Breast Cancer Clinical Trial
— LLTECHBreastOfficial title:
Performance Study of BIOPSY SCANNER LLTECH© Technology in the Immediate Diagnosis of Breast Cancer
Breast cancer is a frequent pathology and the speed of initial diagnosis makes it possible to
improve the course of care and to reduce the anxiety of the patients. For a complete
assessment, several biopsies may be necessary, including lymph node biopsies. Once the
histological sample has been taken, a preparation is necessary (time consuming technician)
then a reading by a pathologist requiring at least 48-72h. Cytology allows immediate
diagnosis, but it requires the presence of a pathologist in the collection room. Finally,
some biopsies can be non-contributory (if there is not enough tissue removed) and require new
samples. A tool allowing immediate control of the tissue and an initial diagnosis without
mobilizing the pathologist (who will make the result complete with immunohistochemistry)
would make it possible to anticipate the next course of care and facilitate treatment. The
BIOPSY SCANNER LLTECH © technology would allow images on fresh unprepared tissue to obtain
images allowing immediate diagnosis by a non-pathologist, the same tissue could then be
technical for a complete analysis by the pathologist.
The investigators propose a study evaluating the diagnostic capacities by non pathologists
from images obtained by the BIOPSY SCANNER LLTECH © technology on breast and lymph node
biopsies. Based on this study, an atlas on breast lesions could be created to allow a broader
evaluation of this technology in daily practice in diagnostic of breast pathology.
| Status | Recruiting |
| Enrollment | 204 |
| Est. completion date | September 15, 2021 |
| Est. primary completion date | September 15, 2021 |
| Accepts healthy volunteers | No |
| Gender | Female |
| Age group | 18 Years and older |
| Eligibility |
Inclusion Criteria: - Patients over 18 years old requiring a breast biopsy for an birads 4 or 5 nodular radiological lesion or lymph node for a lymph node judged to be radiologically suspect (cortex thickened by more than 3 mm) Exclusion Criteria: - Patients under 18 |
| Country | Name | City | State |
|---|---|---|---|
| France | Hôpital de la Pitié Salpêtrière | Paris |
| Lead Sponsor | Collaborator |
|---|---|
| Assistance Publique - Hôpitaux de Paris |
France,
| Type | Measure | Description | Time frame | Safety issue |
|---|---|---|---|---|
| Primary | Positive predictive value (PPV) | Positive predictive value (PPV) of the diagnosis of breast cancer by the analysis of images BIOPSY SCANNER LLTECH © carried out by a senior radiologist taking as reference the results provided by histology on tissue section. | At the end of inclusion time | |
| Secondary | Reproductibility | Comparison of sensitivity, specificity, positive predictive value and negative predictive value of the diagnosis of breast cancer by the analysis of BIOPSY SCANNER LLTECH © images by a junior radiologist versus senior radiologist versus pathologist versus surgeon | At the end of inclusion time | |
| Secondary | Efficiency for each histologic type | Comparison of sensitivity, specificity, positive predictive value and negative predictive value of the diagnosis of breast cancer by the analysis of BIOPSY SCANNER LLTECH © images according to the histological characteristics of the tumor (according to grade, according to luminal A / luminal B profile / triple negative / HEr2 3+) | At the end of inclusion time | |
| Secondary | Efficiency compared between breast tissue and lymph node | Comparison of the sensitivity, specificity, positive predictive value and negative predictive value of the diagnosis of breast cancer by the analysis of BIOPSY | At the end of inclusion time | |
| Secondary | Progression curve | Number of samples required to reach the objective of the same diagnostic capacity as the pathologist from these images | At the end of inclusion time | |
| Secondary | Image atlas | Establishment of an image atlas facilitating the subsequent use of this technology by non-pathologists | At the end of inclusion time | |
| Secondary | Image recognition algorithm | Implementation of an image recognition algorithm for automated diagnosis | At the end of inclusion time |
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