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Literature DB >> 25680592

Embracing phenomenological approaches to normal tissue complication probability modeling: a question of method.

Arjen van der Schaaf, Arjien van der Schaaf¹, Johannes Albertus Langendijk¹, Claudio Fiorino², Tiziana Rancati³.

Abstract

Mesh：

Year: 2015 PMID： 25680592 DOI： 10.1016/j.ijrobp.2014.10.017

Source DB: PubMed Journal: Int J Radiat Oncol Biol Phys ISSN： 0360-3016 Impact factor: 7.038

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7 in total

1. Modeling of Xerostomia After Radiotherapy for Head and Neck Cancer: A Registry Study.

Authors: Eva Onjukka; Claes Mercke; Einar Björgvinsson; Anna Embring; Anders Berglund; Gabriella Alexandersson von Döbeln; Signe Friesland; Giovanna Gagliardi; Clara Lenneby Helleday; Helena Sjödin; Ingmar Lax
Journal: Front Oncol Date: 2020-08-14 Impact factor: 6.244

2. Objectively Quantifying Radiation Esophagitis With Novel Computed Tomography-Based Metrics.

Authors: Joshua S Niedzielski; Jinzhong Yang; Francesco Stingo; Mary K Martel; Radhe Mohan; Daniel R Gomez; Tina M Briere; Zhongxing Liao; Laurence E Court
Journal: Int J Radiat Oncol Biol Phys Date: 2015-10-14 Impact factor: 7.038

3. Life years lost attributable to late effects after radiotherapy for early stage Hodgkin lymphoma: The impact of proton therapy and/or deep inspiration breath hold.

Authors: Laura Ann Rechner; Maja Vestmø Maraldo; Ivan Richter Vogelius; Xiaorong Ronald Zhu; Bouthaina Shbib Dabaja; Nils Patrik Brodin; Peter Meidahl Petersen; Lena Specht; Marianne Camille Aznar
Journal: Radiother Oncol Date: 2017-08-30 Impact factor: 6.280

Embracing phenomenological approaches to normal tissue complication probability modeling: a question of method.

1. Modeling of Xerostomia After Radiotherapy for Head and Neck Cancer: A Registry Study.

2. Objectively Quantifying Radiation Esophagitis With Novel Computed Tomography-Based Metrics.

3. Life years lost attributable to late effects after radiotherapy for early stage Hodgkin lymphoma: The impact of proton therapy and/or deep inspiration breath hold.

Review 4. Technology-driven research for radiotherapy innovation.

Review 5. Radiomic and radiogenomic modeling for radiotherapy: strategies, pitfalls, and challenges.

Review 6. Big Data Analytics for Prostate Radiotherapy.

7. Tumor Control Probability Modeling for Radiation Therapy of Keratinocyte Carcinoma.