Performance of a knowledge-based planning model for optimizing intensity-modulated radiotherapy plans for partial breast irradiation

Dosimetric evaluation of different planning strategies for hypofractionated whole-breast irradiation technique

Purpose.The dose hotspot areas in hypofractionated whole-breast irradiation (WBI) greatly increase the risk of acute skin toxicity because of the anatomical peculiarities of the breast. In this study, we presented several novel planning strategies that integrate multiple sub-planning target volumes (sub-PTVs), field secondary placement, and RapidPlan models for right-sided hypofractionated WBI.Methods.A total of 35 cases of WBI with a dose of 42.5 Gy for PTVs using tangential intensity-modulated radiotherapy (IMRT) were selected. Both PTVs were planned for simultaneous treatment using the original manual multiple sub-PTV plan (OMMP) and the original manual single-PTV plan (OMSP). The manual field secondary placement multiple sub-PTV plan (m-FSMP) with multiple objects on the original PTV and the manual field secondary placement single-objective plan (m-FSSP) were initially planned, which were distribution-based of V105 (volume receiving 105% of the prescription dose). In addition, two RapidPlan-based plans were developed, including the RapidPlan-based multiple sub-PTVs plan (r-FSMP) and the RapidPlan-based single-PTV plan (r-FSSP). Dosimetric parameters of the plans were compared, and V105 was evaluated using multivariate analysis to determine how it was related to the volume of PTV and the interval of lateral beam angles (ILBA).Results.The lowest mean V105 (5.64 ± 6.5%) of PTV was observed in m-FSMP compared to other manual plans. Upon validation, r-FSSP demonstrated superior dosimetric quality for OAR compared to the two other manual planning methods, except for V5(the volume of ipsilateral lung receiving 5 Gy) of the ipsilateral lung. While r-FSMP showed no significant difference (p = 0.06) compared to r-FSSP, it achieved the lowest V105 value (4.3 ± 4.5%), albeit with a slight increase in the dose to some OARs. Multivariate GEE linear regression showed that V105 is significantly correlated with target volume and ILBA.Conclusions.m-FSMP and r-FSMP can substantially enhance the homogeneity index (HI) and reduce V105, thereby minimizing the risk of acute skin toxicities, even though there may be a slight dose compromise for certain OARs.

Accelerated Partial Breast Irradiation Using 5 Daily Fractions: A Prospective, Phase 2, Multicenter Trial of Cosmetic Outcomes and Toxicity-ACCEL Final Results

PURPOSE

This study investigated the cosmetic degradation and toxicity for an accelerated partial breast irradiation (APBI) prescription delivered in 5 fractions over 1 week and compared the outcomes with those of whole breast irradiation (WBI).

METHODS AND MATERIALS

The trial was a multicenter, single-arm, phase 2 prospective cohort study. Eligible women 50 years of age or older with estrogen receptor-positive and human epidermal growth factor receptor 2-negative invasive ductal carcinoma or ductal carcinoma in situ after breast-conserving surgery received 27 Gy in 5 daily fractions of APBI. The primary endpoint was noninferiority of 2-year cosmesis using the RAPID trial's WBI arm as the control arm. A global consensus cosmetic score using a European Organisation for Research and Treatment of Cancer rating scale score of excellent, good, fair, or poor for each patient at baseline and 2 years was generated by a panel of 5 radiation oncologists using photographs of treated and untreated breasts.

RESULTS

From 2016 to 2019, 298 eligible women were enrolled. By the 2-year follow-up, 76 patients had been lost or withdrawn and 3 had died, resulting in 219 patients available for complete, 2-year photographic cosmetic evaluation. The median follow-up for all participants was 4.7 years (IQR, 3.8-5.5 years). No patient had a fair or poor cosmetic score at the 2-year evaluation. Cosmesis was better or unchanged for 97% of patients and worse for 3% (excellent to good), and no cosmetic failures occurred. The confidence intervals were 0.88 (0.86-0.90) and 1.00 (0.99-1.00) for the RAPID and ACCEL trials, respectively.

CONCLUSIONS

Cosmetic degradation with 5 daily treatments of the ACCEL trial's APBI intervention is noninferior to the WBI arm of the RAPID trial.

Knowledge-based plan optimization for prostate SBRT delivered with CyberKnife according to RTOG0938 protocol

PURPOSE

To extend the knowledge-based (KB) automatic planning approach to CyberKnife in the case of Stereotactic Body Radiation Therapy (SBRT) for prostate cancer.

METHODS

Seventy-two clinical plans of patients treated according to the RTOG0938 protocol (36.25 Gy/5fr) with CyberKnife were exported from the CyberKnife system to Eclipse to train a KB-model using the Rapid Plan tool. The KB approach provided dose-volume objectives for specific OARs only and not PTV. Bladder, rectum and femoral heads were considered in the model. The KB-model was successfully trained on 51 plans and then validated on 20 new patients. A KB-based template was tuned in the Precision system for both sequential optimization (SO) and VOLO optimization algorithms. Plans of the validation group were re-optimized (KB-TP) using both algorithms without any operator intervention and compared against the original plans (TP) in terms of OARs/PTV dose-volume parameters. Paired Wilcoxon signed-rank tests were performed to assess statistically significant differences (p < 0.05).

RESULTS

Regarding SO, automatic KB-TP plans were generally better than or equivalent to TP plans. PTVs V95% was slightly worse while OARs sparing for KB-TP was significantly improved. Regarding VOLO optimization, the PTVs coverage was significantly better for KB-TP while there was a limited worsening in the rectum. A significant improvement was observed in the bladder in the range of low-intermediate doses.

CONCLUSIONS

An extension of the KB optimization approach to the CyberKnife system has been successfully developed and validated in the case of SBRT prostate cancer.

Dose prediction of organs at risk in patients with cervical cancer receiving brachytherapy using needle insertion based on a neural network method

OBJECTIVE

A neural network method was employed to establish a dose prediction model for organs at risk (OAR) in patients with cervical cancer receiving brachytherapy using needle insertion.

METHODS

A total of 218 CT-based needle-insertion brachytherapy fraction plans for loco-regionally advanced cervical cancer treatment were analyzed in 59 patients. The sub-organ of OAR was automatically generated by self-written MATLAB, and the volume of the sub-organ was read. Correlations between D2cm³ of each OAR and volume of each sub-organ-as well as high-risk clinical target volume for bladder, rectum, and sigmoid colon-were analyzed. We then established a neural network predictive model of D2cm³ of OAR using the matrix laboratory neural net. Of these plans, 70% were selected as the training set, 15% as the validation set, and 15% as the test set. The regression R value and mean squared error were subsequently used to evaluate the predictive model.

RESULTS

The D2cm³/D90 of each OAR was related to volume of each respective sub-organ. The R values for bladder, rectum, and sigmoid colon in the training set for the predictive model were 0.80513, 0.93421, and 0.95978, respectively. The ∆D2cm³/D90 for bladder, rectum, and sigmoid colon in all sets was 0.052 ± 0.044, 0.040 ± 0.032, and 0.041 ± 0.037, respectively. The MSE for bladder, rectum, and sigmoid colon in the training set for the predictive model was 4.779 × 10^-3, 1.967 × 10^-3 and 1.574 × 10^-3, respectively.

CONCLUSION

The neural network method based on a dose-prediction model of OAR in brachytherapy using needle insertion was simple and reliable. In addition, it only addressed volumes of sub-organs to predict the dose of OAR, which we believe is worthy of further promotion and application.

Knowledge-based automatic plan optimization for left-sided whole breast tomotherapy

Background/Purpose

Tomotherapy may deliver high-quality whole breast irradiation at static angles. The aim of this study was to implement Knowledge-Based (KB) automatic planning for left-sided whole breast using this modality.

Materials/Methods

Virtual volumetric plans were associated to the dose distributions of 69 Tomotherapy (TT) clinical plans of previously treated patients, aiming to train a KB-model using a commercial tool completely implemented in our treatment planning system. An individually optimized template based on the resulting KB-model was generated for automatic plan optimization. Thirty patients of the training set and ten new patients were considered for internal/external validation. Fully-automatic plans (KB-TT) were generated and compared using the same geometry/number of fields of the corresponding clinical plans.

Results

KB-TT plans were successfully generated in 26/30 and 10/10 patients of the internal/external validation sets; for 4 patients whose original plans used only two fields, the manual insertion of one/two fields before running the automatic template was sufficient to obtain acceptable plans. Concerning internal validation, planning target volume V_95%/D_1%/dose distribution standard deviation improved by 0.9%/0.4Gy/0.2Gy (p < 0.05) against clinical plans; Organs at risk mean doses were also slightly improved (p < 0.05) by 0.07/0.4/0.2/0.01 Gy for left lung/heart/right breast/right lung respectively. Similarly satisfactory results were replicated in the external validation set. The resulting treatment duration was 8 ± 1 min, consistent with our clinical experience. The active planner time per patient was 5–10 minutes.

Conclusion

Automatic TT left-sided breast KB-plans are comparable to or slightly better than clinical plans and can be obtained with limited planner time. The approach is currently under clinical implementation.

An updated approach for deriving PTV margins using image guidance and deformable dose accumulation

Objective. To demonstrate an updated approach for deriving planning target volume (PTV) margins for a patient population treated with volumetric image-guided radiotherapy. Approach. The approach uses a semi-automated workflow within commercial radiotherapy applications that combines dose accumulation with the bidirectional local distance (BLD) metric. The patient cohort is divided into derivation and validation datasets. For each patient in the derivation dataset, a treatment plan is generated with a 0 mm PTV margin (the idealized treatment scenario without the influence of the standard margin). Deformable image registration enabled dose accumulation of these zero-margin plans. PTV margins are derived by using the BLD to calculate the geometric extent of underdosed regions of the clinical target volume (CTV). The PTV margin is validated by ensuring the specified CTV coverage criterion is met when the margin is applied to the validation dataset. Main results. The methodology was applied to two cohorts: 40 oropharyngeal cancer patients and 50 early-stage breast cancer patients. Ten patients from each cohort were used for validation. PTV margins derived for the oropharyngeal and early-stage breast cancer patient cohorts were 3 and 5 mm, respectively, and ensure that 95% of the prescription dose is delivered to 98% of the CTV for 90% of patients. Dose accumulation showed that the CTV coverage criterion was achieved for at least 90% of patients when the margins were applied. Significance. This methodology can be used to derive appropriate PTV margins for realistic treatment scenarios and any disease site, which will improve our understanding of patient outcomes.