Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Cancer Survival Analysis

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

[Not Available].

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]·2016

Same author

Neutrophil gelatinase-associated lipocalin is a biomarker of acute-on-chronic liver failure and prognosis in cirrhosis.

Journal of hepatology·2016

Same author

Extended-spectrum beta-lactamase-producing Enterobacteriaceae (ESBL-PE) infections: are carbapenem alternatives achievable in daily practice?

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases·2015

Same author

Elaboration of a consensual definition of de-escalation allowing a ranking of β-lactams.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases·2015

Same author

Effects of different forms and origins of oilseeds on dynamics of ruminal biohydrogenation of long-chain fatty acids in vitro.

Journal of animal physiology and animal nutrition·2015

Same author

[Foetal Mortality in Singleton Foetuses at and beyond Term - An Analysis of German Perinatal Data 2004-2013].

Zeitschrift fur Geburtshilfe und Neonatologie·2015

Search research articles

Related Experiment Video

Updated: Jun 15, 2026

Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies

Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies

Published on: February 6, 2019

Coverage optimized planning: probabilistic treatment planning based on dose coverage histogram criteria.

J J Gordon¹, N Sayah, E Weiss

¹Department of Radiation Oncology, Virginia Commonwealth University, P.O. Box 980058, Richmond, Virginia 23298, USA. jgordon@mcvh-vcu.edu

Medical Physics

|March 17, 2010

Summary

Coverage Optimized Planning (COP) improves radiation therapy by using dose coverage histogram (DCH) criteria for better target coverage. This probabilistic approach optimizes treatment plans by considering geometric uncertainties, outperforming traditional methods.

More Related Videos

Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System

Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System

Published on: April 11, 2018

Radiation Planning Assistant - A Web-based Tool to Support High-quality Radiotherapy in Clinics with Limited Resources

Radiation Planning Assistant - A Web-based Tool to Support High-quality Radiotherapy in Clinics with Limited Resources

Published on: October 6, 2023

Related Experiment Videos

Last Updated: Jun 15, 2026

Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies

Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies

Published on: February 6, 2019

Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System

Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System

Published on: April 11, 2018

Radiation Planning Assistant - A Web-based Tool to Support High-quality Radiotherapy in Clinics with Limited Resources

Radiation Planning Assistant - A Web-based Tool to Support High-quality Radiotherapy in Clinics with Limited Resources

Published on: October 6, 2023

Area of Science:

Radiation Oncology
Medical Physics
Radiotherapy Planning

Background:

Conventional radiotherapy planning relies on static dose distributions and planning target volumes (PTVs).
Geometric uncertainties, such as patient setup errors, introduce variability in the delivered dose (Dv).
Dose Volume Histograms (DVHs) traditionally assess dose-volume relationships, but do not inherently account for uncertainties.

Purpose of the Study:

To introduce a probabilistic treatment planning framework, Coverage Optimized Planning (COP), utilizing dose coverage histogram (DCH) criteria.
To implement and evaluate COP within the PINNACLE treatment planning system.
To compare COP-generated plans against traditional PTV-based plans for prostate cancer anatomies.

Main Methods:

Developed a COP framework based on DCH criteria, which plots coverage probability (Q) versus dose (D).
Implemented COP in the PINNACLE system, replacing PTVs and planning organ at risk volumes with clinical target volumes (CTVs) and organs at risk (OARs).
Optimized plans using DCH criteria for CTV minimum dose and conventional DVH criteria for other structures, comparing them to PTV-based plans.

Main Results:

COP plans demonstrated improved target coverage compared to PTV-based plans across 28 prostate anatomies.
COP effectively exploited 'slack' in OAR doses (doses below optimization limits) to enhance target coverage.
COP plans allowed for wider dosimetric margins around the CTV without exceeding OAR dose constraints.

Conclusions:

The Coverage Optimized Planning (COP) framework offers a promising approach to enhance target coverage in radiotherapy by incorporating probabilistic dose assessments.
COP's ability to leverage OAR dose variability suggests potential for improved treatment outcomes.
Further research is needed to fully elucidate the clinical benefits of COP, particularly regarding tumor control and normal tissue complication probabilities.