Clinical Trial Details
— Status: Completed
Administrative data
| NCT number |
NCT05172232 |
| Other study ID # |
CIV-21-12-038346 |
| Secondary ID |
|
| Status |
Completed |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
May 2, 2022 |
| Est. completion date |
January 23, 2023 |
Study information
| Verified date |
February 2023 |
| Source |
Linkoeping University |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
Dermalyzer is a device intended to be used as a decision support system for assessing
cutaneous lesions suspected of being melanomas. The input from the device is not intended to
be used as the sole source of information for diagnosis. Intended to be used by medical
professionals. The service does not provide any other diagnosis. The study is a
pre-marketing, prospective, confirmatory, first in clinical setting, pivotal multi-centre,
non-interventional clinical investigation to evaluate the clinical safety, performance and
benefit of Dermalyzer in patients with cutaneous lesions where malignant melanoma (MM) cannot
be ruled out.
Primary objective: The primary objective of the investigation is to determine the diagnostic
precision of the device; to answer at which level the AI tool Dermalyzer can identify
malignant melanomas among cutaneous lesions that are assessed in clinical use due to any
degree of malignancy suspicion.
Secondary objectives: A) To evaluate usability and applicability in clinical praxis of
Dermalyzer by users (medical professionals), B)To gain an increased knowledge and
understanding of how digital tools enhanced co-artificial intelligence can assist physicians
with the right support for an earlier diagnosis of malignant melanoma.
Exploratory objective: To explore health economic aspects of improved diagnosis support
Methods: The subjects will be included from around 30 primary care centers in Sweden. If the
subject's lesion(s) is suspected of melanoma or melanoma cannot be ruled out, the subject is
asked to participate in the investigation. The investigator examines the subject's lesion(s)
and makes the clinical assessment of the subject lesion(s) based on established clinical
decision algorithms The investigator takes dermoscopy images according to standard of care
and archives the image(s) according to clinical routine. The investigator decides on action,
based on his or her MM suspicion (excision at the primary care center or referral for
excision or referral to a dermatologist for further assessment). The investigator takes
images of the lesion(s) again, this time with a mobile phone, containing the AI software,
connected to a dermatoscope, and follows the on-screen instructions. The image is processed
by the AI and the results are visible on the screen within seconds. The investigator records
how he considers that the degree of suspicion of MM (higher vs lower) would have been
affected by the AI SW result if it had been the governing body for the treatment. At study
follow-up, the final tumor diagnosis from the histopathology results (melanoma/non melanoma)
or by dermatologist assessment (if stated as undoubtedly benign), the degree of agreement
between the true final diagmosis and the outcome of the AI decision support is determined,
and the diagnostic accuracy in distinguishing melanoma from non-melanoma, in terms of
sensitivity and specificity as well the positive and predictive value. The corresponding
comparison is performed from the examining investigators estimated clinical degree of
suspicion. The clinical investigation will collect information from the users, how
participating users (investigators at the site) experience the usability of the AI decision
support and attaching applications, from short surveys including the validated System
Usability Scale.
Description:
Background: Malignant melanoma is a worldwide health issue of concern, of increasing
incidence. Early melanoma detection is crucial for survival and prognosis. Dermalyzer is a
device intended to be used as a decision support system for assessing cutaneous lesions
suspected of being melanomas, based on artificial intelligence (AI), often referred to as
"machine learning". The input from the device is not intended to be used as the sole source
of information for diagnosis. Intended to be used by medical professionals. The service does
not provide any other diagnosis.
Study aims/objectives:
Primary objective: The primary objective of the investigation is to determine the diagnostic
precision of the device; to answer at which level the AI tool Dermalyzer can identify
malignant melanomas among cutaneous lesions that are assessed in clinical use due to any
degree of malignancy suspicion.
Secondary objectives: A) To evaluate usability and applicability in clinical praxis of
Dermalyzer by users (medical professionals), and B) To gain an increased knowledge and
understanding of how digital tools enhanced co-artificial intelligence can assist physicians
with the right support for an earlier diagnosis of malignant melanoma.
Exploratory objective: To explore health economic aspects of improved diagnosis support
Exploratory endpoints
Materials & methods:
The subjects will be included from around 30 primary care centers in Sweden. If the subject's
lesion(s) is suspected of melanoma or melanoma cannot be ruled out, the subject is asked to
participate in the investigation. The investigator examines the subject's lesion(s) and makes
the clinical assessment of the subject lesion(s) based on established clinical decision
algorithms (such as "Chaos & clues", "3- or 7-point checklist", or the ABCDE concept) of
whether there is a suspicion of MM, according to the usual clinical routine (also includes
very low suspicion of MM but cannot be completely dismissed). The investigator takes
dermoscopy images according to standard of care and archives the image(s) according to
clinical routine. The investigator decides on action, based on his or her MM suspicion
(excision at the primary care center or referral for excision or referral to a dermatologist
for further assessment). If the subject has agreed to participate in the investigation, the
investigator indicates in the CRF the clinical suspicion level of MM, and decided action. The
investigator takes images of the lesion(s) again, this time with a mobile phone, containing
the IMD AI SW, connected to a dermatoscope, and follows the on-screen instructions. The image
is processed by the AI SW and the results are visible on the screen within seconds. A unique
auto generated code number is also presented. The code number is registered on the enrollment
log and in the CRF. The investigator records how he considers that the degree of suspicion of
MM (higher vs lower) would have been affected by the AI SW result if it had been the
governing body for the treatment.
When the subject has been fully examined and receives the final tumor diagnosis from the
histopathology/PAD results or dermatologist assessment (melanoma/non melanoma), the degree of
agreement between the PAD and the outcome of the AI SW decision support is calculated with
the Kappa-analysis and the diagnostic accuracy to be able to distinguish melanoma from
non-melanoma in the form of sensitivity and specificity as well the positive and predictive
value. The corresponding comparison is performed from the examining investigators estimated
clinical degree of suspicion, as well as the diagnostic accuracy when both the PAD and the AI
decision support are wigheted together (ei in cases where the investigator and the decisions
support are in agreement in their assessment). The clinical investigation will collect
information from the users, how participating users (investigators at the site) experience
the usability of the AI SW decision support and attaching applications, from short surveys
including the validated System Usability Scale.
