CT images.

Advances In Knowledge: The hybrid CNN has valuable prospect with the ability to segment lung tumor.
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http://dx.doi.org/10.1259/bjr.20210038DOI Listing
October 2021

Regression models for predicting physical and EQD plan parameters of two methods of hybrid planning for stage III NSCLC.

Radiat Oncol 2021 Jun 27;16(1):119. Epub 2021 Jun 27.

Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiaotong University, Shanghai, China.

Background/purpose: To establish regression models of physical and equivalent dose in 2 Gy per fraction (EQD) plan parameters of two kinds of hybrid planning for stage III NSCLC.

Methods: Two kinds of hybrid plans named conventional fraction radiotherapy & stereotactic body radiotherapy (C&S) and conventional fraction radiotherapy & simultaneous integrated boost (C&SIB) were retrospectively made for 20 patients with stage III NSCLC. Prescription dose of C&S plans was 2 Gy × 30f for planning target volume of lymph node (PTV) and 12.5 Gy × 4f for planning target volume of primary tumor (PTV), while prescription dose of C&SIB plans was 2 Gy × 26f for PTV and sequential 2 Gy × 4f for PTV combined with 12.5 Gy × 4f for PTV. Regression models of physical and EQD plan parameters were established based on anatomical geometry features for two kinds of hybrid plans. The features were mainly characterized by volume ratio, min distance and overlapping slices thickness of two structures. The possibilities of regression models of EQD plan parameters were verified by spearman's correlation coefficients between physical and EQD plan parameters, and the influence on the consistence of fitting goodness between physical and EQD models was investigated by the correlations between physical and EQD plan parameters. Finally, physical and EQD models predictions were compared with plan parameters for two new patients.

Results: Physical and EQD plan parameters of PTV CI have shown strong positive correlations with PTV volume and min distance, and strong negative correlations with PTV volume for two kinds of hybrid plans. PTV CI is not only correlated with above three geometry features, but also negatively correlated with overlapping slices thickness. When neck lymph node metastasis was excluded from PTV volume, physical and EQD total lung V showed a high linear correlation with corrected volume ratio Meanwhile, physical total lung mean dose (MLD) had a high linear correlation with corrected volume ratio, while EQD total lung MLD was not only affected by corrected volume ratio but also volume ratio Heart D, D and mean dose (MHD) would be more susceptible to overlapping structure. Min distance may be an important feature for predicting EQD esophageal max dose for hybrid plans. It's feasible for regression models of EQD plan parameters, and the consistence of the fitting goodness of physical and EQD models had a positive correlation with spearman's correlation coefficients between physical and EQD plan parameters. For total lung V, ipsilateral lung V, and ipsilateral lung MLD, the models could predict that C&SIB plans were higher than C&S plans for two new patients.

Conclusion: The regression models of physical and EQD plan parameters were established with at least moderate fitting goodness in this work, and the models have a potential to predict physical and EQD plan parameters for two kinds of hybrid planning.
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http://dx.doi.org/10.1186/s13014-021-01848-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8237456PMC
June 2021

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

Biomed Eng Online 2021 Jun 3;20(1):54. Epub 2021 Jun 3.

Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China.

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.
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http://dx.doi.org/10.1186/s12938-021-00890-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8173789PMC
June 2021

Effect of MU-weighted multi-leaf collimator position error on dose distribution of SBRT radiotherapy in peripheral non-small cell lung cancer.

J Appl Clin Med Phys 2020 Dec 31;21(12):74-83. Epub 2020 Oct 31.

Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.

Purpose: Position accuracy of the multi-leaf collimator (MLC) is essential in stereotactic body radiotherapy (SBRT). This study is aimed to investigate the dosimetric impacts of the MU-weighted MLC positioning uncertainties of SBRT for patients with early stage peripheral non-small cell lung cancer (NSCLC).

Methods: Three types of MLC position error were simulated: Type 1, random error; Type 2, system shift, in which both MLC banks shifted to the left or right direction; and Type 3, in which both MLC banks moved with same magnitudes in the opposite directions. Two baseline plans were generated: an automatic plan (AP) and a manually optimized plan (MP). Multi-leaf collimator position errors were introduced to generate simulated plans with the preset MLC leaf position errors, which were then reimported into the Pinnacle system to generate simulated plans, respectively. The dosimetric parameters (CI, nCI, GI, etc.) and gEUD values of PTV and OARs were calculated. Linear regression between MU-weighted/unweighted MLC position error and gEUD was performed to obtain dose sensitivity.

Results: The dose sensitivities of the PTVs were -4.93, -38.94, -41.70, -55.55, and 30.33 Gy/mm for random, left shift, right shift, system close, and system open MLC errors, respectively. There were significant differences between the MU-weighted and the unweighted dose sensitivity, which was -38.94 Gy/mm vs -3.42 Gy/mm (left shift), -41.70 Gy/mm vs -3.56 Gy/mm (right shift), -55.55 Gy/mm vs -4.84 Gy/mm (system close), and 30.33 vs 2.64 Gy/mm (system open). For the system open/close MLC errors, as the PTV volume became larger, the dose sensitivity decreased. APs provided smaller dose sensitivity for the system shift and system close MLC errors compared to the conventional MPs.

Conclusions: There was significant difference in dose sensitivity between MU-weighted and unweighted MLC position error of SBRT radiotherapy in peripheral NSCLC. MU is suggested to be included in the dosimetric evaluation of the MLC misalignments, since it is much closer to clinical radiotherapy.
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http://dx.doi.org/10.1002/acm2.13061DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7769390PMC
December 2020

Prediction of Three-Dimensional Radiotherapy Optimal Dose Distributions for Lung Cancer Patients With Asymmetric Network.

IEEE J Biomed Health Inform 2021 04 6;25(4):1120-1127. Epub 2021 Apr 6.

The iterative design of radiotherapy treatment plans is time-consuming and labor-intensive. In order to provide a guidance to treatment planning, Asymmetric network (A-Net) is proposed to predict the optimal 3D dose distribution for lung cancer patients. A-Net was trained and tested in 392 lung cancer cases with the prescription doses of 50Gy and 60Gy. In A-Net, the encoder and decoder are asymmetric, able to preserve input information and to adapt the limitation of GPU memory. Squeeze and excitation (SE) units are used to improve the data-fitting ability. A loss function involving both the dose distribution and prescription dose as ground truth are designed. In the experiment, A-Net is separately trained and tested in the 50Gy and 60Gy dataset and most of the metrics A-Net achieve similar performance as HD-Unet and 3D-Unet, and some metrics slightly better. In the 50Gy-and-60Gy-combined dataset, most of the A-Net's metrics perform better than the other two. In conclusion, A-Net can accurately predict the IMRT dose distribution in the three datasets of 50Gy and 50Gy-and-60Gy-combined dataset.
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http://dx.doi.org/10.1109/JBHI.2020.3025712DOI Listing
April 2021

On the optimal number of dose-limiting shells in the SBRT auto-planning design for peripheral lung cancer.

J Appl Clin Med Phys 2020 Sep 23;21(9):134-142. Epub 2020 Jul 23.

Department of Radiation Oncology, Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, USA.

Purpose: The number of dose-limiting shells in the optimization process is one of the key factors determining the quality of stereotactic body radiotherapy (SBRT) auto-planning in the Pinnacle treatment planning system (TPS). This study attempted to derive the optimal number of shells by evaluating the auto-plans designed with different number of shells for peripheral lung cancer patients treated with SBRT.

Methods: Identical treatment technique, optimization process, constraints, and dose calculation algorithm in the Pinnacle TPS were retrospectively applied to 50 peripheral lung cancer patients who underwent SBRT in our center. For each of the patients, auto-plans were optimized based on two shells, three shells, four shells, five shells, six shells, seven shells, eight shells, respectively. The optimal number of shells for the SBRT auto-planning was derived through the evaluations and comparisons of various dosimetric parameters of planning target volume (PTV) and organs at risk (OARs), monitor units (MU), and optimization time of the plans.

Results: The conformity index (CI) and the gradient index (GI) of PTV, the maximum dose outside the 2 cm of PTV (D ), D of spinal cord (SC ), the percentage of volume of total lung excluding ITV receiving 20 Gy (V20) and 10 Gy (V10), and the mean lung dose (MLD) were improved when the number of shell increased, but the improvement became not significant as the number of shell reached six. The monitor units (MUs) varied little among different plans where no statistical differences were found. However, as the number of shell increased, the auto-plan optimization time increased significantly.

Conclusions: It appears that for peripheral lung SBRT plan using six shells can yield satisfactory plan quality with acceptable beam MUs and optimization time in the Pinnacle TPS.
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http://dx.doi.org/10.1002/acm2.12983DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7497906PMC
September 2020

Dosimetric comparison and biological evaluation of PET- and CT-based target delineation for LA-NSCLC using auto-planning.

Phys Med 2019 Nov 31;67:77-84. Epub 2019 Oct 31.

Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China. Electronic address:

Using auto-planning, the dosimetric and biological differences between PET- and CT-based target delineation in LA-NSCLC were studied. Twenty-three patients with IIIA-IIIB NSCLC were included in this retrospective study. For each patient, two AP plans (Plan_PET, Plan_CT) were generated based on PET- and CT-based gross tumor volume (GTV, GTV). The volume, boundary and center of mass (COM) of GTVPET and GTVCT were compared. Dosimetric indicators such as mean lung dose (MLD) and so on were evaluated. Tumor control probability (TCP) of GTVPET and GTVCT and normal tissue complication probability (NTCP) of total lung and heart were calculated. A paired-samples t-test was used to check for significant differences (p < 0.05) between dataset. Volume of GTVPET was significantly smaller than that of GTVCT. Under the premise that GTVPET met the clinical requirements in Plan_PET, GTVCT couldn't satisfy the requirements. GTVCT met the clinical requirements in Plan_CT, and four cases of GTVPET could not satisfy the requirements. Compared with Plan_CT, Plan_PET significantly reduced MLD, V5, V10, V13, V15, V20, V30 and V40 of total lung, and MHD, V30 and V40 of heart, and MUs. No significant difference was observed with respect to Dmax of spinal cord. TCP of GTVPET in Plan_PET was significantly higher than that of GTVCT. NTCP of total lung in Plan_PET was significantly lower than that in Plan_CT. There were differences in volume, boundary, and COM of targets based on the two delineation methods. These led to differences in dosimetric and biological indicators. For LA-NSCLC, the way that most hospitals only use CT to delineate the target should be careful consideration.
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http://dx.doi.org/10.1016/j.ejmp.2019.09.080DOI Listing
November 2019
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