Optimization of a newly defined target volume in fiducial marker-based dynamic tumor-tracking radiotherapy

Demonstration of real-time positron emission tomography biology-guided radiotherapy delivery to targets

BACKGROUND

Biology-guided radiotherapy (BgRT) is a novel technology that uses positron emission tomography (PET) data to direct radiotherapy delivery in real-time. BgRT enables the precise delivery of radiation doses based on the PET signals emanating from PET-avid tumors on the fly. In this way, BgRT uniquely utilizes radiotracer uptake as a biological beacon for controlling and adjusting dose delivery in real-time to account for target motion.

PURPOSE

To demonstrate using real-time PET for BgRT delivery on the RefleXion X1 radiotherapy machine. The X1 radiotherapy machine is a rotating ring-gantry radiotherapy system that generates a nominal 6MV photon beam, PET, and computed tomography (CT) components. The system utilizes emitted photons from PET-avid targets to deliver effective radiation beamlets or pulses to the tumor in real-time.

METHODS

This study demonstrated a real-time PET BgRT delivery experiment under three scenarios. These scenarios included BgRT delivering to (S1) a static target in a homogeneous and heterogeneous environment, (S2) a static target with a hot avoidance structure and partial PET-avid target, and (S3) a moving target. The first step was to create stereotactic body radiotherapy (SBRT) and BgRT plans (offline PET data supported) using RefleXion's custom-built treatment planning system (TPS). Additionally, to create a BgRT plan using PET-guided delivery, the targets were filled with 18F-Fluorodeoxyglucose (FDG), which represents a tumor/target, that is, PET-avid. The background materials were created in the insert with homogeneous water medium (for S1) and heterogeneous water with styrofoam mesh medium. A heterogeneous background medium simulated soft tissue surrounding the tumor. The treatment plan was then delivered to the experimental setups using a pre-commercial version of the X1 machine. As a final step, the dosimetric accuracy for S1 and S2 was assessed using the ArcCheck analysis tool-the gamma criteria of 3%/3 mm. For S3, the delivery dose was quantified using EBT-XD radiochromic film. The accuracy criteria were based on coverage, where 100% of the clinical target volume (CTV) receives at least 97% of the prescription dose, and the maximum dose in the CTV was ≤130% of the maximum planned dose (97 % ≤ CTV ≤ 130%).

RESULTS

For the S1, both SBRT and BgRT deliveries had gamma pass rates greater than 95% (SBRT range: 96.9%-100%, BgRT range: 95.2%-98.9%), while in S2, the gamma pass rate was 98% for SBRT and between 95.2% and 98.9% for BgRT plan delivering. For S3, both SBRT and BgRT motion deliveries met CTV dose coverage requirements, with BgRT plans delivering a very high dose to the target. The CTV dose ranges were (a) SBRT:100.4%-120.4%, and (b) BgRT: 121.3%-139.9%.

CONCLUSIONS

This phantom-based study demonstrated that PET signals from PET-avid tumors can be utilized to direct real-time dose delivery to the tumor accurately, which is comparable to the dosimetric accuracy of SBRT. Furthermore, BgRT delivered a PET-signal controlled dose to the moving target, equivalent to the dose distribution to the static target. A future study will compare the performance of BgRT with conventional image-guided radiotherapy.

Dynamic tumor-tracking stereotactic body radiotherapy with real-time monitoring of liver tumors using a gimbal-mounted linac: A multi-institutional phase II study

Background and purpose

This prospective multicenter phase II study aimed to evaluate the safety and efficacy of dynamic tumor tracking (DTT) stereotactic body radiotherapy (SBRT) with real-time monitoring of liver tumors using a gimbal-mounted system.

Materials and methods

Patients with < 4 primary or metastatic liver tumors with diameters ≤ 50 mm and expected to have a respiratory motion of ≥ 10 mm were eligible. The prescribed dose was 40 Gy in five fractions. The primary endpoint was local control (LC) at 2 years. The secondary endpoints were overall survival (OS), progression-free survival (PFS), treatment-related toxicity, and tracking accuracy.

Results

Between September 2015 and March 2019, 48 patients (48 lesions) with a median age of 74 years were enrolled from four institutions. Of these, 39 were diagnosed with hepatocellular carcinoma and nine with metastatic liver cancer. The median tumor diameter was 17.5 mm. DTT-SBRT was successfully performed in all patients; the median treatment time was 28 min/fraction. The median follow-up period was 36.5 months. The 2-year LC, OS, and PFS rates were 98.0 %, 88.8 %, and 55.1 %, respectively. Disease progression was observed in 33 (68.8 %) patients. One patient (0.2 %) had local recurrence, 31 (64.6 %) developed new hepatic lesions outside the irradiation field, and nine (18.8 %) had distant metastases (including overlap). Grade 3 late adverse events were observed in seven patients (14.5 %). No grade 4 or 5 treatment-related toxicity was observed. The median tracking accuracy was 2.9 mm.

Conclusion

Employing DTT-SBRT to treat liver tumors results in excellent LC with acceptable adverse-event incidence.

Patient-specific respiratory motion management using lung tumors vs fiducial markers for real-time tumor-tracking stereotactic body radiotherapy

Background and purpose

In real-time lung tumor-tracking stereotactic body radiotherapy (SBRT), tracking accuracy is related to radiotherapy efficacy. This study aimed to evaluate the respiratory movement relationship between a lung tumor and a fiducial marker position in each direction using four-dimensional (4D) computed tomography (CT) images.

Materials and methods

A series of 31 patients with a fiducial marker for lung SBRT was retrospectively analyzed using 4DCT. In the upper (UG) and middle and lower lobe groups (MLG), the cross-correlation coefficients of respiratory movement between the lung tumor and fiducial marker position in four directions (anterior-posterior, left-right, superior-inferior [SI], and three-dimensional [3D]) were calculated for each gating window (≤1, ≤2, and ≤ 3 mm). Subsequently, the proportions of phase numbers in unplanned irradiation (with lung tumors outside the gating window and fiducial markers inside the gating window) were calculated for each gating window.

Results

In the SI and 3D directions, the cross-correlation coefficients were significantly different between UG (mean r = 0.59, 0.63, respectively) and MLG (mean r = 0.95, 0.97, respectively). In both the groups, the proportions of phase numbers in unplanned irradiation were 11 %, 28 %, and 63 % for the ≤ 1-, ≤2-, and ≤ 3-mm gating windows, respectively.

Conclusions

Compared with MLG, fiducial markers for UG have low cross-correlation coefficients between the lung tumor and the fiducial marker position. Using 4DCT to assess the risk of unplanned irradiation in a gating window setting and selecting a high cross-correlation coefficient fiducial marker in advance are important for accurate treatment using lung SBRT.

Quantification of the geometric uncertainty when using implanted markers as a surrogate for lung tumor motion

BACKGROUND

Fiducial markers are used as surrogates for tumor location during radiation therapy treatment. Developments in lung fiducial marker and implantation technology have provided a means to insert markers endobronchially for tracking of lung tumors. This study quantifies the surrogacy uncertainty (SU) when using endobronchially implanted markers as a surrogate for lung tumor position.

METHODS

We evaluated SU for 17 patients treated in a prospective electromagnetic-guided MLC tracking trial. Tumor and markers were segmented on all phases of treatment planning 4DCTs and all frames of pretreatment kilovoltage fluoroscopy acquired from lateral and frontal views. The difference in tumor and marker position relative to end-exhale position was calculated as the SU for both imaging methods and the distributions of uncertainties analyzed.

RESULTS

The mean (range) tumor motion amplitude in the 4DCT scan was 5.9 mm (1.7-11.7 mm) in the superior-inferior (SI) direction, 2.2 mm (0.9-5.5 mm) in the left-right (LR) direction, and 3.9 mm (1.2-12.9 mm) in the anterior-posterior (AP) direction. Population-based analysis indicated symmetric SU centered close to 0 mm, with maximum 5th/95th percentile values over all axes of -2.0 mm/2.1 mm with 4DCT, and -2.3/1.3 mm for fluoroscopy. There was poor correlation between the SU measured with 4DCT and that measured with fluoroscopy on a per-patient basis. We observed increasing SU with increasing surrogate motion. Based on fluoroscopy analysis, the mean (95% CI) SU was 5% (2%-8%) of the motion magnitude in the SI direction, 16% (6%-26%) of the motion magnitude in the LR direction, and 33% (23%-42%) of the motion magnitude in the AP direction. There was no dependence of SU on marker distance from the tumor.

CONCLUSION

We have quantified SU due to use of implanted markers as surrogates for lung tumor motion. Population 95th percentile range are up to 2.3 mm, indicating the approximate contribution of SU to total geometric uncertainty. SU was relatively small compared with the SI motion, but substantial compared with LR and AP motion. Due to uncertainty in estimations of patient-specific SU, it is recommended that population-based margins are used to account for this component of the total geometric uncertainty.

Tumour volume comparison between 16-row multi-detector computed tomography and 320-row area-detector computed tomography in patients with small lung tumours treated with stereotactic body radiotherapy: Effect of respiratory motion

PURPOSE

We compared image quality and volume of a moving simulated tumour and of lung tumours in patients who were treated with stereotactic body radiotherapy (SBRT) in a 16-row multi-detector CT (MDCT) versus a 320-row area-detector CT (ADCT). Tumour volumes in each respiratory phase were also evaluated.

MATERIALS AND METHODS

We acquired static and four-dimensional CT (4DCT) images of a moving phantom with 10- and 30-mm amplitudes with three periods of patterns (2, 4, and 6 s). Breath-hold and 4DCT images were acquired for 12 lung tumour patients who underwent SBRT. Image data were acquired via MDCT and ADCT. The tumours were delineated in each respiratory phase and their volumes in end-expiratory/end-inspiratory phase and mid-respiratory phase were compared.

RESULTS

In the phantom study, tumour volumes were smaller and closer to the static image when evaluated by ADCT than by MDCT. In the clinical study, average tumour volumes ± standard deviations were 9.58 ± 1.07 cm³ with MDCT (2.5-mm slice), and 7.12 ± 0.23 cm³ with ADCT (p < 0.01). Tumour volumes were closer to that of the breath hold CT in all patients evaluated by ADCT than by MDCT. Unlike MDCT, tumour volumes acquired by ADCT were smaller in end-expiratory or end-inspiratory phase than in the mid-respiratory phase.

CONCLUSIONS

Tumour volumes in each of the respiratory phases in ADCT were significantly smaller and closer to the static image than the corresponding volumes in MDCT. This suggests that treated volume can be reduced if ADCT is used in treatment planning.