Knowledge-based planning using pseudo-structures for volumetric modulated arc therapy (VMAT) of postoperative uterine cervical cancer: a multi-institutional study.

BACKGROUND: The aim of this study was to investigate the performance of the RapidPlan (RP ) using models registered pseudostructures, and to determine how many structures are required for automatic optimization of volumetric modulated arc therapy (VMAT) for postoperative uterine cervical cancer. MATERIALS AND METHODS: Pseudo-structures around the PTV were retrospectively contoured for patients who had completed treatment at five institutions. For 22 common patients, plans were generated with a single optimization for models with two (RP_2), four (RP_4), and five (RP_5) registered structures, and the dosimetric parameters of these models were compared with a clinical plan with several optimizations. RESULTS: Most dosimetric parameters showed no major differences between each RP model. In particular, the rectum Dmax, V50Gy, and V40Gy with RP_2, RP_4, and RP_5 were not significantly different, and were lower than those of the clinical plan. The average proportions of plans achieving acceptable criteria for dosimetric parameters were close to 100% for all models. Using RP_2, the average time for the VMAT planning was reduced by 88 minutes compared with the clinical plan. CONCLUSION: The RapidPlan model with two registered pseudo-structures could generate clinically acceptable plans while saving time.

Observer uncertainties of soft tissue-based patient positioning in IGRT.

PURPOSE: There remain uncertainties due to inter- and intraobserver variability in soft-tissue-based patient positioning even with the use of image-guided radiation therapy (IGRT). This study aimed to reveal observer uncertainties of soft-tissue-based patient positioning on cone-beam computed tomography (CBCT) images for prostate cancer IGRT. METHODS: Twenty-six patients (7-8 fractions/patient, total number of 204 fractions) who underwent IGRT for prostate cancer were selected. Six radiation therapists retrospectively measured prostate cancer location errors (PCLEs) of soft-tissue-based patient positioning between planning CT (pCT) and pretreatment CBCT (pre-CBCT) images after automatic bone-based registration. Observer uncertainties were evaluated based on residual errors, which denoted the differences between soft-tissue and reference positioning errors. Reference positioning errors were obtained as PCLEs of contour-based patient positioning between pCT and pre-CBCT images. Intraobserver variations were obtained from the difference between the first and second soft-tissue-based patient positioning repeated by the same observer for each fraction. Systematic and random errors of inter- and intraobserver variations were calculated in anterior-posterior (AP), superior-inferior (SI), and left-right (LR) directions. Finally, clinical target volume (CTV)-to-planning target volume (PTV) margins were obtained from systematic and random errors of inter- and intraobserver variations in AP, SI, and LR directions. RESULTS: Interobserver variations in AP, SI, and LR directions were 0.9, 0.9, and 0.5 mm, respectively, for the systematic error, and 1.8, 2.2, and 1.1 mm, respectively, for random error. Intraobserver variations were <0.2 mm in all directions. CTV-to-PTV margins in AP, SI, and LR directions were 3.5, 3.8, and 2.1 mm, respectively. CONCLUSION: Intraobserver variability was sufficiently small and would be negligible. However, uncertainties due to interobserver variability for soft-tissue-based patient positioning using CBCT images should be considered in CTV-to-PTV margins.

Characterization of knowledge-based volumetric modulated arc therapy plans created by three different institutions' models for prostate cancer.

BACKGROUND: The aim of this study was to clarify factors predicting the performance of knowledge-based planning (KBP) models in volume modulated arc therapy for prostate cancer in terms of sparing the organ at risk (OAR). MATERIALS AND METHODS: In three institutions, each KBP model was trained by more than 20 library plans (LP) per model. To validate the characterization of each KBP model, 45 validation plans (VP) were calculated by the KBP system. The ratios of overlap between the OAR volume and the planning target volume (PTV) to the whole organ volume (Voverlap/Vwhole) were analyzed for each LP and VP. Regression lines between dose-volume parameters (V90, V75, and V50) and Voverlap/Vwhole were evaluated. The mean OAR dose, V90, V75, and V50 of LP did not necessarily match those of VP. RESULTS: In both the rectum and bladder, the dose-volume parameters for VP were strongly correlated with Voverlap/Vwhole at institutes A, B, and C (R > 0.74, 0.85, and 0.56, respectively). Except in the rectum at institute B, the slopes of the regression lines for LP corresponded to those for VP. For dose-volume parameters for the rectum, the ratios of slopes of the regression lines in VP to those in LP ranged 0.51-1.26. In the bladder, most ratios were less than 1.0 (mean: 0.77). CONCLUSION: For each OAR, each model made distinct dosimetric characterizations in terms of Voverlap/Vwhole. The relationship between dose-volume parameters and Voverlap/Vwhole of OARs in LP predicts the KBP models' performance sparing OARs.

[Evaluation of a 2D Diode Array Corresponding to Flattening Filter Free X-ray Beams].

Recently, a medical linear accelerator with a flattening filter free (FFF) mode has led to the use of FFF X-ray beams at clinical sites. The usefulness of FFF X-ray beams in high-precision radiation therapy has been reported. Therefore, the quality assurance and quality control for FFF X-ray beams have become necessary. In this study, the characteristics of the detectors of a newly developed 2-D diode array (MapCHECK2, Sun Nuclear Corporation) for FFF X-ray beams, i.e., dose reproducibility, dose rate dependence, dose linearity, and output factor, were evaluated. For the measurements, 6 and 10 MV FFF beams were used. The results showed that the coefficient of variation for dose reproducibility was within 0.08%, the dose rate dependence was less than 1.0%, the coefficient of determination of dose linearity was found to be R2=1.0, which was high, and the output factor agreed within 2.5% as compared with the farmer ion chamber, diode E, and pinpoint ion chamber for field sizes greater than 2×2 cm2. The results suggested that MapCHECK2 could be a useful tool for quality assurance and quality control for FFF X-ray beams.

Evaluation of PTV margin in CBCT-based online adaptive radiation therapy for gastric mucosa-associated lymphoid tissue lymphoma.

The aim of this study was to investigate planning target volume (PTV) margin in online adaptive radiation therapy (oART) for gastric mucosa-associated lymphoid tissue (MALT) lymphomas. Four consecutive patients with gastric MALT lymphoma who received oART (30 Gy in 15 fractions) on the oART system were included in this study. One hundred and twenty cone-beam computed tomography (CBCT) scans acquired pre- and post-treatment of 60 fractions for all patients were used to evaluate intra- and interfractional motions. Patients were instructed on breath-holding at exhalation during image acquisition. To assess the intrafraction gastric motion, different PTVs were created by isotropically extending the CTV contoured on a pre-CBCT image (CTVpre) at1 mm intervals. Intrafraction motion was defined as the amount of expansion covering the contoured CTV on post-CBCT images (CTVpost). Interfractional motion was defined as the amount of reference CTV expansion that could cover each CTVpre, as well as the evaluation of the intrafractional motion. PTV margins were estimated from the cumulative proportion of fraction covering the intra- and interfractional motions. The extent of expansion covering the CTVs in 90% of fractions was adopted as the PTV margin. The PTV margin for intrafractional gastric motion using the oART system with breath-holding was 14 mm. In contrast, the PTV margin for interfractional gastric organ motion without the oART system was 25 mm. These results indicated that the oART system can reduce the PTV margin by >10 mm. Our results could be valuable data for oART cases.

Deep Learning-based Lung dose Prediction Using Chest X-ray Images in Non-small Cell Lung Cancer Radiotherapy.

Purpose: This study aimed to develop a deep learning model for the prediction of V20 (the volume of the lung parenchyma that received ≥20 Gy) during intensity-modulated radiation therapy using chest X-ray images. Methods: The study utilized 91 chest X-ray images of patients with lung cancer acquired routinely during the admission workup. The prescription dose for the planning target volume was 60 Gy in 30 fractions. A convolutional neural network-based regression model was developed to predict V20. To evaluate model performance, the coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE) were calculated with conducting a four-fold cross-validation method. The patient characteristics of the eligible data were treatment period (2018-2022) and V20 (19.3%; 4.9%-30.7%). Results: The predictive results of the developed model for V20 were 0.16, 5.4%, and 4.5% for the R2, RMSE, and MAE, respectively. The median error was -1.8% (range, -13.0% to 9.2%). The Pearson correlation coefficient between the calculated and predicted V20 values was 0.40. As a binary classifier with V20 <20%, the model showed a sensitivity of 75.0%, specificity of 82.6%, diagnostic accuracy of 80.6%, and area under the receiver operator characteristic curve of 0.79. Conclusions: The proposed deep learning chest X-ray model can predict V20 and play an important role in the early determination of patient treatment strategies.

Standardization of knowledge-based volumetric modulated arc therapy planning with a multi-institution model (broad model) to improve prostate cancer treatment quality.

PURPOSE: To evaluate whether knowledge-based volumetric modulated arc therapy plans for prostate cancer with a multi-institution model (broad model) are clinically useful and effective as a standardization method. METHODS: A knowledge-based planning (KBP) model was trained with 561 prostate VMAT plans from five institutions with different contouring and planning policies. Five clinical plans at each institution were reoptimized with the broad and single institution model, and the dosimetric parameters and relationship between Dmean and the overlapping volume (rectum or bladder and target) were compared. RESULTS: The differences between the broad and single institution models in the dosimetric parameters for V50, V80, V90, and Dmean were: rectum; 9.5% ± 10.3%, 3.3% ± 1.5%, 1.7% ± 1.6%, and 3.6% ± 3.6%, (p < 0.001), bladder; 8.7% ± 12.8%, 1.5% ± 2.6%, 0.7% ± 2.4%, and 2.7% ± 4.6% (p < 0.02), respectively. The differences between the broad model and clinical plans were: rectum; 2.4% ± 4.6%, 1.7% ± 1.7%, 0.7% ± 2.4%, and 1.5% ± 2.0%, (p = 0.004, 0.015, 0.112, and 0.009) bladder; 2.9% ± 5.8%, 1.6% ± 1.9%, 0.9% ± 1.7%, and 1.1% ± 4.8%, (p < 0.018), respectively. Positive values indicate that the broad model has a lower value. Strong correlations were observed (p < 0.001) in the relationship between Dmean and the rectal and bladder volume overlapping with the target in the broad model (R = 0.815 and 0.891, respectively). The broad model had the smallest R2 of the three plans. CONCLUSIONS: KBP with the broad model is clinically effective and applicable as a standardization method at multiple institutions.

Investigation of uncertainty in internal target volume definition for lung stereotactic body radiotherapy.

This study evaluated the validity of internal target volumes (ITVs) defined by three- (3DCT) and four-dimensional computed tomography (4DCT), and subsequently compared them with actual movements during treatment. Five patients with upper lobe lung tumors were treated with stereotactic body radiotherapy (SBRT) at 48 Gy in four fractions. Planning 3DCT images were acquired with peak-exhale and peak-inhale breath-holds, and 4DCT images were acquired in the cine mode under free breathing. Cine images were acquired using an electronic portal imaging device during irradiation. Tumor coverage was evaluated based on the manner in which the peak-to-peak breathing amplitude on the planning CT covered the range of tumor motion (± 3 SD) during irradiation in the left-right, anteroposterior, and cranio-caudal (CC) directions. The mean tumor coverage of the 4DCT-based ITV was better than that of the 3DCT-based ITV in the CC direction. The internal margin should be considered when setting the irradiation field for 4DCT. The proposed 4DCT-based ITV can be used as an efficient approach in free-breathing SBRT for upper-lobe tumors of the lung because its coverage is superior to that of 3DCT.

[Dosimetric Properties of Brass Mesh Bolus for High-energy Photon Beam].

PURPOSE: To investigate fundamental dosimetric properties of surface dose, exit dose, and beam profile of the brass mesh bolus for 4, 6, and 10 MV high-energy photon beams in radiation therapy. METHODS: Surface dose and exit dose in the water-equivalent phantom were measured, and percent depth doses (PDDs) were calculated with no bolus, one layer of brass mesh, two layers of brass mesh bolus, three layers of brass mesh bolus, and 0.5 cm tissue-equivalent (TE) bolus. Exit dose was measured at a phantom thickness of 10 cm. Beam profiles were measured at phantom depths of 0 cm and 10 cm. All dosimetry was performed for 4, 6, and 10 MV photon beams using a linear accelerator. RESULTS: The surface dose at a phantom depth of 0 cm increased to 37.3%, 36.3%, and 31.0% for 4, 6, and 10 MV, respectively, with the brass mesh bolus compared to the case of no bolus. The surface dose decreased with one layer of brass mesh bolus compared to that with the 0.5 cm TE bolus. On the other hand, the exit dose increased to 22.0%, 23.1%, and 22.8% for 4, 6, and 10 MV, respectively, with the brass mesh bolus compared to the case of no bolus. The beam profile at the depth of 0 cm showed oscillations, and the difference between the maximum and minimum doses was up to 13.1% with one layer of brass mesh bolus. CONCLUSION: It was suggested that the brass mesh bolus not only increases the surface dose but also has different properties from the conventional TE bolus.

Difference in target dose distributions between Acuros XB and collapsed cone convolution/superposition and the impact of the tumor locations in clinical cases of stereotactic ablative body radiotherapy for lung cancer.

Objectives: The objective of the study is to analyze the difference in target dose distributions between Acuros XB (AXB) and collapsed cone convolution (CCC)/superposition and the impact of the tumor locations in clinical cases of stereotactic ablative body radiotherapy (SABR) for lung cancer. Materials and Methods: Ninety-six patients underwent SABR for lung cancers Kyushu University Hospital from 2014 to 2017. We recalculated clinical plans originally calculated by AXB using CCC with the identical monitor units (MUs) and beam arrangements. We calculated the following dosimetric parameters: maximum dose (Dmax), minimum dose (Dmin), homogeneity index (HI), conformity index (CI), and D95 of the planning target volume (PTV). We investigated the difference between the results of two calculations and examined the impact of tumor location. Moreover, we determined the target central dose using a thorax phantom and assessed the calculation accuracy of the two algorithms for each fraction. Results: CCC significantly overestimated the dose to PTV, compared to AXB (P < 0.05). The mean differences of Dmax, Dmin, and D95 were 1.17, 1.95, and 1.85 Gy, respectively. The mean differences of HI and CI were 0.02 and - 0.06. Dmin, HI, and D95 had significant correlations with the tumor location, and the difference was greater when the PTV was included the chest wall (P < 0.05). The discrepancy between the calculated and irradiated dose was 2.48% for CCC, whereas it was 0.14% for AXB. Conclusions: We demonstrated that CCC significantly overestimated the dose to PTV relative to AXB in clinical cases of lung SABR.

Impact of Knowledge-based Plan Model Improvement on Plan Complexity and Deliverability in VMAT For Prostate Cancer: A Multi-institutional Study.

BACKGROUND/AIM: This study evaluated the impact of knowledge-based plan (KBP) model improvement on plan complexity and delivery accuracy in volumetric modulated arc therapy (VMAT) for prostate cancer at multiple institutions. MATERIALS AND METHODS: Five institutions created the first KBP model before April 2017 and subsequently devised a new model (second model) based on feedback from the first KBP and the efforts of planners after April 2019. The dose-volume histogram (DVH) parameters were validated for two prostate cancer cases between the first and second KBPs. Plan complexity metrics, of the modulation complexity score for VMAT (MCSv), closed leaf score (CLS), small aperture score (SAS), and leaf travel (LT), were compared. The delivery accuracy metrics of γ pass rate and point dose discrepancy (plan vs. measurement) at isocenter were also compared. RESULTS: There were no significant differences in DVH parameters between the KBPs. Conversely, V50% of the rectum and bladder was reduced in 6/10 and 8/10 patients, respectively, and these variations were also converged from the first KBP to the second KBP. The mean±1SDs of MCSv, CLS, SAS20mm, and LT (first KBP vs. second KBP) were 0.27±0.033 vs. 0.26±0.044, 0.062±0.032 vs. 0.14±0.091, 0.59±0.048 vs. 0.70±0.14, and 411.91±32.08 mm vs. 548.33±127.50 mm, respectively. The delivery accuracy did not differ, whereas MCSv was moderately correlated with the point dose discrepancy. CONCLUSION: Multi-leaf collimator motion could be more complex with KBP model improvement, which had the potential to deteriorate the delivery accuracy.

Multi-institution model (big model) versus single-institution model of knowledge-based volumetric modulated arc therapy (VMAT) planning for prostate cancer.

We established a multi-institution model (big model) of knowledge-based treatment planning with over 500 treatment plans from five institutions in volumetric modulated arc therapy (VMAT) for prostate cancer. This study aimed to clarify the efficacy of using a large number of registered treatment plans for sharing the big model. The big model was created with 561 clinically approved VMAT plans for prostate cancer from five institutions (A: 150, B: 153, C: 49, D: 60, and E: 149) with different planning strategies. The dosimetric parameters of planning target volume (PTV), rectum, and bladder for two validation VMAT plans generated with the big model were compared with those from each institutional model (single-institution model). The goodness-of-fit of regression lines (R2 and χ2 values) and ratios of the outliers of Cook's distance (CD) > 4.0, modified Z-score (mZ) > 3.5, studentized residual (SR) > 3.0, and areal difference of estimate (dA) > 3.0 for regression scatter plots in the big model and single-institution model were also evaluated. The mean ± standard deviation (SD) of dosimetric parameters were as follows (big model vs. single-institution model): 79.0 ± 1.6 vs. 78.7 ± 0.5 (D50) and 0.13 ± 0.06 vs. 0.13 ± 0.07 (Homogeneity Index) for the PTV; 6.6 ± 4.0 vs. 8.4 ± 3.6 (V90) and 32.4 ± 3.8 vs. 46.6 ± 15.4 (V50) for the rectum; and 13.8 ± 1.8 vs. 13.3 ± 4.3 (V90) and 39.9 ± 2.0 vs. 38.4 ± 5.2 (V50) for the bladder. The R2 values in the big model were 0.251 and 0.755 for rectum and bladder, respectively, which were comparable to those from each institution model. The respective χ2 values in the big model were 1.009 and 1.002, which were closer to 1.0 than those from each institution model. The ratios of the outliers in the big model were also comparable to those from each institution model. The big model could generate a comparable VMAT plan quality compared with each single-institution model and therefore could possibly be shared with other institutions.

Radiomic prediction of radiation pneumonitis on pretreatment planning computed tomography images prior to lung cancer stereotactic body radiation therapy.

This study developed a radiomics-based predictive model for radiation-induced pneumonitis (RP) after lung cancer stereotactic body radiation therapy (SBRT) on pretreatment planning computed tomography (CT) images. For the RP prediction models, 275 non-small-cell lung cancer patients consisted of 245 training (22 with grade ≥ 2 RP) and 30 test cases (8 with grade ≥ 2 RP) were selected. A total of 486 radiomic features were calculated to quantify the RP texture patterns reflecting radiation-induced tissue reaction within lung volumes irradiated with more than x Gy, which were defined as LVx. Ten subsets consisting of all 22 RP cases and 22 or 23 randomly selected non-RP cases were created from the imbalanced dataset of 245 training patients. For each subset, signatures were constructed, and predictive models were built using the least absolute shrinkage and selection operator logistic regression. An ensemble averaging model was built by averaging the RP probabilities of the 10 models. The best model areas under the receiver operating characteristic curves (AUCs) calculated on the training and test cohort for LV5 were 0.871 and 0.756, respectively. The radiomic features calculated on pretreatment planning CT images could be predictive imaging biomarkers for RP after lung cancer SBRT.

Dosimetric evaluation with knowledge-based planning created at different periods in volumetric-modulated arc therapy for prostate cancer: a multi-institution study.

Dosimetric evaluation and variation assessment were performed with two knowledge-based planning (KBP) models created at different periods for volumetric-modulated arc therapy (VMAT) for prostate cancer at five institutes. The first and second models (F- and S-models) for KBP were created before April 2017 and April 2019, respectively. The S-model was created using feedback plans from the F-model. Dose evaluation was compared between the two models using the same two computed tomography (CT) datasets and structures. The evaluation metrics were the dose received by 95.0% and 2.0% of the planning target volume (PTV); dose-volume parameters to the rectum and bladder as V90, V80, and V50; and monitor unit (MU). Dosimetric variation was compared by exporting estimated dose-volume histograms for each model to the Model Analytics website and assessing the organ at risk volume. There were no dosimetric differences between the two models for PTV. The V50 of the rectum in the S-model had improved compared to that of the F-model (case I: 49.3 ± 15.6 and 43.5 ± 15.2 [p = 0.08]; case II: 42.5 ± 16.9 and 36.0 ± 15.6 [p = 0.138]). The differences in other parameters were within ± 1.8% between the rectum and the bladder. The MU was slightly higher in the S-model than in the F-model, and dosimetric variation was reduced to the rectum and bladder among all the institutes. The polished S-model for KBP could be used for standardization of the plan quality and sharing of KBP models in VMAT for prostate cancer.

Assessment of the anatomical position of point B and the relationship between point B dose and the dose delivered to pelvic lymph nodes in CT-based high-dose-rate brachytherapy for uterine cervical cancer.

PURPOSE: To examine the anatomical position of point B and the relationship between the dose at point B and the dose delivered to the pelvic lymph nodes in computed tomography (CT)-based brachytherapy for cervical cancer. MATERIAL AND METHODS: Forty-nine cervical cancer patients were treated at Kyushu University Hospital. For all cases, planning CT images obtained after the applicator insertion were imported to an Oncentra Brachy (Elekta AB, Stockholm, Sweden), and points A (dose prescription, 6 Gy) and points B were set according to the Manchester method. The pelvic lymph node regions (external iliac, internal iliac, and obturator) were contoured, and the anatomic positions of 98 points B in 49 patients were examined. Dose volume histogram (DVH) parameters (D100, D90, D50, D2cc, D1cc, and D0.1cc) were calculated for each lymph node region and compared with the point B dose. RESULTS: The mean bilateral dose to point B was 1.70 ±0.18 Gy, and 26 (27%) of 98 points B were not located in any pelvic lymph node regions. The DVH analysis indicated a low degree of correlation overall, and all values were significantly different from point B doses (p < 0.05), except for D0.1cc of the external iliac node (p = 0.0594) and D1cc of the internal iliac node (p = 0.0711). CONCLUSIONS: We investigated the anatomical location of point B in patients with cervical cancer who underwent brachytherapy, and the DVH analysis revealed that the point B dose was a poor surrogate for the dose delivered to the pelvic lymph nodes.

Multi-institutional evaluation of knowledge-based planning performance of volumetric modulated arc therapy (VMAT) for head and neck cancer.

PURPOSE: The aim of this study was to investigate whether additional manual objectives are necessary for the RapidPlan (RP) with a single optimization. We conducted multi-institutional comparisons of plan quality for head and neck cancer (HNC) using the models created at each institute. METHODS: The ability of RP to produce acceptable plans for dose requirements was evaluated in two types of oropharynx cancers at five institutes in Japan. Volumetric modulated arc therapy plans created without (RP plan) and with additional manual objectives (M-RP plan) were compared in terms of planning target volume (PTV), brainstem, spinal cord and parotid glands in dosimetric parameters. RESULTS: There were no major dosimetric PTV differences between RP and M-RP plans. For the brainstem and spinal cord in the RP plans, only 40% and 30% of the plans achieved the dose requirements, while the M-RP plans with upper objective added to volume 0% at all institutes achieved them for 90% of the plans. For the L-parotid gland, there was no difference in the RP and M-RP plans (both were 40%) in achieving the acceptable criteria. For the R-parotid gland, 60% and 80% of the RP and M-RP plans achieved the constraint criteria, and in terms of the achievement rate, the RP plans were relatively high. CONCLUSIONS: M-RP plans did not require reoptimization; only an upper objective was needed for the brainstem and spinal cord, while the parotid gland dose was reduced in both RP plans with the auto generated line objectives alone.

Comparison of volumetric-modulated arc therapy and intensity-modulated radiation therapy prostate cancer plans accounting for cold spots.

This study compared dosimetric indices of volumetric-modulated arc therapy (VMAT) with intensity-modulated radiation therapy (IMRT) accounting for cold spots in prostate cancer plans. IMRT plans were retrospectively generated from 30 prostate cancer patients with ten cases for each risk group, who received VMAT plans. The mean, maximum, and minimum doses, and conformity and homogeneity indexes were evaluated for planning target volume (PTV) and the mean dose and V20-V70 for organs at risk (OAR) including the rectum, bladder, right and left femoral heads, and rectum overlapped with PTV (ROP) regions. The numbers and volume percentages of cold spots within PTVs and ROP regions were measured using in-house software. Three-dimensional probabilistic distributions of the probability and distributions of cold spots were generated using a centroid matching technique for visualization and analysis. There was a statistically better dose conformity in the PTV, rectum, and bladder dose-sparing in VMAT compared to that in the IMRT plans, whereas VMAT had statistically worse target dose homogeneity, and right and left femoral head dose-sparing than those of the IMRT plans. The average volume percentage of cold spots per PTV for the VMAT was 4.37 ± 2.68%, which was smaller than the 5.72 ± 1.84% observed for IMRT plans (P = 0.007). The volume percentage of cold spots per ROP for the VMAT did not significantly differ from those for the IMRT plans. Compared with IMRT, the VMAT plans achieved better PTV dose conformity, OAR dose-sparing, and smaller cold spots in the treatment of prostate cancer.

A base pair at the bottom of the anticodon stem is reciprocally preferred for discrimination of cognate tRNAs by Escherichia coli lysyl- and glutaminyl-tRNA synthetases.

Although the yeast amber suppressor tRNA(Tyr) is a good candidate for a carrier of unnatural amino acids into proteins, slight misacylation with lysine was found to occur in an Escherichia coli protein synthesis system. Although it was possible to restrain the mislysylation by genetically engineering the anticodon stem region of the amber suppressor tRNA(Tyr), the mutant tRNA showing the lowest acceptance of lysine was found to accept a trace level of glutamine instead. Moreover, the glutamine-acceptance of various tRNA(Tyr) transcripts substituted at the anticodon stem region varied in reverse proportion to the lysine-acceptance, similar to a 'seesaw'. The introduction of a C31-G39 base pair at the site was most effective for decreasing the lysine-acceptance and increasing the glutamine-acceptance. When the same substitution was introduced into E.coli tRNA(Lys) transcripts, the lysine-accepting activity was decreased by 100-fold and faint acceptance of glutamine was observed. These results may support the idea that there are some structural element(s) in the anticodon stem of tRNA, which are not shared by aminoacyl-tRNA synthetases that have similar recognition sites in the anticodon, such as E.coli lysyl- and glutaminyl-tRNA synthetases.

Effect of accounting for interfractional CTV shape variations in PTV margins on prostate cancer radiation treatment plans.

PURPOSE: The aim of this study was to account for interfractional clinical target volume (CTV) shape variation and apply this to the planning target volume (PTV) margin for prostate cancer radiation treatment plans. METHODS: Interfractional CTV shape variations were estimated from weekly cone-beam computed tomography (CBCT) images using statistical point distribution models. The interfractional CTV shape variation was taken into account in the van Herk's margin formula. The PTV margins without and with the CTV shape variation, i.e., standard (PTVori) and new (PTVshape) margins, were applied to 10 clinical cases that had weekly CBCT images acquired during their treatment sessions. Each patient was replanned for low-, intermediate-, and high-risk CTVs, using both margins. The dose indices (D98 and V70) of treatment plans with the two margins were compared on weekly pseudo-planning computed tomography (PCT) images, which were defined as PCT images registered using a deformable image registration technique with weekly CBCT images, including contours of the CTV, rectum, and bladder. RESULTS: The percentage of treatment fractions of patients who received CTV D98 greater than 95% of a prescribed dose increased from 80.3 (PTVori) to 81.8% (PTVshape) for low-risk CTVs, 78.8 (PTVori) to 87.9% (PTVshape) for intermediate-risk CTVs, and 80.3 (PTVori) to 87.9% (PTVshape) for high-risk CTVs. In most cases, the dose indices of the rectum and bladder were acceptable in clinical practice. CONCLUSION: The results of this study suggest that interfractional CTV shape variations should be taken into account when determining PTV margins to increase CTV coverages.

Evaluation of multiple institutions' models for knowledge-based planning of volumetric modulated arc therapy (VMAT) for prostate cancer.

BACKGROUND: The aim of this study was to evaluate the performance of a commercial knowledge-based planning system, in volumetric modulated arc therapy for prostate cancer at multiple radiation therapy departments. METHODS: In each institute, > 20 cases were assessed. For the knowledge-based planning, the estimated dose (ED) based on geometric and dosimetric information of plans was generated in the model. Lower and upper limits of estimated dose were saved as dose volume histograms for each organ at risk. To verify whether the models performed correctly, KBP was compared with manual optimization planning in two cases. The relationships between the EDs in the models and the ratio of the OAR volumes overlapping volume with PTV to the whole organ volume (Voverlap/Vwhole) were investigated. RESULTS: There were no significant dosimetric differences in OARs and PTV between manual optimization planning and knowledge-based planning. In knowledge-based planning, the difference in the volume ratio of receiving 90% and 50% of the prescribed dose (V90 and V50) between institutes were more than 5.0% and 10.0%, respectively. The calculated doses with knowledge-based planning were between the upper and lower limits of ED or slightly under the lower limit of ED. The relationships between the lower limit of ED and Voverlap/Vwhole were different among the models. In the V90 and V50 for the rectum, the maximum differences between the lower limit of ED among institutes were 8.2% and 53.5% when Voverlap/Vwhole for the rectum was 10%. In the V90 and V50 for the bladder, the maximum differences of the lower limit of ED among institutes were 15.1% and 33.1% when Voverlap/Vwhole for the bladder was 10%. CONCLUSION: Organs' upper and lower limits of ED in the models correlated closely with the Voverlap/Vwhole. It is important to determine whether the models in KBP match a different institute's plan design before the models can be shared.