AI Algorithms to Automate the TMI by VMAT Optimization Using WB-CT/MRI and Synthetic WB-CT - The AuToMI Project

NCT ID: NCT04976205

Last Updated: 2026-01-21

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

60 participants

Study Classification

INTERVENTIONAL

Study Start Date

2021-06-15

Study Completion Date

2025-08-08

Brief Summary

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Total Body Irradiation (TBI) was shown to help in providing immunosuppression that facilitates the donor transplant acceptance. Randomized trials demonstrated that conditioning regimens to bone marrow transplantation (BMT) including TBI have produced better survival rates than chemo-only regimens. The TBI target is represented by the whole BM, and eventually the whole lymphatic system, liver, spleen. The increased life expectancy revealed the occurrence of important toxicities because of full doses received by organs at risk (OARs) and this limited the use of TBI. Many groups have explored the possibility of sophisticated techniques for reducing the dose to healthy tissues while increasing the dose to the BM. These newer approaches aim to generate total marrow (lymph-node) irradiation (TMI/TMLI), sparing as much as possible non-skeletal and non-lymphoid structures.

Actually, the time required to optimize a TMI/TMLI plan is 10 days. Therefore, the simulation Computed Tomography (CT) is performed many days before the BMT. Furthermore, the lymph-nodes are defined only on CT images.

Detailed Description

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Total Body Irradiation (TBI) was shown to help in providing immunosuppression that facilitates the donor transplant acceptance. Moreover, TBI plays a role in the annihilation of malignant cells, and may also deplete normal hematopoietic stem cells, thus helping the donor marrow cells to repopulate the bone marrow (BM). Randomized trials demonstrated that conditioning regimens to BMT including TBI have produced better survival rates than chemo-only regimens.

The TBI target is represented by the whole BM, and eventually the whole lymphatic system, liver, spleen. Usually, a very simple geometry is adopted, with patient positioned on a dedicated couch at 3-4 meters away from the linear accelerator to fully cover the target with a single beam, avoiding field junctions.

The increased life expectancy revealed the occurrence of important toxicities because of full doses received by organs at risk (OARs) and this limited the use of TBI as stated by the 2018 ILGROG guidelines. Many groups have, therefore, explored the possibility of sophisticated techniques for reducing the dose to healthy tissues while increasing the dose to the BM. These newer approaches aim to generate total marrow (lymph-node) irradiation (TMI/TMLI), sparing as much as possible non-skeletal and non-lymphoid structures.

Preliminary clinical data on phase I/II trials support the use of TMI/TMLI as part of conditioning for BMT for relapsed-refractory acute leukemia patients and multiple myeloma. However, TMI/TMLI adoption is still very limited to few skilled hospitals due to the extreme difficulty in the planning that needs many days.

The evaluation of TMI/TMLI with Volumetric Modulated Arc Therapy (VMAT) was started in our institute in 2009 and we treated around 90 patients in 10 years.

VMAT-TMI/TMLI requires multiple arcs from isocenters with different positions to fully include the patient length. Therefore, many field junctions between arcs with different isocenters should be managed. Furthermore, the CT length does not allow to acquire the patient in a single CT scan. Two CT series must be acquired and co-registered.

Actually, the time required to optimize a TMI/TMLI plan is 10 days. Therefore, the simulation Computed Tomography (CT) is performed many days before the BMT. Furthermore, the lymph-nodes are defined only on CT images.

Deep learning (DL) artificial intelligence (AI) algorithms in medical imaging and RT are rapidly expanding. DL focused on lesion detection and classification by features extraction. Image segmentations using fully convolutional network (FCN), holistically nested network (HNN) or other customized network architectures were implemented in many regions.

Over the past decades, the use of magnetic resonance imaging (MRI) to support RT has increased. MRI provides excellent soft-tissue imaging that could improve the target definition. The lymph-nodes contouring, based on MRI, will result in smaller target, enabling a better sparing of healthy tissues. Moreover, MRI significantly reduces inter/intra-observer contouring variability. At this aim, new generation MRI consoles with larger bore size, flat tabletops and dedicated imaging protocols with reduced image distortion to \<1 mm were developed. Moreover, newly developed gradient-echo 3D sequences, and dedicated coils, can be used for producing a whole body WB-MRI acquisition in a few minutes. Furthermore, synthetic CT from MRI was proposed and implemented in some regions (i.e. brain and prostate) to substitute the CT for providing electron density information for dose planning calculation.

Conditions

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Hematological Disease

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

NONE

Study Groups

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TMI/TMLI

The standard planning optimization for TMI/TMLI preview a two-free-breathing-CT scan without contrast will be performed for simulation at day -15(-10) to the BMT. The same day a WB-MRI will be acquired for lymph-nodes delineation. WB-MRI scans will be performed using a 1.5T MR scanner. The two CT will be co-registered to the WB-MRI.

CTV will be manually defined as the bones excluding mandible and hands (CTVBones), the spleen (CTVSpleen), and lymph nodes (CTVLN) using both MRI and CT images. The day -3 (4) to the BMT, further two-CT series will be acquired and co-registered to the first CTs for dose verification. Pre-treatment quality assurance (QA) will be performed the day before the treatment using the standard internal procedure.

The treatment will be performed the day before the BMT.

Group Type EXPERIMENTAL

Total Marrow (Lymph-node) Irradiation

Intervention Type RADIATION

To the standard procedure for TMI/TMLI target definition, based on simulation WB-CT acquired 10/15 days before BMT, we acquire: WB- magnetic resonance imaging (MRI) the same day of the simulation WB-CT. A verification WB-CT will be performed 3/4 days before the delivery. Plans will be optimized with Volumetric Modulated Arc Therapy (VMAT) technique.

Interventions

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Total Marrow (Lymph-node) Irradiation

To the standard procedure for TMI/TMLI target definition, based on simulation WB-CT acquired 10/15 days before BMT, we acquire: WB- magnetic resonance imaging (MRI) the same day of the simulation WB-CT. A verification WB-CT will be performed 3/4 days before the delivery. Plans will be optimized with Volumetric Modulated Arc Therapy (VMAT) technique.

Intervention Type RADIATION

Eligibility Criteria

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Inclusion Criteria

* Written, signed informed consent
* Adult patients aged ≥18 years
* Diagnosis of Hematological disease
* Eligibility for allogeneic stem cell transplantation as center guidelines
* TMI/TLI as part of the conditioning regimen

Exclusion Criteria

\- Conditioning regimen including only chemotherapeutic agents
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Istituto Clinico Humanitas

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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IRCCS Humanitas Research Center

Rozzano, Milano, Italy

Site Status

Countries

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Italy

References

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Dei D, Lambri N, Sopranzi C, Galdieri C, Franzese C, Scorsetti M, Mancosu P. Impact of reduced interval from simulation CT to treatment delivery on dosimetric and positioning accuracy for total marrow lymph-node irradiation. Strahlenther Onkol. 2025 Jun 13. doi: 10.1007/s00066-025-02415-x. Online ahead of print.

Reference Type DERIVED
PMID: 40512423 (View on PubMed)

Other Identifiers

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2928

Identifier Type: -

Identifier Source: org_study_id

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