Preoperative chemoradiotherapy for locally advanced low rectal cancer using intensity-modulated radiotherapy to spare the intestines: a single-institutional pilot trial

The irradiated volume of intestines is associated with gastrointestinal toxicity in preoperative chemoradiotherapy for rectal cancer. The current trial prospectively explored how much of the irradiated volume of intestines was reduced by intensity-modulated radiotherapy (IMRT) compared with 3-dimensional conformal radiotherapy (3DCRT) and whether IMRT might alleviate the acute gastrointestinal toxicity in this population. The treatment protocol encompassed preoperative chemoradiotherapy using IMRT plus surgery for patients with clinical T3–4, N0–2 low rectal cancer. IMRT delivered 45 Gy per 25 fractions for gross tumors, mesorectal and lateral lymph nodal regions, and tried to reduce the volume of intestines receiving 15 Gy (V₁₅ Gy) < 120 cc and V₄₅ Gy ≤ 0 cc, respectively, while keeping target coverage. S-1 and irinotecan were concurrently administered. Acute gastrointestinal toxicity, rates of clinical downstaging, sphincter preservation, local regional control (LRC) and overall survival (OS) were evaluated. Twelve enrolled patients completed the chemoradiotherapy protocol. The volumes of intestines receiving medium to high doses were reduced by the current IMRT protocol compared to 3DCRT; however, the predefined constraint of V15 Gy was met only in three patients. The rate of ≥ grade 2 gastrointestinal toxicity excluding anorectal symptoms was 17%. The rates of clinical downstaging, sphincter preservation, three-year LRC and OS were 75%, 92%, 92% and 92%, respectively. In conclusion, preoperative chemoradiotherapy using IMRT for this population might alleviate acute gastrointestinal toxicity, achieving high LRC and sphincter preservation; although further advancement is required to reduce the irradiated volume of intestines, especially those receiving low doses

Multi-institutional phase II study on the safety and efficacy of dynamic tumor tracking-stereotactic body radiotherapy for lung tumors

Background and purpose: This study aimed to evaluate the safety and efficacy of dynamic tumor tracking-stereotactic body radiotherapy (DTT-SBRT) for lung tumors. Materials and methods: Patients with cStage I primary lung cancer or metastatic lung cancer with an expected range of respiratory motion of ≥10 mm were eligible for the study. The prescribed dose was 50 Gy in four fractions. A gimbal-mounted linac was used for DTT-SBRT delivery. The primary endpoint was local control at 2 years. Results: Forty-eight patients from four institutions were enrolled in this study. Forty-two patients had primary non-small-cell lung cancer, and six had metastatic lung tumors. DTT-SBRT was delivered for 47 lesions in 47 patients with a median treatment time of 28 min per fraction. The median respiratory motion during the treatment was 13.7 mm (range: 4.5–28.1 mm). The motion-encompassing method was applied for the one remaining patient due to the poor correlation between the abdominal wall and tumor movement. The median follow-up period was 32.3 months, and the local control at 2 years was 95.2% (lower limit of the one-sided 85% confidence interval [CI]: 90.3%). The overall survival and progression-free survival at 2 years were 79.2% (95% CI: 64.7%–88.2%) and 75.0% (95% CI: 60.2%–85.0%), respectively. Grade 3 toxicity was observed in one patient (2.1%) with radiation pneumonitis. Grade 4 or 5 toxicity was not observed. Conclusion: DTT-SBRT achieved excellent local control with low incidences of severe toxicities in lung tumors with respiratory motion

Development of AI-driven prediction models to realize real-time tumor tracking during radiotherapy

[Background] In infrared reflective (IR) marker-based hybrid real-time tumor tracking (RTTT), the internal target position is predicted with the positions of IR markers attached on the patient’s body surface using a prediction model. In this work, we developed two artificial intelligence (AI)-driven prediction models to improve RTTT radiotherapy, namely, a convolutional neural network (CNN) and an adaptive neuro-fuzzy inference system (ANFIS) model. The models aim to improve the accuracy in predicting three-dimensional tumor motion. [Methods] From patients whose respiration-induced motion of the tumor, indicated by the fiducial markers, exceeded 8 mm, 1079 logfiles of IR marker-based hybrid RTTT (IR Tracking) with the gimbal-head radiotherapy system were acquired and randomly divided into two datasets. All the included patients were breathing freely with more than four external IR markers. The historical dataset for the CNN model contained 1003 logfiles, while the remaining 76 logfiles complemented the evaluation dataset. The logfiles recorded the external IR marker positions at a frequency of 60 Hz and fiducial markers as surrogates for the detected target positions every 80-640 ms for 20-40 s. For each logfile in the evaluation dataset, the prediction models were trained based on the data in the first three quarters of the recording period. In the last quarter, the performance of the patient-specific prediction models was tested and evaluated. The overall performance of the AI-driven prediction models was ranked by the percentage of predicted target position within 2 mm of the detected target position. Moreover, the performance of the AI-driven models was compared to a regression prediction model currently implemented in gimbal-head radiotherapy systems. [Results] The percentage of the predicted target position within 2 mm of the detected target position was 95.1%, 92.6% and 85.6% for the CNN, ANFIS, and regression model, respectively. In the evaluation dataset, the CNN, ANFIS, and regression model performed best in 43, 28 and 5 logfiles, respectively. [Conclusions] The proposed AI-driven prediction models outperformed the regression prediction model, and the overall performance of the CNN model was slightly better than that of the ANFIS model on the evaluation dataset

Reducing variability among treatment machines using knowledge‐based planning for head and neck, pancreatic, and rectal cancer

PURPOSE: This study aimed to assess dosimetric indices of RapidPlan model-based plans for different energies (6, 8, 10, and 15 MV; 6- and 10-MV flattening filter-free), multileaf collimator (MLC) types (Millennium 120, High Definition 120, dual-layer MLC), and disease sites (head and neck, pancreatic, and rectal cancer) and compare these parameters with those of clinical plans. METHODS: RapidPlan models in the Eclipse version 15.6 were used with the data of 28, 42, and 20 patients with head and neck, pancreatic, and rectal cancer, respectively. RapidPlan models of head and neck, pancreatic, and rectal cancer were created for TrueBeam STx (High Definition 120) with 6 MV, TrueBeam STx with 10-MV flattening filter-free, and Clinac iX (Millennium 120) with 15 MV, respectively. The models were used to create volumetric-modulated arc therapy plans for a 10-patient test dataset using all energy and MLC types at all disease sites. The Holm test was used to compare multiple dosimetric indices in different treatment machines and energy types. RESULTS: The dosimetric indices for planning target volume and organs at risk in RapidPlan model-based plans were comparable to those in the clinical plan. Furthermore, no dose difference was observed among the RapidPlan models. The variability among RapidPlan models was consistent regardless of the treatment machines, MLC types, and energy. CONCLUSIONS: Dosimetric indices of RapidPlan model-based plans appear to be comparable to the ones based on clinical plans regardless of energies, MLC types, and disease sites. The results suggest that the RapidPlan model can generate treatment plans independent of the type of treatment machine

Dosimetric Comparison between Dynamic Wave Arc and Co-Planar Volumetric Modulated Radiotherapy for Locally Advanced Pancreatic Cancer

Introduction: Dose reduction to the duodenum is important to decrease gastrointestinal toxicities in patients with locally advanced pancreatic cancer (LAPC) treated with definitive chemoradiotherapy. We aimed to compare dynamic wave arc (DWA), a volumetric-modulated beam delivery technique with simultaneous gantry/ring rotations passing the waved trajectories, with coplanar VMAT (co-VMAT) with respect to dose distributions in LAPC cases. Material and Methods: DWA and co-VMAT plans were created for 13 patients with LAPC. The prescribed dose was 45.6 or 48 Gy in 15 fractions. The dose volume indices (DVIs) for target volumes and organs at risk were compared between the corresponding plans. Gamma passing rate, monitor unit (MU), and beam-on time were also compared. Results: DWA significantly reduced the duodenal V39Gy, V42Gy, and V45Gy by 1.1, 0.8, and 0.2 cm3, and increased the liver mean dose and D2cm3 of the spinal cord planning volume by 1.0 and 1.5 Gy, respectively. Meanwhile, there was no significant difference in the target volumes except for D2% of PTV (111.5% in DWA vs. 110.5% in co-VMAT). Further, the gamma passing rate was similar in both plans. MU and beam-on time increased in DWA by 31 MUs and 15 seconds, respectively. Conclusion: DWA generated significantly lower duodenal doses in LAPC cases, albeit with slight increasing liver and spinal cord doses and increasing MU and the beam delivery time. Further evaluation is needed to know how the dose differences would affect the clinical outcomes in chemoradiotherapy for LAPC

四次元画像誘導放射線治療の開発: ジンバル機構に基づく動体追尾照射の精度検証

京都大学0048新制・課程博士博士(医学)甲第18139号医博第3859号新制||医||1002(附属図書館)30997京都大学大学院医学研究科医学専攻(主査)教授 武藤 学, 教授 武田 俊一, 教授 富樫 かおり学位規則第4条第1項該当Doctor of Medical ScienceKyoto UniversityDFA

Quality assurance of non-coplanar, volumetric-modulated arc therapy employing a C-arm linear accelerator, featuring continuous patient couch rotation

Purpose: To perform quality assurance of non-coplanar, volumetric-modulated arc therapy featuring continuous couch rotation (CCR-VMAT) using a C-arm linear accelerator. Methods: We planned and delivered CCR-VMAT using the TrueBeam Developer Mode. Treatment plans were created for both a C-shaped phantom and five prostate cancer patients using seven CCR trajectories that lacked collisions; we used RayStation software (ver. 4.7) to this end. Subsequently, verification plans were generated. The mean absolute error (MAE) between the center of an MV-imaged steel ball and the radiation field was calculated using the Winston–Lutz test. The MAEs between planned and actual irradiation values were also calculated from trajectory logs. In addition, correlation coefficients (r values) among the MAEs of gantry angle, couch angle, and multi-leaf collimator (MLC) position, and mechanical parameters including gantry speed, couch speed, MLC speed, and beam output, were estimated. The dosimetric accuracies of planned and measured values were also assessed using ArcCHECK. Results: The MAEs ±2 standard deviations as revealed by the Winston–Lutz test for all trajectories were 0.3 ± 0.3 mm in two dimensions. The MAEs of the gantry, couch, and MLC positions calculated from all trajectory logs were within 0.04°, 0.08°, and 0.02 mm, respectively. Deviations in the couch angle (r = 0.98, p < 0.05) and MLC position (r = 0.86, p < 0.05) increased significantly with speed. The MAE of the beam output error was less than 0.01 MU. The mean gamma passing rate ± 2 SD (range) of the 3%/3 mm, 3%/1 mm, and 5%/1 mm was 98.1 ± 1.9% (95.7–99.6%), 87.2 ± 2.8% (80.2–96.7%), and 96.3 ± 2.8% (93.9–99.6%), respectively. Conclusions: CCR-VMAT delivered via the TrueBeam Developer Mode was associated with high-level geometric and mechanical accuracy, thus affording to high dosimetric accuracy. The CCR-VMAT performance was stable regardless of the trajectory chosen

Investigation of 4D dose in volumetric modulated arc therapy-based stereotactic body radiation therapy: does fractional dose or number of arcs matter?

The aim of this study was to assess the impact of fractional dose and the number of arcs on interplay effects when volumetric modulated arc therapy (VMAT) is used to treat lung tumors with large respiratory motions. A three (fractional dose of 4, 7.5 or 12.5 Gy) by two (number of arcs, one or two) VMAT plan was created for 10 lung cancer cases. The median 3D tumor motion was 17.9 mm (range: 8.2–27.2 mm). Ten phase-specific subplans were generated by calculating the dose on each respiratory phase computed tomography (CT) scan using temporally assigned VMAT arcs. We performed temporal assignment of VMAT arcs using respiratory information obtained from infrared markers placed on the abdomens of the patients during CT simulations. Each phase-specific dose distribution was deformed onto exhale phase CT scans using contour-based deformable image registration, and a 4D plan was created by dose accumulation. The gross tumor volume dose of each 4D plan (4D GTV dose) was compared with the internal target volume dose of the original plan (3D ITV dose). The near-minimum 4D GTV dose (D99%) was higher than the near-minimum 3D internal target volume (ITV) dose, whereas the near-maximum 4D GTV dose (D1%) was lower than the near-maximum 3D ITV dose. However, the difference was negligible, and thus the 4D GTV dose corresponded well with the 3D ITV dose, regardless of the fractional dose and number of arcs. Therefore, interplay effects were negligible in VMAT-based stereotactic body radiation therapy for lung tumors with large respiratory motions

Baseline correction of a correlation model for improving the prediction accuracy of infrared marker-based dynamic tumor tracking

We previously found that the baseline drift of external and internal respiratory motion reduced the prediction accuracy of infrared (IR) marker-based dynamic tumor tracking irradiation (IR Tracking) using the Vero4DRT system. Here, we proposed a baseline correction method, applied immediately before beam delivery, to improve the prediction accuracy of IR Tracking. To perform IR Tracking, a four-dimensional (4D) model was constructed at the beginning of treatment to correlate the internal and external respiratory signals, and the model was expressed using a quadratic function involving the IR marker position (x) and its velocity (v), namely function F(x, v). First, the first 4D model, F1st(x, v), was adjusted by the baseline drift of IR markers (BDIR) along the x-axis, as function F′(x, v). Next, BDdetect, that defined as the difference between the target positions indicated by the implanted fiducial markers (Pdetect) and the predicted target positions with F′(x, v) (Ppredict) was determined using orthogonal kV X-ray images at the peaks of the Pdetect of the end-inhale and end-exhale phases for 10 s just before irradiation. F′(x, v) was corrected with BDdetect to compensate for the residual error. The final corrected 4D model was expressed as Fcor(x, v) = F1st{(x-BDIR), v}-BDdetect. We retrospectively applied this function to 53 paired log files of the 4D model for 12 lung cancer patients who underwent IR Tracking. The 95th percentile of the absolute differences between Pdetect and Ppredict (|Ep|) was compared between F1st(x, v) and Fcor(x, v). The median 95th percentile of |Ep| (units: mm) was 1.0, 1.7, and 3.5 for F1st(x, v), and 0.6, 1.1, and 2.1 for Fcor(x, v) in the left–right, anterior–posterior, and superior–inferior directions, respectively. Over all treatment sessions, the 95th percentile of |Ep| peaked at 3.2 mm using Fcor(x, v) compared with 8.4 mm using F1st(x, v). Our proposed method improved the prediction accuracy of IR Tracking by correcting the baseline drift immediately before irradiation

Long-term stability assessment of a 4D tumor tracking system integrated into a gimbaled linear accelerator

We assessed long-term stability of tracking accuracy using the Vero4DRT system. This metric was observed between September 2012 and March 2015. A programmable respiratory motion phantom, designed to move phantoms synchronously with respiratory surrogates, was used. The infrared (IR) markers moved in the anterior-posterior (AP) direction as respiratory surrogates, while a cube phantom with a steel ball at the center, representing the tumor, and with radiopaque markers around it moved in the superior-inferior (SI) direction with one-dimensional (1D) sinusoidal patterns. A correlation model between the tumor and IR marker motion (4D model) was created from the training data obtained for 20 s just before beam delivery. The irradiation field was set to 3× 3cm2 and 300 monitor units (MUs) of desired MV X-ray beam were delivered. The gantry and ring angles were set to 0o and 45o, respectively. During beam delivery, the system recorded approximately 60 electronic portal imaging device (EPID) images. We analyzed: 1) the predictive accuracy of the 4D model (EP), defined as the difference between the detected and predicted target positions during 4D model creation, and 2) the tracking accuracy (ET), defined as the difference between the center of the steel ball and the MV X-ray field on the EPID image. The median values of mean plus two standard deviations (SDs) for EP were 0.06, 0.35, and 0.06mm in the left-right (LR), SI, and AP directions, respectively. The mean values of maximum deviation for ET were 0.38, 0.49, and 0.53mm and the coefficients of variance (CV) were 0.16, 0.10, and 0.05 in lateral, longitudinal, and 2D directions, respectively. Consequently, the IR Tracking accuracy was consistent over a period of two years. Our proposed method assessed the overall tracking accuracy readily using real-time EPID images, and proved to be a useful QA tool for dynamic tumor tracking with the Vero4DRT system