An Evaluation of Total Internal Motions of Locally Advanced Pancreatic Cancer during SABR Using Calypso ® Extracranial Tracking, and Its Possible Clinical Impact on Motion Management.
Hrvoje KaučićDomagoj KosminaDragan SchwarzAdlan ČehobašićVanda LeipoldIvo PedišićMihaela MlinarićMatea LekićHrvoje ŠobatAndreas MackPublished in: Current oncology (Toronto, Ont.) (2021)
(1) Background: the aims of this study were to determine the total extent of pancreatic cancer's internal motions, using Calypso ® extracranial tracking, and to indicate possible clinical advantages of continuous intrafractional fiducial-based tumor motion tracking during SABR. (2) Methods: thirty-four patients were treated with SABR for LAPC using Calypso ® for motion management. Planning MSCTs in FB and DBH, and 4D-CTs were performed. Using data from Calypso ® and 4D-CTs, the movements of the lesions in the CC, AP and LR directions, as well as the volumes of the 4D-CT-based ITV and the volumes of the Calypso ® -based ITV were compared. (3) Results: significantly larger medians of tumor excursions were found with Calypso ® than with 4D-CT: CC: 29 mm ( p < 0.001); AP: 14 mm ( p < 0.001) and LR: 11 mm ( p < 0.039). The median volume of the Calypso ® -based ITV was significantly larger than that of the 4D-CT based ITV ( p < 0.001). (4) Conclusion: beside known respiratory-induced internal motions, pancreatic cancer seems to have significant additional motions which should be considered during respiratory motion management. Only direct and continuous intrafractional fiducial-based motion tracking seems to provide complete coverage of the target lesion with the prescribed isodose, which could allow for safe tumor dose escalation.
Keyphrases
- high speed
- image quality
- computed tomography
- contrast enhanced
- locally advanced
- end stage renal disease
- newly diagnosed
- transcription factor
- ejection fraction
- squamous cell carcinoma
- chronic kidney disease
- radiation therapy
- positron emission tomography
- rectal cancer
- mass spectrometry
- oxidative stress
- machine learning
- diabetic rats
- patient reported
- double blind