Justus Adamson

Overview:

Radiosurgery and SBRT
Image Guided Radiation Therapy (IGRT)
Quality Assurance (QA) in Radiation Therapy
3D Dosimetry

Positions:

Associate Professor of Radiation Oncology

Radiation Oncology
School of Medicine

Member of the Duke Cancer Institute

Duke Cancer Institute
School of Medicine

Education:

Ph.D. 2009

Wayne State University

Research Assistant

William Beaumont Hospital, Royal Oak

Postdoctoral Associate/Medical Physicist Residency Program, Radiation Oncology Physics Division

Duke University School of Medicine

Grants:

MC Independent Dose Calculation for Single Isocenter Multi-target Stereotactic Radiosurgery

Administered By
Radiation Oncology
Awarded By
Radialogica
Role
Principal Investigator
Start Date
End Date

Publications:

TARDIS: An updated artificial intelligence model to predict linear accelerator machine parameters at treatment delivery

We present an open-source artificial intelligence (AI) model that predicts machine parameters at treatment delivery using trajectory files from prior patients. Predictive models for IMRT and VMAT utilized a boosted and bagged tree, respectively, and predicted MLC errors with a high degree of accuracy (IMRT R2=0.99 and 0.98 for high and low-resolution respectively; VMAT R2=0.97 and 0.90). Residual error for constructed cases was <0.01 mm with R2 ranging from 0.84 – 0.99. The updated AI model is now made available to predict error in machine parameters at treatment delivery for a new DICOM-RT plan.
Authors
Lay, LM; Chuang, KC; Giles, W; Adamson, J
MLA Citation
Lay, L. M., et al. “TARDIS: An updated artificial intelligence model to predict linear accelerator machine parameters at treatment delivery.” Softwarex, vol. 19, July 2022. Scopus, doi:10.1016/j.softx.2022.101146.
URI
https://scholars.duke.edu/individual/pub1532027
Source
scopus
Published In
Softwarex
Volume
19
Published Date
DOI
10.1016/j.softx.2022.101146

Virtual patient-specific QA with DVH-based metrics.

We demonstrate a virtual pretreatment patient-specific QA (PSQA) procedure that is capable of quantifying dosimetric effect on patient anatomy for both intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT). A machine learning prediction model was developed to use linear accelerator parameters derived from the DICOM-RT plan to predict delivery discrepancies at treatment delivery (defined as the difference between trajectory log file and DICOM-RT) and was coupled with an independent Monte Carlo dose calculation algorithm for dosimetric analysis. Machine learning models for IMRT and VMAT were trained and validated using 120 IMRT and 206 VMAT fields of prior patients, with 80% assigned for iterative training and testing, and 20% for post-training validation. Various prediction models were trained and validated, with the final models selected for clinical implementation being a boosted tree and bagged tree for IMRT and VMAT, respectively. After validation, these models were then applied clinically to predict the machine parameters at treatment delivery for 7 IMRT plans from various sites (61 fields) and 10 VMAT multi-target intracranial radiosurgery plans (35 arcs) and compared to the dosimetric effect calculated directly from trajectory log files. Dose indices tracked for targets and organs at risk included dose received by 99%, 95%, and 1% of the volume, mean dose, percent of volume receiving 25%-100% of the prescription dose. The average coefficient of determination (r2 ) when comparing intra-field predicted and actual delivery error was 0.987 ± 0.012 for IMRT and 0.895 ± 0.095 for VMAT, whereas r2 when comparing inter-field predicted versus actual delivery error was 0.982 for IMRT and 0.989 for VMAT. Regarding dosimetric analysis, r2 when comparing predicted versus actual dosimetric changes for all dose indices was 0.966 for IMRT and 0.907 for VMAT. Prediction models can be used to anticipate the dosimetric effect calculated from trajectory files and have potential as a "delivery-free" pretreatment analysis to enhance PSQA.
Authors
Lay, LM; Chuang, K-C; Wu, Y; Giles, W; Adamson, J
MLA Citation
Lay, Lam M., et al. “Virtual patient-specific QA with DVH-based metrics.J Appl Clin Med Phys, May 2022, p. e13639. Pubmed, doi:10.1002/acm2.13639.
URI
https://scholars.duke.edu/individual/pub1521486
PMID
35570395
Source
pubmed
Published In
Journal of Applied Clinical Medical Physics
Published Date
Start Page
e13639
DOI
10.1002/acm2.13639

The Effect of Various Dose Normalization Strategies When Implementing Linear Boltzmann Transport Equation Dose Calculation for Lung Stereotactic Body Radiation Therapy Planning.

PURPOSE: To explore implications of various plan normalizations when implementing a linear Boltzmann transport equation solver dose calculation algorithm (LBTE) for lung stereotactic body radiation therapy (SBRT). METHODS AND MATERIALS: Eighty-seven plans originally calculated with a convolution-superposition algorithm (CS) were recalculated with LBTE and normalized in 3 ways: prescription covering 95% of planning target volume (PTV), 99% of internal target volume (ITV), and keeping the original planned PTV coverage. Effect on delivered dose after implementing the new algorithm was quantified using change in total monitor units for each renormalization strategy. Treatment planning system-reported changes in PTV, ITV, and organ at risk (OAR) doses were also quantified, along with the feasibility of LBTE plans to meet institutional OAR planning objectives. RESULTS: LBTE renormalization resulted in monitor unit increases of 7.0 ± 8.8%, 0.31 ± 5.8%, and 7.9 ± 8.6% when normalizing to the PTV D95%, ITV D99%, and planned coverage, respectively. When normalizing to PTV D95%, the LBTE reported increased PTV and ITV D1% (Gy) relative to CS (median, 3.4% and 3.2%, respectively), and normalizing to ITV D99% showed a median 1.9% decrease. For LBTE plans, reported OAR doses were increased when normalizing to PTV D95% or planned coverage (median chest wall V30 Gy [cc] increase of 0.85 and 1.7 cc, respectively) and normalizing to ITV D99% resulted in decreased dose (median chest wall V30 Gy [cc] decrease of 1.8 cc). LBTE plans normalized to PTV D95% showed inferior ability to meet the OAR objectives, but reoptimizing kept the objectives manageable while maintaining PTV coverage. CONCLUSIONS: When transitioning from CS to LBTE dose calculation for lung SBRT, maintaining a PTV coverage-based normalization generally results in increased dose delivered relative to CS and increased reported target and OAR dose. In cases where PTV normalization results in unacceptably high doses to targets or OARs, normalizing based on ITV coverage can be considered to maintain similar target dose as CS.
Authors
Erickson, BG; Ackerson, BG; Kelsey, CR; Yin, F-F; Adamson, J; Cui, Y
MLA Citation
URI
https://scholars.duke.edu/individual/pub1512162
PMID
35219882
Source
pubmed
Published In
Pract Radiat Oncol
Published Date
DOI
10.1016/j.prro.2022.02.005

Development of a practical clinical application of NIPAM kV-CBCT dosimetry

We report our progress towards developing a clinical application of NIPAM kV-CBCT dosimetry. The goal is to develop a practical kV-MV isocenter verification test for which the measurement and analysis can be carried out quickly (within an hour), and that eliminates the need for separate readout (other than on board kV-CBCT) or extra analysis steps such as image registration. Isocenter verification is performed using a NIPAM 3D gel dosimeter which is irradiated with a small field to ~16Gy at eight unique couch/gantry angles. Pre- and post-irradiation kV-CBCT images are acquired and dose is manifest as the intensity difference between pre- and post-CBCTs due to radiation induced changes in density. Code was developed to detect the geometry of each beam in the kV-CBCT and quantify relevant parameters. We applied this technique to verify the isocenter for MLCs as well as for SRS cones. The measured radius to encompass all beams for 4mm, 6mm, 7.5mm, 12.5mm, and 15mm cones was 0.55±0.11mm. The efficiency, robustness to setup errors, and unique ability to visualize spatial uncertainties in the kV-CBCT coordinate system make the NIPAM kV-CBCT test a practical and unique tool for kV-MV isocenter verification.
Authors
Pant, K; Oldham, M; Giles, W; Adamson, J
MLA Citation
Pant, K., et al. “Development of a practical clinical application of NIPAM kV-CBCT dosimetry.” Journal of Physics: Conference Series, vol. 2167, no. 1, 2022. Scopus, doi:10.1088/1742-6596/2167/1/012007.
URI
https://scholars.duke.edu/individual/pub1510989
Source
scopus
Published In
Journal of Physics: Conference Series
Volume
2167
Published Date
DOI
10.1088/1742-6596/2167/1/012007

Outcomes in Patients With 4 to 10 Brain Metastases Treated With Dose-Adapted Single-Isocenter Multitarget Stereotactic Radiosurgery: A Prospective Study.

PURPOSE: To examine the effectiveness and safety of single-isocenter multitarget stereotactic radiosurgery using a volume-adapted dosing strategy in patients with 4 to 10 brain metastases. METHODS AND MATERIALS: Adult patients with 4 to 10 brain metastases were eligible for this prospective trial. The primary endpoint was overall survival. Secondary endpoints were local recurrence, distant brain failure, neurologic death, and rate of adverse events. Exploratory objectives were neurocognition, quality of life, dosimetric data, salvage rate, and radionecrosis. Dose was prescribed in a single fraction per RTOG 90-05 or as 5 Gy × 5 fractions for lesions ≥3 cm diameter, lesions involving critical structures, or single-fraction brain V12Gy >20 mL. RESULTS: Forty patients were treated with median age of 61 years, Karnofsky performance status 90, and 6 brain metastases. Twenty-two patients survived longer than expected from the time of protocol SRS, with 1 living patient who has not reached that milestone. Median overall survival was 8.1 months with a 1-year overall survival of 35.7%. The 1-year local recurrence rate was 5% (10 of 204 of evaluable lesions) in 12.5% (4 of 32) of the patients. Distant brain failure was observed in 19 of 32 patients with a 1-year rate of 35.8%. Grade 1-2 headache was the most common complaint, with no grade 3-5 treatment-related adverse events. Radionecrosis was observed in only 5 lesions, with a 1-year rate of 1.5%. Rate of neurologic death was 20%. Neurocognition and quality of life did not significantly change 3 months after SRS compared with pretreatment. CONCLUSIONS: These results suggest that volume-adapted dosing single-isocenter multitarget stereotactic radiosurgery is an effective and safe treatment for patients with 4 to 10 brain metastases.
Authors
Kim, GJ; Buckley, ED; Herndon, JE; Allen, KJ; Dale, TS; Adamson, JD; Lay, L; Giles, WM; Rodrigues, AE; Wang, Z; Kelsey, CR; Torok, JA; Chino, JP; Fecci, PE; Sampson, JH; Anders, CK; Floyd, SR; Yin, F-F; Kirkpatrick, JP
MLA Citation
Kim, Grace J., et al. “Outcomes in Patients With 4 to 10 Brain Metastases Treated With Dose-Adapted Single-Isocenter Multitarget Stereotactic Radiosurgery: A Prospective Study.Adv Radiat Oncol, vol. 6, no. 6, Nov. 2021, p. 100760. Pubmed, doi:10.1016/j.adro.2021.100760.
URI
https://scholars.duke.edu/individual/pub1504691
PMID
34934856
Source
pubmed
Published In
Advances in Radiation Oncology
Volume
6
Published Date
Start Page
100760
DOI
10.1016/j.adro.2021.100760