Ignite Creation Date:
2024-05-06 @ 8:21 PM
Last Modification Date:
2024-10-26 @ 3:25 PM
Study NCT ID:
NCT06342934
Status:
COMPLETED
Last Update Posted:
2024-04-02
First Post:
2024-01-15
Brief Title:
Radiomics and Machine Learning in the Diagnosis of Ovarian Masses
Sponsor:
Fondazione IRCCS Istituto Nazionale dei Tumori Milano
Organization:
Fondazione IRCCS Istituto Nazionale dei Tumori Milano
Study Overview
Official Title:
Multicentric Evaluation of the Adoption of Radiomics and Machine Learning in the Diagnosis of Ovarian Masses
Status:
COMPLETED
Status Verified Date:
2024-01
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
Multi-AROMA
Brief Summary:
The correct differential diagnosis between benign and malignant adnexal masses is the main goal of preoperative ultrasound diagnostics and is very important to plan the correct treatment for the patient in terms of surgical team gynecologist oncologist or benign pathology center surgical access laparoscopy laparotomy and type of surgery conservative demolitive
Several ultrasound models have been developed to help gynecologists define the risk of malignancy of adnexal masses In order to use the predictive models the examiner had to collect certain ultrasound features of the lesion which integrated with the patients clinical and or biochemical characteristics provided a risk of malignancy of the mass
Recently radiomics is emerging as an interesting tool to be applied to diagnostic imaging computed tomography magnetic resonance and even ultrasound Radiomics is the evaluation of images through complex software that allows to read the intrinsic characteristics of the tissue identifying aspects that are not visible by subjective interpretation of the operator in a fully automated and therefore reproducible way
Radiomics applied to artificial intelligence for the creation of predictive models represents an interesting tool to overcome the limitations of previous models at least partly dependent on the operators experience
Among the serous ovarian cancer those with BRCA gene mutation represent an interesting subgroup and are characterized by a different pathophysiological history than wild type tumors due to greater chemosensitivity and the possibility of targeted treatment with antiangiogenic drugs and PARP-inhibitors
The application of radiomics to preoperative ultrasound images could identify BRCA mutated tumors before surgical planning radiogenomic analysis and allow a personalized treatment
The aim of the study is to validate a predictive model to define the risk of malignancy of adnexal masses that the investigators developed at the Fondazione IRCCS Istituto Nazionale dei Tumori di Milano
The model based on the integration of radiomics and artificial intelligence uses complex software capable of reading the ultrasound images in a completely automatic way and is able to estimate the risk of malignancy of the mass
If the patient decide to participate in the clinical study the patient will undergo transvaginal ultrasound eventually supplemented by transabdominal ultrasound in case of large adnexal masses if the patients are virgo or if the patients will refuse transvaginal approach for any reason This exam is part of the routine preoperative evaluation for adnexal pathology and therefore the patients dont have to undergo any additional clinical biochemical or imaging examination according to national and international guidelines
Thereafter the images stored during the preoperative ultrasound will be exported in anonymous format from the ultrasound system and sent to the coordinating center Fondazione IRCCS Istituto Nazionale dei Tumori di Milano There images will be submet to radiomic analysis through the application of a dedicated software that will allow to evaluate the intrinsic characteristics of the tissue according to different parameters shape intensity grade of heterogeneity and many others of the pixels gray dots that constitute the ultrasound image
This analysis once validated will provide clinicians an additional tool to identify malignant adnexal masses prior to surgery
If the final histological diagnosis is of serous epithelial ovarian cancer through the use of the same radiomics software described above the investigators will try to identify the intrinsic characteristics of the tissue associated with the presence or absence of the BRCA 1 or 2 mutation
Several ultrasound models have been developed to help gynecologists define the risk of malignancy of adnexal masses In order to use the predictive models the examiner had to collect certain ultrasound features of the lesion which integrated with the patients clinical and or biochemical characteristics provided a risk of malignancy of the mass
Recently radiomics is emerging as an interesting tool to be applied to diagnostic imaging computed tomography magnetic resonance and even ultrasound Radiomics is the evaluation of images through complex software that allows to read the intrinsic characteristics of the tissue identifying aspects that are not visible by subjective interpretation of the operator in a fully automated and therefore reproducible way
Radiomics applied to artificial intelligence for the creation of predictive models represents an interesting tool to overcome the limitations of previous models at least partly dependent on the operators experience
Among the serous ovarian cancer those with BRCA gene mutation represent an interesting subgroup and are characterized by a different pathophysiological history than wild type tumors due to greater chemosensitivity and the possibility of targeted treatment with antiangiogenic drugs and PARP-inhibitors
The application of radiomics to preoperative ultrasound images could identify BRCA mutated tumors before surgical planning radiogenomic analysis and allow a personalized treatment
The aim of the study is to validate a predictive model to define the risk of malignancy of adnexal masses that the investigators developed at the Fondazione IRCCS Istituto Nazionale dei Tumori di Milano
The model based on the integration of radiomics and artificial intelligence uses complex software capable of reading the ultrasound images in a completely automatic way and is able to estimate the risk of malignancy of the mass
If the patient decide to participate in the clinical study the patient will undergo transvaginal ultrasound eventually supplemented by transabdominal ultrasound in case of large adnexal masses if the patients are virgo or if the patients will refuse transvaginal approach for any reason This exam is part of the routine preoperative evaluation for adnexal pathology and therefore the patients dont have to undergo any additional clinical biochemical or imaging examination according to national and international guidelines
Thereafter the images stored during the preoperative ultrasound will be exported in anonymous format from the ultrasound system and sent to the coordinating center Fondazione IRCCS Istituto Nazionale dei Tumori di Milano There images will be submet to radiomic analysis through the application of a dedicated software that will allow to evaluate the intrinsic characteristics of the tissue according to different parameters shape intensity grade of heterogeneity and many others of the pixels gray dots that constitute the ultrasound image
This analysis once validated will provide clinicians an additional tool to identify malignant adnexal masses prior to surgery
If the final histological diagnosis is of serous epithelial ovarian cancer through the use of the same radiomics software described above the investigators will try to identify the intrinsic characteristics of the tissue associated with the presence or absence of the BRCA 1 or 2 mutation
Detailed Description:
None
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None