Analysis of clinical complication data for radiation hepatitis using a parallel architecture model

Jackson, Andrew; Haken, Randall K. Ten; Robertson, John M.; Kessler, M.L.; Kutcher, Gerald J.; Lawrence, Theodore S.

doi:10.1016/0360-3016(94)00471-4

Cited by 229 publications

(96 citation statements)

References 28 publications

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“…Newer and more accurate clinical data about dose-response relations of tumors and normal tissues are reported by many investigators at an increasing rate [2,17,18,25,31,37]. However, the reliability of biological treatment planning evaluation needs to be supported through further clinical verification of these data.…”

Section: Introductionmentioning

confidence: 99%

“…However, the reliability of biological treatment planning evaluation needs to be supported through further clinical verification of these data. For this reason, analysis of large patient datasets should be conducted before introducing information about normal-tissue radiation reactions in the clinical routine [25,28,35]. A number of different radiobiological models have been developed to calculate normal-tissue complication probability (NTCP), which is very important in the evaluation and comparison of treatment plans [9,11,26,27].…”

Section: Introductionmentioning

confidence: 99%

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Dose-Response Relations for Anal Sphincter Regarding Fecal Leakage and Blood or Phlegm in Stools after Radiotherapy for Prostate Cancer

Mavroidis

al-Abany

Helgason³

et al. 2005

Strahlenther Onkol

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dose-Response Relations for Anal Sphincter Regarding Fecal Leakage and Blood or Phlegm in Stools after Radiotherapy for Prostate Cancer

Mavroidis

al-Abany

Helgason³

et al. 2005

Strahlenther Onkol

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“…A parallel architecture model proposed by Jackson et al [25] considers the phenomenological response of functional subunits describing the probability defined in terms of the tolerance dose and slope of the dose-response. Whilst each of these models attempts to model the dose-response relationship for an individual structure, the LKB model is still dominant in the clinic.…”

Section: Dosimetric Data Reduction-summary Measurementioning

confidence: 99%

Modelling of Normal Tissue Complication Probabilities (NTCP): Review of Application of Machine Learning in Predicting NTCP

Gulliford

2015

Machine Learning in Radiation Oncology

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Predicting normal tissue toxicity following radiotherapy is a multidimensional challenge. The dose received by healthy tissue surrounding the tumour is described using a 3D dose distribution. In addition, patient-and treatment-related factors must also be considered in any predictive model of toxicity. Mixing these complex and disparate data types is a challenge that can be addressed with machine learning. This chapter introduces the concept of normal tissue complication probability (NTCP) and reviews literature related to the use of machine learning in this field. NTCP ModellingThe response of normal tissue incidentally and unavoidably irradiated during radiotherapy is the main factor limiting the increase in prescription dose to the tumour. Optimising this trade-off, known as the therapeutic ratio, is the fundamental challenge in radiotherapy (Fig. 17.1). Although complimentary in approach, the complexity of predicting normal tissue response is a higher dimensional problem than predicting local control. The reasons for this are (1) there are usually more than one organ at risk irradiated and protecting all of these structures requires compromise, (2) each structure responds differently to radiotherapy due to the type of cells and the structural and functional organisation of the tissue, and (3) the dose distributions to the surrounding normal tissues are inhomogeneous with gradients

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“…Hinsichtlich der Strahlenexposition gesunden Leberparenchyms und der damit verbundenen Gefährdung der Leberfunktion nach dem Eingriff ist zu bemerken, dass die funktionelle Kapazität der Leber direkt proportional der Anzahl intakter Hepatozyten sein dürfte [10,11,17,18]. Entsprechend stellt das über die Toleranzschwelle bestrahlte Lebervolumen die entscheidende Determinante für die Entwicklung einer Bestrahlungshepatitis dar.…”

Section: Diskussionunclassified

CT-gesteuerte Brachytherapie

et al. 2004

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Analysis of clinical complication data for radiation hepatitis using a parallel architecture model

Cited by 229 publications

References 28 publications

Dose-Response Relations for Anal Sphincter Regarding Fecal Leakage and Blood or Phlegm in Stools after Radiotherapy for Prostate Cancer

Dose-Response Relations for Anal Sphincter Regarding Fecal Leakage and Blood or Phlegm in Stools after Radiotherapy for Prostate Cancer

Modelling of Normal Tissue Complication Probabilities (NTCP): Review of Application of Machine Learning in Predicting NTCP

CT-gesteuerte Brachytherapie

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