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iToBoS: Clinical Data Acquisition Study (iToBoS)

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ClinicalTrials.gov Identifier: NCT05075356
Recruitment Status : Not yet recruiting
First Posted : October 12, 2021
Last Update Posted : October 12, 2021
Sponsor:
Collaborators:
Universitat de Girona
Fundacion Clinic per a la Recerca Biomédica
University of Trieste
Trilateral Research Limited
Robert Bosch Espana Fabrica
IBM Israel - Science and Technology Ltd
Information provided by (Responsible Party):
The University of Queensland

Brief Summary:

The (overarching) iToBoS Project involves 18 research partners spanning the European Union (including UK and Israel), and 1 Australian partner. The overall aim is to develop an AI assisted diagnostic platform for the early detection of melanoma.

The Clinical Data Acquisition Study (this study) will recruit 600 participants across 3 international sites (Brisbane, Italy, and Spain). The primary objective is to compare the quality and resolution of conventional dermoscopic images of skin lesions with the full-body images captured by the iToBoS imaging system. Secondary objectives are to collect imaging, clinical and genetic data across the three sites, to create labelled datasets for use in training the iToBoS AI component. Also, to refine and develop a holistic melanoma risk score method to be used for the iToBoS system. Lastly, to assess safety of the iToBoS system.

At study site we will aim to recruit 200 participants stratified by risk (of melanoma) categories (low/normal, high, and ultra-high). Participants will be required to attend 3 study visits (months 0, 6 and 12), for total body imaging with the iToBoS system, and dermoscopic images of individual moles. Genetic research and clinical testing are an optional part of the study.


Condition or disease Intervention/treatment Phase
Melanoma Device: The intelligent total body scanner (iToBoS) Not Applicable

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Study Type : Interventional  (Clinical Trial)
Estimated Enrollment : 600 participants
Allocation: N/A
Intervention Model: Single Group Assignment
Intervention Model Description: All participants will follow the same protocol (single arm).
Masking: None (Open Label)
Primary Purpose: Prevention
Official Title: iToBoS: Intelligent Total Body Scanner for Early Detection of Melanoma - Clinical Data Acquisition Study
Estimated Study Start Date : October 1, 2022
Estimated Primary Completion Date : June 30, 2024
Estimated Study Completion Date : June 30, 2024

Resource links provided by the National Library of Medicine

MedlinePlus Genetics related topics: Melanoma
MedlinePlus related topics: Melanoma

Arm Intervention/treatment
Experimental: Single participant arm

The iToBoS intervention is a total body imaging device, to image the total skin surface in order to detect and monitor for signs of skin cancer.

The imaging process involves laying down on a bed that has a framework of cameras arched over it. The imaging process takes less then 10 minutes, and requires the participant to lay in two different positions (face-up and face-down).

The study visit also includes individual dermoscopic images taken of certain moles on the skin. This is done in combination with a clinical skin examination. Participants are given the option of providing a saliva sample for genetic research. Participants are then asked to complete a series of questionnaires.

There a three visits in total (month 0, 6 and 12), in which these procedures are repeated (except for saliva sample).

Device: The intelligent total body scanner (iToBoS)

The intelligent total body scanner (iToBoS) device will be an AI diagnostic platform for early detection for melanoma, which includes a novel total-body high-resolution scanner and a Computer Aided Diagnostics (CAD) tool. The prototype iToBoS imaging device used in this study, will not have the integrated CAD system.

The device consists of a horizontal bed on which the participant would lie on. The bed will slide under a series of 5 arc shaped rails that have a total of 15 vision units mounted on rails (3 vision units per arc). The vision units incorporate high-resolution cameras and LED lighting system. When imaging is initiated by an operator, the vision units systematically move along the arch rails taking numerous images capturing majority of the skin surface. The imaging process will take approx. 10 minutes.

Purpose built software will be used to stitch images together to create a body avatar on which skin lesions can be viewed and monitored with.

Other Name: iToBoS




Primary Outcome Measures :
  1. iToBoS image quality assessment [ Time Frame: Baseline (Month 0) ]
    The primary outcome measure of this study is the assessment of image quality of total-body photography taken with the iToBoS system. A clinical and quantitative comparison of conventional dermoscopy images of individual lesions with iToBoS images will be systematically assessed by a panel of dermatologically trained clinicians and research assistants. The panel will be asked to independently assess the iToBoS image and dermoscopic images as acceptable or not acceptable. Three panel members will assess each image, with consensus being considered with agreement of 2 or more. The order of the images presented to each panel member will be randomised.


Secondary Outcome Measures :
  1. Creation of labelled datasets for AI training [ Time Frame: Baseline (Month 0) ]
    The secondary outcome measure will include classification, by field experts, of dermoscopic images into 9 diagnostic categories (e.g., naevus, melanoma, basal cell carcinoma, squamous cell carcinoma, actinic keratosis & intraepidermal squamous cell carcinoma, benign keratosis, dermatofibroma, vascular tumour, and other). The field experts will also be asked to provide a binary classification of suspicious or benign. Sequential dermoscopy images of the same lesion taken over different visits will additionally be assessed for clinically significant phenotypic change (yes/no). This dataset of labelled lesion images will be used to train the iToBoS artificial intelligence algorithms for development of computer aided diagnosis.

  2. Refinement of a holistic risk score algorithm [ Time Frame: Month 12 ]
    An additional secondary outcome measure is the holistic risk score algorithm developed as part of the wider iToBoS project, which will be tested on the complete prospective dataset from the initial visits of all 600 individuals in three centres. The ability of the model to discriminate between case and control individuals will be assessed. In addition, the net reclassification improvement index will be calculated to quantify the sensitivity and specificity of model classification. These factors will enable assessment as to the relative contribution of individual risk factors in accurate risk stratification. The goal of this task will be to refine the clinical protocol for stratification of participants into low/average, high and ultra-high-risk categories to be used in a subsequent clinical validation study (separate protocol).

  3. Safety Assessment [ Time Frame: At completion of study (Month 12) ]

    A protocol for recording any Adverse Events, and Serious Adverse Events is established.

    Adverse events are catogrised by the nature of the event, the intensity (mild/moderate/severe), the duration, and the relatedness to the investigational device (probably/possibly/not related), and the outcome is recorded (recovered/resoved, recovering/resolving, not recovered/not resolved, recovered with sequelae, fatal, unknown).

    AEs and SAEs are not expected in the study, and therefore any reported AEs and SAEs will be reviewed by the trial investigator within 48 hours.


  4. Detecting change in lesions imaged (from baseline to month 12) [ Time Frame: At completion of the study (Month 12) ]

    Images of the same skin lesions taken at baseline, compared to the participant's last study visit at 12 months will be used to detect any changes in the lesion. This will be important in training the iToBoS AI component to detect changes in skin lesions. An expert panel of clinicians will classify subsequent images as 'not changed', or 'changed'.

    Cohen's Kappa will be used to compare agreement between the lesion classification of change vs. no change.




Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   Yes
Criteria

Inclusion Criteria:

  1. Aged 18 years or older
  2. Able to provide written informed consent
  3. Willing to attend 3 clinical visits over a 12-month period
  4. Willing to provide a genetic sample (optional)
  5. Willing to follow the clinical procedures (e.g. no physical restrictions from imaging process)
  6. Have a BMI between 18.5 to 40 kg/m2
  7. Have a height between 140 - 190 cm
  8. Have a thorax height (participant lying face up) of 20 - 45 cm
  9. Have an elbow to elbow width (breadth) of 40-50cm

Exclusion Criteria:

  1. Have a pacemaker
  2. Are pregnant, or planning to become pregnant
  3. Any condition in which the investigator's opinion may adversely affect the participant's ability to complete the study, or its measures, or which may pose significant risk to the participant.

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT05075356


Contacts
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Contact: Clare A Primiero, BSc +61 7 344 37496 c.bover@uq.edu.au
Contact: Katie Lee, BSci +61 7 344 37482 k.lee5@uq.edu.au

Sponsors and Collaborators
The University of Queensland
Universitat de Girona
Fundacion Clinic per a la Recerca Biomédica
University of Trieste
Trilateral Research Limited
Robert Bosch Espana Fabrica
IBM Israel - Science and Technology Ltd
Investigators
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Principal Investigator: Peter Soyer, MD The University of Queensland
Study Director: Rafael Garcia, PhD Universitat de Girona
Additional Information:
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Responsible Party: The University of Queensland
ClinicalTrials.gov Identifier: NCT05075356    
Other Study ID Numbers: D1.4
First Posted: October 12, 2021    Key Record Dates
Last Update Posted: October 12, 2021
Last Verified: September 2021
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: Yes
Plan Description:

The iToBoS consortium will organise two competitive 'skin image analysis' challenges where groups can participate in solving new problems on: 1) lesion detection and boundary segmentationTotal Body Photography images, and 2) on lesion classification using minimal (non-identifying) participant clinical data, genotyping results, and the lesion images extracted from Total Body Photography images.

To facilitate these challenges we are sharing limted patient data (non-identifiable images, minimal clinical information, a genetic risk score, and minimal genotype information).

Supporting Materials: Study Protocol
Time Frame: These challenges will run 2025-2026
Access Criteria:

The datasets will be shared in international conferences, for example MICCAI (Medical Image Computing and Computer Assisted Intervention) or similar, where the challenge and corresponding workshop will run.

The details are not finalised at this stage.


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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Product Manufactured in and Exported from the U.S.: No
Keywords provided by The University of Queensland:
Total Body Imaging
Diagnostic
Artificial Intelligence
Skin Examination
Additional relevant MeSH terms:
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Melanoma
Neuroendocrine Tumors
Neuroectodermal Tumors
Neoplasms, Germ Cell and Embryonal
Neoplasms by Histologic Type
Neoplasms
Neoplasms, Nerve Tissue
Nevi and Melanomas