Improving the Quality of Radiotherapy by Multi-Institution Knowledge-Based Planning Optimization Models (Acronym: MIKAPOCo, Multi-Institutional Knowledge-based Approach in Plan Optimization for the Community)

An observational study of Breast Cancer and Prostate Cancer, run by IRCCS Ospedale San Raffaele at 1 site in Italy.

Unknown status

Status not confirmed. The sponsor has not verified this record for over two years, so it may be out of date.

Trial summary

Investigators central hypothesis is that it is possible to create libraries of "consistent" Knowledge-Based plan-models derived from large Institutional experiences. These libraries can be used to guide automated RT planning and serve as tools to assist centers for plan quality assurance (QA) and plan prediction. Read more about this study

Who is it for?: Any age
Conditions the study is for: Breast Cancer, Prostate Cancer
What is being tested?: treatment plan comparison
How many people: 1,000 participants
Where: 1 siteItaly
Study dates: 28 Oct 2022to 28 Oct 2025
Phase: Observational
Are there results?: None posted in the registry

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

Ages Any age
All sexes
No healthy volunteers
Child, Adult, Older adult

Study population: prostate cancer, breast cancer and for selected SBRT situations (spine and prostate, according to RTOG 0631 and 0938 schemes respectively).

Who may be able to join

real life consecutive (or randomly chosen) plan data of patients treated for prostate cancer during the last 10 years;
real life consecutive (or randomly chosen) plan data of patients treated for breast cancer during the last 10 years;
real life consecutive (or randomly chosen) plan data of patients treated for selected SBRT situations (spine and prostate, according to RTOG 0631 and 0938 schemes respectively) during the last 10 years.

Who cannot join

Trial locations and contacts

1 site in 1 country.

Italy1 site

IRCCS Ospedale San Raffaele
Milan, 20133

Other trials in Italy

About this study

Official title: Improving the Quality of Radiotherapy by Multi-Institution Knowledge-Based Planning Optimization Models

Quantifying Inter-institute variability of RT planning and building libraries of interchangeable and validated multi-Institutional KB plan prediction models is expected to impact on the quality of planning at the national level. The project has the potential of facilitating the introduction of AI approaches in plan optimization, thus reducing intra and inter-Institute planning variability. Improving plan quality is expected to translate into better outcome after RT in terms of local control and, even more, of side effects and Quality of life. Positive impact is also expected in patient selection for advanced techniques, in plan audit and plan optimization in clinical trials, in technology comparison and cost-benefit analyses as well as in the RT educational field.

Read the detailed description

Major aims

To create libraries of consistently generated KB models for patients treated with RT for breast and prostate cancer and for selected stereotactic-body RT (SBRT) applications based on the experience of many Italian Institutions; to quantify planning inter-institute variability in homogeneous classes of patients.
To group models based on their characteristics and interchangeability. To assess groups of highly interchangeable models to be considered for multi-institutional dose-volume histogram (DVH) prediction purposes.

Conditions: Breast Cancer, Prostate Cancer
Being tested: treatment plan comparison
Medical subject headings: Breast Neoplasms, Prostatic Neoplasms

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

treatment plan comparisonOther
In order to assess inter-Institute variability of DVH prediction of the various models, for the different situations and the different OARs, DVH and dose statistics (min, mean, median, max and SD of the dose received by each OAR) predicted on the patients owning to the different centers by the different models will be compared

What is being measured

The primary outcome is the main question the study is designed to answer.

model interchangeability
interchangeability will be assessed by considering: a) the fraction of patients identified as "anatomy outlier" (in terms of out of the geometric features (GF) boundary of each single model) once the model coming from Institute X is applied to patients of Institute Y (modX-Y) and vice-versa (modY-X); b) the relative differences in DVH predictions between modX-Y and modY-X, including and not including the previously recognized "GF outlier" patients. Based on these results and on their clinical interpretation, sub-groups of KB-models with "high" interchangeability will be tentatively identified and the relationships between GF and interchangeability quantified.
Measured: 3 years

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

28 Oct 202228 Oct 2025

First posted19 Mar 2024
Study start28 Oct 2022
Primary completion28 Oct 2022
Study completion28 Oct 2025 (estimated)

Resources

Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
Publications (5)Papers the sponsor has linked to this study.
Other trials for Breast CancerStudies of the same condition, open and under way.
What the trial phases meanHow a treatment moves from first tests in people to approval.

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design

Study type: Observational
Observational model: Cohort
Time perspective: Retrospective
Enrolment: 1,000 participants (estimated)

IDs, dates and publications

ClinicalTrials.gov ID: NCT06317948
Sponsor's protocol ID: IG23150
Acronym: MIKAPOCo
Status last verified: Mar 2024
First submitted: 12 Mar 2024
Last updated: 20 Mar 2024
Results posted: No
Data monitoring committee: No
FDA-regulated drug: No
FDA-regulated device: No
Individual data sharing: No

Publications

Esposito PG, Castriconi R, Mangili P, Broggi S, Fodor A, Pasetti M, Tudda A, Di Muzio NG, Del Vecchio A, Fiorino C. Knowledge-based automatic plan optimization for left-sided whole breast tomotherapy. Phys Imaging Radiat Oncol. 2022 Jun 23;23:54-59. doi: 10.1016/j.phro.2022.06.009. eCollection 2022 Jul.
PubMed 35814259
Tudda A, Castriconi R, Benecchi G, Cagni E, Cicchetti A, Dusi F, Esposito PG, Guernieri M, Ianiro A, Landoni V, Mazzilli A, Moretti E, Oliviero C, Placidi L, Rambaldi Guidasci G, Rancati T, Scaggion A, Trojani V, Fiorino C. Knowledge-based multi-institution plan prediction of whole breast irradiation with tangential fields. Radiother Oncol. 2022 Oct;175:10-16. doi: 10.1016/j.radonc.2022.07.012. Epub 2022 Jul 19.
PubMed 35868603
Monticelli D, Castriconi R, Tudda A, Fodor A, Deantoni C, Gisella Di Muzio N, Mangili P, Del Vecchio A, Fiorino C, Broggi S. Knowledge-based plan optimization for prostate SBRT delivered with CyberKnife according to RTOG0938 protocol. Phys Med. 2023 Jun;110:102606. doi: 10.1016/j.ejmp.2023.102606. Epub 2023 May 15.
PubMed 37196603
Castriconi R, Esposito PG, Tudda A, Mangili P, Broggi S, Fodor A, Deantoni CL, Longobardi B, Pasetti M, Perna L, Del Vecchio A, Di Muzio NG, Fiorino C. Replacing Manual Planning of Whole Breast Irradiation With Knowledge-Based Automatic Optimization by Virtual Tangential-Fields Arc Therapy. Front Oncol. 2021 Aug 24;11:712423. doi: 10.3389/fonc.2021.712423. eCollection 2021.
PubMed 34504790
Placidi L, Griffin P, Castriconi R, Tudda A, Benecchi G, Burns M, Cagni E, Markham C, Landoni V, Moretti E, Oliviero C, Guidasci GR, Meffe G, Rancati T, Scaggion A, McGoldrick K, Panettieri V, Fiorino C. An International Inter-Consortium Validation of Knowledge-Based Plan Prediction Modeling for Whole Breast Radiotherapy Treatment. Cancers (Basel). 2025 Nov 5;17(21):3576. doi: 10.3390/cancers17213576.
PubMed 41228368

Want to know more?

The sponsor has not listed a contact. The official record may have more details.

Talk to your doctor first and take this page with you. Only the study team can confirm whether you can join.

Questions to ask the study team

What is the study trying to find out?
What would I need to do, and how often would I visit?
Could I receive a placebo instead of the treatment?
What are the possible risks and benefits for me?
Will it cost me anything? Are travel or time paid for?
Can I keep seeing my own doctor during the study?
What happens when the study ends?

See locations

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Study at a glance

From the registry record, last updated by the sponsor on 20 Mar 2024. Recruitment status is as the sponsor reported it: confirm with the study team.

Official title: Improving the Quality of Radiotherapy by Multi-Institution Knowledge-Based Planning Optimization Models
ClinicalTrials.gov ID: NCT06317948
Acronym / sponsor ID: MIKAPOCo / IG23150
Conditions: Breast Cancer, Prostate Cancer
Study type: Observational
Recruitment status: Unknown status
Enrolment: 1,000 participants (estimated)
Lead sponsor: IRCCS Ospedale San RaffaeleUniversity, hospital or other
Study start: 28 Oct 2022 (actual)
Primary completion: 28 Oct 2022 (actual)
Study completion: 28 Oct 2025 (estimated)
First posted: 19 Mar 2024 (actual)
Results: Not posted in the source record

Clinical summary

The research question as the sponsor registered it. This describes what the study plans to test, not what it found.

Detailed description

Major aims

To create libraries of consistently generated KB models for patients treated with RT for breast and prostate cancer and for selected stereotactic-body RT (SBRT) applications based on the experience of many Italian Institutions; to quantify planning inter-institute variability in homogeneous classes of patients.
To group models based on their characteristics and interchangeability. To assess groups of highly interchangeable models to be considered for multi-institutional dose-volume histogram (DVH) prediction purposes.

Study design

Observational model: Cohort
Time perspective: Retrospective

Who may qualify

Sex: All
Healthy volunteers: Not accepted
Age groups: Child, Adult, Older adult
Study population: prostate cancer, breast cancer and for selected SBRT situations (spine and prostate, according to RTOG 0631 and 0938 schemes respectively).

Key inclusion criteria (3 listed)

real life consecutive (or randomly chosen) plan data of patients treated for prostate cancer during the last 10 years;
real life consecutive (or randomly chosen) plan data of patients treated for breast cancer during the last 10 years;
real life consecutive (or randomly chosen) plan data of patients treated for selected SBRT situations (spine and prostate, according to RTOG 0631 and 0938 schemes respectively) during the last 10 years.

Key exclusion criteria (1 listed)

Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.

Interventions

Intervention	Type	Arms
treatment plan comparisonIn order to assess inter-Institute variability of DVH prediction of the various models, for the different situations and the different OARs, DVH and dose statistics (min, mean, median, max and SD of the dose received by each OAR) predicted on the patients owning to the different centers by the different models will be compared	Other	–

Primary outcome

model interchangeability
Time frame: 3 years
interchangeability will be assessed by considering: a) the fraction of patients identified as "anatomy outlier" (in terms of out of the geometric features (GF) boundary of each single model) once the model coming from Institute X is applied to patients of Institute Y (modX-Y) and vice-versa (modY-X); b) the relative differences in DVH predictions between modX-Y and modY-X, including and not including the previously recognized "GF outlier" patients. Based on these results and on their clinical interpretation, sub-groups of KB-models with "high" interchangeability will be tentatively identified and the relationships between GF and interchangeability quantified.

Results and safety

Results are not available in the source record.

Research links

Official record on ClinicalTrials.govLast updated by the sponsor 20 Mar 2024.
Background: PubMed 35814259Esposito PG, Castriconi R, Mangili P, Broggi S, Fodor A, Pasetti M, Tudda A, Di Muzio NG, Del Vecchio A, Fiorino C. Knowledge-based automatic plan optimization for left-sided whole breast tomotherapy. Phys Imaging Radiat Oncol. 2022 Jun 23;23:54-59. doi: 10.1016/j.phro.2022.06.009. eCollection 2022 Jul.
Background: PubMed 35868603Tudda A, Castriconi R, Benecchi G, Cagni E, Cicchetti A, Dusi F, Esposito PG, Guernieri M, Ianiro A, Landoni V, Mazzilli A, Moretti E, Oliviero C, Placidi L, Rambaldi Guidasci G, Rancati T, Scaggion A, Trojani V, Fiorino C. Knowledge-based multi-institution plan prediction of whole breast irradiation with tangential fields. Radiother Oncol. 2022 Oct;175:10-16. doi: 10.1016/j.radonc.2022.07.012. Epub 2022 Jul 19.
Background: PubMed 37196603Monticelli D, Castriconi R, Tudda A, Fodor A, Deantoni C, Gisella Di Muzio N, Mangili P, Del Vecchio A, Fiorino C, Broggi S. Knowledge-based plan optimization for prostate SBRT delivered with CyberKnife according to RTOG0938 protocol. Phys Med. 2023 Jun;110:102606. doi: 10.1016/j.ejmp.2023.102606. Epub 2023 May 15.
Background: PubMed 34504790Castriconi R, Esposito PG, Tudda A, Mangili P, Broggi S, Fodor A, Deantoni CL, Longobardi B, Pasetti M, Perna L, Del Vecchio A, Di Muzio NG, Fiorino C. Replacing Manual Planning of Whole Breast Irradiation With Knowledge-Based Automatic Optimization by Virtual Tangential-Fields Arc Therapy. Front Oncol. 2021 Aug 24;11:712423. doi: 10.3389/fonc.2021.712423. eCollection 2021.
Derived from this study: PubMed 41228368Placidi L, Griffin P, Castriconi R, Tudda A, Benecchi G, Burns M, Cagni E, Markham C, Landoni V, Moretti E, Oliviero C, Guidasci GR, Meffe G, Rancati T, Scaggion A, McGoldrick K, Panettieri V, Fiorino C. An International Inter-Consortium Validation of Knowledge-Based Plan Prediction Modeling for Whole Breast Radiotherapy Treatment. Cancers (Basel). 2025 Nov 5;17(21):3576. doi: 10.3390/cancers17213576.
Individual participant dataSharing planned: No

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Advanced Solid Tumors, Metastatic Pancreatic Cancer
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Referral and contact

AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.

Claudio Fiorino, Msc principal investigator

IRCCS Ospedale San Raffaele

1 site in 1 country: see every site and its status.

Questions about this trial

What is this clinical trial studying?

An observational study of Breast Cancer and Prostate Cancer, run by IRCCS Ospedale San Raffaele at 1 site in Italy.

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

The sponsor lists 3 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: status not confirmed, as of the sponsor's last update on 20 Mar 2024. Status can change between updates, so confirm with the study contact before making plans.

Where is the study taking place?

The record lists 1 site in Italy. Whether a site is taking part right now should be confirmed with that site. See every site.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

Are results available for this study?

Results are not available in the source record.

How can a doctor refer a patient or contact the research team?

The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

model interchangeability (time frame: 3 years). It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT06317948, which also lists 5 linked publications.

Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 20 Mar 2024; AzTrials last refreshed its copy on 31 Oct 2026.