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Physik-Institut Group of Jan Unkelbach

Target volume definition

Intensity-modulated radiotherapy and image-guided radiotherapy allow us to deliver radiation precisely to the tumor and conform the dose distribution to complex shaped target volumes. Nowadays, the largest uncertainty is often the definition of the target volume, i.e. the region that should be irradiated. Radiotherapy planning distinguishes three target volumes:

  • The gross tumor volume (GTV) comprising the macroscopic tumor mass
  • The clinical target volume (CTV) containing microscopic extensions of the tumor
  • The planning target volume (PTV) compensating for setup uncertainty and motion

GTV definition improved with the development of novel biomedical imaging techniques such as novel PET tracers and functional MRI. PTV margins were reduced through modern image guidance. Arguably, the definition of the CTV has made the least progress over the years. GTV definition amounts to delineating an abnormal tumor mass that es visible on imaging. In contrast, the CTV is invisible as it consists of microscopic tumor infiltration into normal appearing functioning tissues. Therefore, CTV definition is conceptually different from GTV definiton and is based on knowledge of the anatomically defined routes of tumor progression.

CTV definition has long been considered the domain of radiation oncologists and has attracted relatively little attention in the medical physics community. In our research group we work on computational methods to support target volume definition. Current research focuses on lymphatic cancer progression; past research projects considered brain tumors. This publication summarizes the role of computational methods for improving CTV definition:

  • J. Unkelbach, T. Bortfeld, CE. Cardenas, V. Gregoire, W. Hager, B. Heijmen, R. Jeraj, S. Korreman, R. Ludwig, B. Pouymayou, N. Shusharina, J. Söderberg, I. Toma-Dasu, EGC. Troost, E. Vasquez Osorio. The role of computational methods for automating and improving clinical target volume definition. Radiotherapy and Oncology, 153:15-25, 2020

This presentation given remotely at the annual ESTRO meeting 2020 provides an overview on how computational methods may improve or automate the definition of the clinical target volume (CTV).

 

Elective nodal CTV definition for head & neck cancer

Head & neck squamous cell carcinoma (HNSCC) spread through the lymphatic system and form metastases in regional lymph nodes. Target volume definition involves detecting macroscopic metastases based on CT, PET, and MR imaging. However, in current practice a much larger part of the lymph drainage region is irradiated, which may harbor microscopic metastases despite negative imaging findings. In one of our projects, we work on statistical models for the lymphatic progression of tumors using Bayesian networks and Hidden Markov Models:

  • R. Ludwig, J. Hoffmann, B. Pouymayou, M. Broglie Däppen, G. Morand, M. Guckenberger, V. Grégoire, P. Balermpas; J. Unkelbach. Detailed patient-individual reporting of lymph node involvement in oropharyngeal squamous cell carcinoma with an online interface. Radiotherapy & Oncology, 169:p1-7, 2022 
  • R. Ludwig, B. Pouymayou, P. Balermpas, J. Unkelbach. A hidden Markov model for lymphatic tumor progression in the head & neck. Scientific Reports, 11(1):p1-17, 2021
  • Pouymayou B, Balermpas P, Riesterer O, Guckenberger M, Unkelbach J. A Bayesian network model of lymphatic tumor progression for personalized elective CTV definition in head and neck cancer. Phys Med Biol. 2019;64(16):165003

Two videos provide an introduction to our work, which is funded by the clinical reserach priority program (CRPP) on Artificial Intelligence in Oncological Imaging by the UZH. 

1) Introduction to AI for target volume definition in head & neck cancer

2) Modeling lymphatic progression of cancer

As part of our efforts, we develop the online platformLyProx to host, share and visualize datasets on patterns of lymph node involvement in HNSCC patients, which is the basis for a better quantification of tumor progression. The GUI allows users to study how the risk of lymph node metastases in a lymph node level depends on location and stage of the primary tumor and the presence of lymph node metastases in other lymph node levels.

CTV definition for glioblastoma

Glioblastoma are known to infiltrate the healthy appearing brain tissue far beyond the tumor mass that is visible on MR imaging. However, the spatial patterns of tumor infiltartion are determined by the complex anatomy of the brain. Tumor cells spread primarily along white matter fibers while the falx and the ventricles represent anatomical barriers. In a previous project, we worked on phenomenological tumor growth models to facilitate automatic CTV definition that is consistent with neuroanatomy.

  • J. Unkelbach, B. H. Menze, E. Konukoglu, F. Dittmann, M. Le, N. Ayache, and H. Shih. Radiotherapy planning for glioblastoma based on a tumor growth model: improving target volume delineation. Phys. Med. Biol., 2014; 59(3):747-770
  • J. Unkelbach, B. H. Menze, E. Konukoglu, F. Dittmann, N. Ayache, and H. Shih. Radiotherapy planning for glioblastoma based on a tumor growth model: implications for spatial dose redistribution. Phys. Med. Biol., 2014; 59(3):771-790