Software for quantitative analysis of radiotherapy: Overview, requirement analysis and design solutions

Radiotherapy is a fast-developing discipline which plays a major role in cancer care. Quantitative analysis of radiotherapy data can improve the success of the treatment and support the prediction of outcome. In this paper, we first identify functional, conceptional and general requirements on a software system for quantitative analysis of radiotherapy. Further we present an overview of existing radiotherapy analysis software tools and check them against the stated requirements. As none of them could meet all of the demands presented herein, we analyzed possible conceptional problems and present software design solutions and recommendations to meet the stated requirements (e.g. algorithmic decoupling via dose iterator pattern; analysis database design). As a proof of concept we developed a software library "RTToolbox" following the presented design principles. The RTToolbox is available as open source library and has already been tested in a larger-scale software system for different use cases. These examples demonstrate the benefit of the presented design principles.

[1]  D. G. Lewis,et al.  A DICOM-RT-based toolbox for the evaluation and verification of radiotherapy plans. , 2002, Physics in medicine and biology.

[2]  C. Burman,et al.  Calculation of complication probability factors for non-uniform normal tissue irradiation: the effective volume method. , 1989, International journal of radiation oncology, biology, physics.

[3]  L M Chin,et al.  Sampling techniques for the evaluation of treatment plans. , 1993, Medical physics.

[4]  M Goitein,et al.  Comments on "Sampling techniques for the evaluation of treatment plans" [Med. Phys. 20, 151-161 (1993)]. , 1993, Medical physics.

[5]  A. Niemierko,et al.  Dose-volume distributions: a new approach to dose-volume histograms in three-dimensional treatment planning. , 1994, Medical physics.

[6]  A. Nahum,et al.  Incorporating clinical measurements of hypoxia into tumor local control modeling of prostate cancer: Implications for the α/β ratio , 2003 .

[7]  Alexander A. Stepanov,et al.  C++ Standard Template Library , 2000 .

[8]  Alan E. Nahum,et al.  Handbook of Radiotherapy Physics: Theory and Practice , 2007 .

[9]  Michael Adamowicz,et al.  Data base systems , 1976 .

[10]  R. Mohan,et al.  Histogram reduction method for calculating complication probabilities for three-dimensional treatment planning evaluations. , 1991, International journal of radiation oncology, biology, physics.

[11]  Niko Papanikolaou,et al.  A graphic user interface toolkit for specification, report and comparison of dose-response relations and treatment plans using the biologically effective uniform dose , 2010, Comput. Methods Programs Biomed..

[12]  R Mohan,et al.  Comments on "Sampling techniques for the evaluation of treatment plans" [Med. Phys. 20, 151-161 (1993)]. , 1993, Medical physics.

[13]  A B Wolbarst,et al.  Optimization of radiation therapy, III: A method of assessing complication probabilities from dose-volume histograms. , 1987, International journal of radiation oncology, biology, physics.

[14]  A. Nahum,et al.  Tumour control probability modelling: Basic principles and applications in treatment planning. , 2001 .

[15]  Indrin J Chetty,et al.  Analysis of outcomes in radiation oncology: an integrated computational platform. , 2009, Medical physics.

[16]  Marco Eichelberg,et al.  Ten years of medical imaging standardization and prototypical implementation: the DICOM standard and the OFFIS DICOM toolkit (DCMTK) , 2004, SPIE Medical Imaging.

[17]  A. Niemierko.  Reporting and analyzing dose distributions: a concept of equivalent uniform dose. , 1997, Medical physics.

[18]  W Schlegel,et al.  Stereotactically guided fractionated radiotherapy: technical aspects. , 1993, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[19]  B. Gino Fallone,et al.  A TCP‐NTCP estimation module using DVHs and known radiobiological models and parameter sets , 2004, Journal of applied clinical medical physics.

[20]  J. Fowler.  The linear-quadratic formula and progress in fractionated radiotherapy. , 1989, The British journal of radiology.

[21]  A. Niemierko,et al.  Modeling of normal tissue response to radiation: the critical volume model. , 1993, International journal of radiation oncology, biology, physics.

[22]  B Sanchez-Nieto,et al.  BIOPLAN: software for the biological evaluation of. Radiotherapy treatment plans. , 2000, Medical dosimetry : official journal of the American Association of Medical Dosimetrists.

[23]  Joseph O Deasy,et al.  CERR: a computational environment for radiotherapy research. , 2003, Medical physics.

[24]  E. F. Codd,et al.  Further Normalization of the Data Base Relational Model , 1971, Research Report / RJ / IBM / San Jose, California.

[25]  I El Naqa,et al.  Dose response explorer: an integrated open-source tool for exploring and modelling radiotherapy dose–volume outcome relationships , 2006, Physics in medicine and biology.

[26]  D. Baltas,et al.  A conformal index (COIN) to evaluate implant quality and dose specification in brachytherapy. , 1998, International journal of radiation oncology, biology, physics.

[27]  A. Nahum,et al.  The delta-TCP concept: a clinically useful measure of tumor control probability. , 1999, International journal of radiation oncology, biology, physics.

[28]  A. Brahme,et al.  Optimization of radiation therapy , 1994 .

[29]  M. Goitein,et al.  Tolerance of normal tissue to therapeutic irradiation. , 1991, International journal of radiation oncology, biology, physics.

[30]  A Brahme,et al.  Dosimetric precision requirements in radiation therapy. , 1984, Acta radiologica. Oncology.

[31]  David R. Wigg.  A radiobiological basis for bioeffect planning , 2000 .

[32]  D. Joseph,et al.  Comparison of DVH data from multiple radiotherapy treatment planning systems. , 2010, Physics in medicine and biology.

[33]  M. Moerland,et al.  A conformation number to quantify the degree of conformality in brachytherapy and external beam irradiation: application to the prostate. , 1997, International journal of radiation oncology, biology, physics.

[34]  W Schlegel,et al.  Computer systems and mechanical tools for stereotactically guided conformation therapy with linear accelerators. , 1992, International journal of radiation oncology, biology, physics.

[35]  E. Glatstein.  Personal thoughts on normal tissue tolerance, or, what the textbooks don't tell you. , 2001, International journal of radiation oncology, biology, physics.

[36]  M Goitein,et al.  Implementation of a model for estimating tumor control probability for an inhomogeneously irradiated tumor. , 1993, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[37]  J. Lyman,et al.  Normal tissue complication probabilities: variable dose per fraction. , 1992, International journal of radiation oncology, biology, physics.

[38]  R. Garcia,et al.  Evaluation dosimétrique d'une radiothérapie conformationnelle: le facteur de conformation , 2000 .

[39]  G T Chen,et al.  Dose volume histograms in treatment planning. , 1988, International journal of radiation oncology, biology, physics.

[40]  Moyed Miften,et al.  EUCLID: an outcome analysis tool for high-dimensional clinical studies , 2007, Physics in medicine and biology.

[41]  A Brahme,et al.  Tumour and normal tissue responses to fractionated non-uniform dose delivery. , 1992, International journal of radiation biology.

[42]  H. Thames,et al.  Dose-response relationships for late radiation effects in the head and neck: regarding the analysis of the RTOG 8313 trial, Fu et al. IJROBP 32:577-588; 1995. , 1996, International journal of radiation oncology, biology, physics.

[43]  J. Deasy,et al.  Multivariable modeling of radiotherapy outcomes, including dose-volume and clinical factors. , 2006, International journal of radiation oncology, biology, physics.

[44]  S Webb,et al.  A model for calculating tumour control probability in radiotherapy including the effects of inhomogeneous distributions of dose and clonogenic cell density. , 1993, Physics in medicine and biology.

[45]  G E Hanks,et al.  The effect of dose on local control of prostate cancer. , 1988, International journal of radiation oncology, biology, physics.