BackgroundThe development of a dose-volume-histogram (DVH) estimation model for knowledge-based planning is very time-consuming and it could be inefficient if it was only used for similar upcoming cases as supposed. It is clinically desirable to explore and validate other potential applications for a configured model. This study tests the hypothesis that a supine volumetric modulated arc therapy (VMAT) model can optimize intensity modulated radiotherapy (IMRT) plans of other patient setup orientations.MethodsBased on RapidPlan, a DVH estimation model was trained using 81 supine VMAT rectal plans and validated on 10 similar cases to ensure the robustness of its designed purpose. Attempts were then made to apply the model to re-optimize the dynamic MLC-sequences of the duplicated IMRT plans from 30 historical patients (20 prone and 10 supine) that were treated with the same prescription as for the model (50.6 and 41.8 Gy to 95 % of PGTV and PTV simultaneously/22 fractions). The performance of knowledge-based re-optimization and the impact of setup orientations were evaluated dosimetrically.ResultsThe VMAT model validation on similar cases showed comparable target dose distribution and significantly improved organ sparing (by 10.77 ~ 18.65 %) than the original plans. IMRT plans of either setup can be re-optimized using the supine VMAT model, which significantly reduced the dose to the bladder (by 25.88 % from 33.85 ± 2.96 to 25.09 ± 1.32 Gy for D50 %; by 22.77 % from 33.99 ± 2.77 to 26.25 ± 1.22 Gy for mean dose) and femoral head (by 12.27 % from 15.65 ± 3.33 to 13.73 ± 1.43 Gy for D50 %; by 10.09 % from 16.26 ± 2.74 to 14.62 ± 1.10 Gy for mean dose), all P < 0.01. Although the dose homogeneity and PGTV conformity index (CI_PGTV) changed slightly (≤0.01), CI_PTV of IMRT plans was significantly increased (Δ = 0.17, P < 0.01) by the manually defined target-objectives in the VMAT optimizer. The semi-automated IMRT planning increased the global maximum dose and V107 % due to the missing of hot spot suppression by specific manual optimizing or fluence map editing.ConclusionsThe Varian RapidPlan model trained on a technique and orientation can be used for another. Knowledge-based planning improves organ sparing and quality consistency, yet the target-objectives defined for VMAT-optimizer should be readapted to IMRT planning, followed by manual hot spot processing.

Purpose The implementation of radiomics and machine learning (ML) techniques on analyzing two‐dimensional gamma maps has been demonstrated superior to the conventional gamma analysis for error identification in intensity modulated radiotherapy (IMRT) quality assurance (QA). Recently, the Structural SIMilarity (SSIM) sub‐index maps were shown to be able to reveal the error types of the dose distributions. In this study, we aimed to apply radiomics analysis on SSIM sub‐index maps and develop ML models to classify delivery errors in patient‐specific dynamic IMRT QA. Methods Twenty‐one sliding‐window IMRT plans of 180 beams for three treatment sites were involved in this study. Four types of machine‐related errors of various magnitudes were simulated for each beam at each control point, including the monitor unit (MU) variations, same‐directional and opposite‐directional shifts of the multileaf collimators (MLCs) and random mispositioning of the MLCs. In the QA process, a total of 1620 portal dose (PD) images were acquired for the beams with and without errors. The predicted PD images of the original beams were set as references. To quantify the agreement between a measured PD image and the corresponding predicted PD image, four difference maps including three SSIM sub‐index maps, and one dose difference‐derived map were calculated. Then, radiomic features were extracted from the four difference maps of each measured PD image. We tested four typical classifiers including linear discriminant classifier (LDC), two supporting vector machine (SVM) classifiers, and random forest (RF) for this multiclass classification task. A nested cross‐validation scheme was used for model evaluations, where the SVM recursive feature elimination method was applied for feature selection. Finally, the performance of the ML model on identifying the error‐free and the erroneous cases was compared to that of the conventional gamma analysis. Results The statistics of the selected features showed that all of the difference maps and the feature categories made balanced contributions to solve this classification task. Best performance was achieved by the Linear‐SVM model with average overall classification accuracy of 0.86. Specifically, the average classification accuracies of the shift, opening, and the random errors were around 0.9. Moreover, ~80% of error‐free and MU errors were correctly classified. Using gamma analysis, the 3 mm/3% criterion was found insensitive to errors (sensitivity was only 0.33). Although the sensitivity to errors with the 2 mm/2% criterion increased to 0.79, still 8% worse than that of the ML model. Conclusions We proposed an ML‐based method for machine‐related error identification in patient‐specific dynamic IMRT QA, where radiomic analysis on SSIM sub‐index maps were used for feature extraction. With extensive validation to select the best features and classifiers, high accuracies in error classification were achieved. Compared with the conventional gamma threshold method, this approach has great potential in error...

RapidPlan, a commercial knowledge‐based optimizer, has been tested on head and neck, lung, esophageal, breast, liver, and prostate cancer patients. To appraise its performance on VMAT planning with simultaneous integrated boosting (SIB) for rectal cancer, this study configured a DVH (dose‐volume histogram) estimation model consisting 80 best‐effort manual cases of this type. Using the model‐ generated objectives, the MLC (multileaf collimator) sequences of other 70 clinically approved plans were reoptimized, while the remaining parameters, such as field geometry and photon energy, were maintained. Dosimetric outcomes were assessed by comparing homogeneity index (HI), conformal index (CI), hot spots (volumes receiving over 107% of the prescribed dose, normalV107%), mean dose and dose to the 50% volume of femoral head (normalDmean_FH and normalD50%_FH), and urinary bladder (normalDmean_UB and normalD50%_UB), and the mean DVH plotting. Paired samples t‐test or Wilcoxon signed‐rank test suggested that comparable CI were achieved by RapidPlan (0.99 ± 0.04 for PTVboost, and 1.03 ± 0.02 for PTV) and original plans (1.00 ± 0.05 for PTVboost and 1.03 ± 0.02 for PTV), respectively (p > 0.05). Slightly improved HI of planning target volume (PTVboost) and PTV were observed in the RapidPlan cases (0.05 ± 0.01 for PTVboost, and 0.26 ± 0.01 for PTV) than the original plans (0.06 ± 0.01 for PTVboost and 0.26 ± 0.01 for PTV), p < 0.05. More cases with positive V107% were found in the original (18 plans) than the RapidPlan group (none). RapidPlan significantly reduced the normalD50%_FH (by 1.53 Gy/9.86% from 15.52 ± 2.17 to 13.99 ± 1.16 Gy), normalDmean_FH (by 1.29 Gy/7.78% from 16.59±2.07 to 15.30±0.70 G), normalD50%_UB (by 4.93 Gy/17.50% from 28.17±3.07 to 23.24±2.13 Gy), and normalDmean_UB (by 3.94 Gy/13.43% from 29.34±2.34 to 25.40±1.36 Gy), respectively. The more concentrated distribution of RapidPlan data points indicated an enhanced consistency of plan quality.PACS number(s): 87.55.de; 87.55.dk

PCI after any response to initial chemotherapy significantly improved OS of ESCLC patients analyzed in this study.

We present experimental studies of higher-order modes of the flow in turbulent thermal convection in cells of aspect ratio ($\unicode[STIX]{x1D6E4}$) 1 and 0.5. The working fluid is water with the Prandtl number ($Pr$) kept at around 5.0. The Rayleigh number ($Ra$) ranges from $9\times 10^{8}$ to $6\times 10^{9}$ for $\unicode[STIX]{x1D6E4}=1$ and from $1.6\times 10^{10}$ to $7.2\times 10^{10}$ for $\unicode[STIX]{x1D6E4}=0.5$. We found that in $\unicode[STIX]{x1D6E4}=1$ cells, the first mode, which corresponds to the large-scale circulation (LSC), dominates the flow. The second mode (quadrupole mode), the third mode (sextupole mode) and the fourth mode (octupole mode) are very weak, on average these higher-order modes each contains less than 4 % of the total flow energy. In $\unicode[STIX]{x1D6E4}=0.5$ cells, the first mode is still the strongest but less dominant, the second mode becomes stronger which contains 13.7 % of the total flow energy and the third and the fourth modes are also stronger (containing 6.5 % and 1.1 % of the total flow energy respectively). It is found that during a reversal/cessation, the amplitude of the second mode and the remaining modes experiences a rapid increase followed by a decrease, which is opposite to the behaviour of the amplitude of the first mode – it decreases to almost zero then rebounds. In addition, it is found that during the cessation (reversal) of the LSC, the second mode dominates, containing 51.3 % (50.1 %) of the total flow energy, which reveals that the commonly called cessation event is not the cessation of the entire flow but only the cessation of the first mode (LSC). The experiment reveals that the second mode and the remaining higher-order modes play important roles in the dynamical process of the reversal/cessation of the LSC. We also show direct evidence that the first mode is more efficient for heat transfer. Furthermore, our study reveals that, during the cessation/reversal of the LSC, $Nu$ drops to its local minimum and the minimum of $Nu$ is ahead of the minimum of the amplitude of the LSC; and reversals can be distinguished from cessations in terms of global heat transport. A direct velocity measurement reveals the flow structure of the first- and higher-order modes.

PurposeTo compare the dosimetric differences between jaw tracking technique (JTT) and static jaw technique (SJT) in dynamic intensity-modulated radiotherapy (d-IMRT) and assess the potential advantages of jaw tracking technique.MethodsTwo techniques, jaw tracking and static jaw, were used respectively to develop the d-IMRT plans for 28 cancer patients with various lesion sites: head and neck, lungs, esophageal, abdominal, prostate, rectal and cervical. The dose volume histograms (DVH) and selected dosimetric indexes for the whole body and for organs at risk (OARs) were compared. A two dimensional ionization chamber Array Seven29 (PTW, Freiburg, Germany) and OCTAVIUS Octagonal phantom (PTW, Freiburg, Germany) were used to verify all the plans.ResultsFor all patients, the treatment plans using both techniques met the clinical requirements. The V5, V10, V20, V30, V40 (volumes receiving 5, 10, 20, 30 and 40 Gy at least, respectively), mean dose (Dmean) for the whole body and V5, V10, V20, Dmean for lungs in the JTT d-IMRT plans were significantly less than the corresponding values of the SJT d-IMRT plans (p < 0.001). The JTT d-IMRT plans deposited lower maximum dose (Dmax) to the lens, eyes, brainstem, spinal cord, and right optic nerve, the doses reductions for these OARs ranged from 2.2% to 28.6%. The JTT d-IMRT plans deposited significantly lower Dmean to various OARs (all p values < 0.05), the mean doses reductions for these OARs ranged from 1.1% to 31.0%, and the value reductions depend on the volume and the location of the OARs. The γ evaluation method showed an excellent agreement between calculation and measurement for all techniques with criteria of 3%/3 mm.ConclusionsBoth jaw tracking and static jaw d-IMRT plans can achieve comparable target dose coverage. JTT displays superior OARs sparing than SJT plans. These results are of clinical importance, especially for the patients with large and complex targets but close to some highly radio-sensitive organs to spare, and for patients with local recurrent or secondary primary malignant lesion within a previously irradiated area.

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The objective of this study was to evaluate the efficacy and safety of CT-guided radioactive 125 I seed implantation as a salvage treatment for locally recurrent head and neck soft tissue sarcoma (HNSTS) after surgery and external beam radiotherapy. METHODS AND MATERIALS: From December 2006 to February 2018, 25 patients with locally recurrent HNSTS after surgery and external beam radiotherapy were enrolled. All the patients successfully underwent CT-guided 125 I seed implantation. The primary end points included the objective response rate (ORR) and local progression-free survival (LPFS). The secondary end points were survival (OS) and safety profiles. RESULTS: After 125 I seed implantation, the ORR was 76.0%. The 1-, 3-, and 5-year LPFS rates were 65.6%, 34.4%, and 22.9%, respectively, with the median LPFS of 16.0 months. The 1-, 3-, and 5-year OS rates were 70.8%, 46.6%, and 34.0%, respectively, with the median OS of 28.0 months. Furthermore, univariate analyses showed that the recurrent T stage and histological grade were prognostic factors of LPFS, whereas only the histological grade was a predictor of OS. The major adverse events were skin/mucosal toxicities, which were generally of lower grade (#Grade 2) and were well tolerated. CONCLUSIONS: Radioactive 125 I seed implantation could be an effective and safe alternative treatment for locally recurrent HNSTS after failure of surgery and radiotherapy. Recurrent T stage and histological grade were the main factors influencing the efficacy.