Neoplasms

Skin and Connective Tissue Diseases

All Conditions

Breast Neoplasms

Breast Diseases

Skin Diseases

Gregory J Czarnota, PhD, MD

Gregory Czarnota, PhD, MD

This work explores the possibility of using ultrasound imaging and spectroscopy as a way of monitoring cell death, hence, tumour response to treatment. The hypothesis here is that it can be used as a way of monitoring early response to cancer treatment and predicting which patients continue on in their therapy to have a complete pathological response as a primary endpoint and tumour size decrease as a secondary endpoint. If this work is successful it could be used in the future early on in a cancer patient's treatment to predict whether or not a course of chemotherapy or radiotherapy is going to be successful. For example, in patients in which the analysis indicates a poor response the chemotherapy regimen could be changed to a more efficacious one or for those receiving radiotherapy predicted to have a poor response a radiosensitizing agent could be used to improve outcome.

The primary objective in this study is to identify optimal ultrasound spectroscopy parameters that can be used as an early predictor of pathological complete or partial response in women with locally advanced breast cancer receiving treatment with chemotherapy or combined modality chemotherapy and radiotherapy. A secondary objective is to perform an inter-user variability comparison by comparing second site data analysis outcomes with central co-coordinating site data analysis. The overarching goal of this research is to transform the delivery of neoadjuvant chemotherapy using quantitative ultrasound, which is non-invasive, inexpensive and portable to assess breast cancer therapies through functional imaging, in which tumour cell death is detected. By detecting cell death early in a treatment on the order of hours to days, rather than traditional anatomical assessments that take place weeks to months after the completion of therapy, ineffective therapies could be switched to more efficacious treatments or aggressive salvage therapy which has shown to already benefit patients. This has the potential of improving survival in addition to sparing patients unnecessary side effects of treatments that may span weeks to months. The investigators will use these quantitative methods to evaluate treatments with neoadjuvant chemotherapy in women with locally advanced breast cancer. This investigation will track the spatio-temporal changes in quantitative ultrasound surrogates of treatment response during neoadjuvant chemotherapy of locally advanced breast cancer and use these parameters to adapt clinical treatment. The study specifically will expand on single- institution research underway and involve a second clinical site. Data will be independently collected and analysis carried out at that site and at the co-ordinating site for comparison evaluating technology-use feasibility and reproducibility of results.

Ultrasound Imaging and Spectroscopy as Early Indicators of Locally-Advanced Breast Cancer Response

Pilot Investigation of Ultrasound Imaging and Spectroscopy as Early Indicators of Locally- Advanced Breast Cancer Response to Neoadjuvant Treatment

Correlate changes in ultrasound backscatter parameters obtained throughout the course of treatment with pathological complete or partial response

Comparing second site data analysis outcomes with central co-coordinating site data analysis

Sunnybrook Health Sciences Centre

Radiation Oncologist and Clinician Scientist

Schontal Halstead

Gregory J Czarnota, Phd, MD

Our objective in this study is to identify an optimal set of quantitative ultrasound parameters that can be used, non-invasively, to characterize breast masses with high accuracy, as determined histopathologically. Breast cancer is the most frequent form of non-epithelial cancer diagnosed in women, with approximately 1.5 million new cases diagnosed annually worldwide. Accurate diagnosis and characterization of disease play an important role in therapy planning for breast cancer treatment. Currently, the gold standard method of tumour diagnosis is pathological examination of core biopsy specimens. However, the invasive core biopsies can cause post-surgical complications. Besides, some lesions require repeat biopsy due to sampling errors during the initial biopsy. Also X-ray mammography and ultrasound B-mode images, which are used by radiologists for breast examination, lack reliable information about micro-structural properties of tissues. There is an urgent need of a non-invasive imaging modality that can provide rapid and quantitative information for breast tumour characterization, in real time and at the patient bed. The main goal, as described above, is to select the best quantitative ultrasound parameters that can facilitate breast cancer characterization, non-invasively.

This project is an observational/early validation study in human subjects that will use ultrasound imaging and spectroscopy to characterize suspected breast cancers. Patients will be imaged with ultrasound, and the acquired data will be analyzed using quantitative ultrasound techniques, in conjunction with textural analysis on generated parametric images. Results of quantitative ultrasound data analysis for these breast lumps will be compared to and correlated with their histopathological characteristics from pathology reports on core biopsy specimens, surgery reports, or radiology reports, available from patient charts. From this data we will potentially estimate the best hybrid ultrasound-based biomarker that can characterize suspected breast cancers, noninvasively.

Investigation of Ultrasound Imaging and Spectroscopy for Characterizing Breast Masses

Correlate quantitative ultrasound parameters obtained using spectroscopic techniques, in conjunction with textural analysis on generated parametric images, to the histopathological characteristics from pathology reports on core biopsy specimens, surgery reports, or radiology reports.

Correlating the results of ultrasound-based breast cancer characterization.

Urinary Tract, Sexual Organs, and Pregnancy Conditions

Prostatic Neoplasms

Genital Neoplasms, Male

Urogenital Neoplasms

Genital Diseases

Genital Diseases, Male

Urogenital Diseases

Prostatic Diseases

Male Urogenital Diseases

Infusion of Indocyanine Green 0,25 mg/Kg 24h before prostatic surgery

intravenous injection (0,25mg/kg) of the indocyanine green 24h before prostatic surgery.

indocyanine green infusion

Nicolas MOTTET, PhD

Prostate cancer, with more than 70,000 new cases and 8900 deaths a year in France, is a major public health problem. Until 28% of patients treated with surgery will present a positive surgical margin resulting in an incomplete clearance of the tumoral process and exposing so the patient at a local, systemic recurrence and increased morbidity. An increasing number of international publications have shown (ICG) was interesting for the detection of the sentinel lymph node, in the surgery of tumors of type hepatocarcinoma and liver metastases from colorectal diseases, but also in the surgery of the kidney, bladder or breast. ICG has affinity for tumor and tissues around the tumor related to micro-vascular histology for a localized and specific deposit (EPR effect).

The detection of ICG 's deposits is now possible with to the use of a device which allow to visualize the infra-red fluorescence (NIR; Near Infra-Red) for objects larger than 0.15 mm. Thanks to this feature, the location of residual tumor tissue when performing a radical prostatectomy could be made much easier.

The ability of ICG to detect a surgical margin positive intraoperatively has never be evaluated. We want to perform a monocentric prospective ex-vivo pilot in order to evaluate the diagnostic performance of fluorescence in the detection of surgical margins compared to pathologic analysis. This study will be conducted in 37 patients operated on for a radical prostatectomy after systemic injection of 0, 25 mg/Kg of ICG 24 h before the surgery. The fluorescence analysis will be performed in the operation room and then specimen will be sent to the laboratory for an analysis as usual. Two pieces of prostate will be prelevated according to a protocol. The histopathological procedure will be performed without knowledge of fluorescence analysis. Except the ICG injection the medical procedure won't be changed.

Interest of Indocyanine Green in Neoplastic Prostatic Tissue

Interest of Indocyanine Green in the Neoplastic Prostatic Tissue Characterization and the Peroperative Surgical Margins Detection During a Radical Prostatectomy.

Sensitivity (true positive) of the fluorescence due to indocyanine green to detect neoplasm tissue in prostatic biopsy compared to histological analysis

Specificity (true negative) of the fluorescence due to indocyanine green to detect neoplasm tissue in prostatic biopsy compared to histological analysis

Centre Hospitalier Universitaire de Saint Etienne

Digestive System Diseases

Symptoms and General Pathology

Colorectal Neoplasms

Polyps

Intestinal Neoplasms

Gastrointestinal Neoplasms

Digestive System Neoplasms

Gastrointestinal Diseases

Colonic Diseases

Intestinal Diseases

Rectal Diseases

The examinator will provide a HOD for every lesion (regardless of their size) found during the examination (adenoma vs non-adenoma) following one of the available validated classifications (NICE, JNET, BASIC). He/she will also give a level of confidence in his/her diagnosis (high/low confidence). However, only diminutive lesions will be considered when analyzing the main outcome. The time to get a HOD will be recorded. An in situ surveillance interval will be provided if possible.

GI-Genius will provide an artificial intelligence diagnosis (AIOD) for every lesion detected (adenoma vs non-adenoma). Only diminutive lesions will be considered for the analysis of the main outcome. However, data on larger lesions will be recorded to describe GI-Genius´ performance in detail (secondary outcome). The time to get an AIOD will be recorded. An in situ surveillance interval will be provided if possible

The software allows for the real-time characterization of framed polyps during a colonoscopy classifying them on adenoma or non-adenoma.

GI-Genius artificial intelligence

Marco Bustamante Balén, M.D., Ph.D.

Sylwia Jaworska Fernandez

Marco Bustamante Balén, M.D.;Ph.D.

Marco Bustamante Balén, M.D.; Ph.D.

Artificial intelligence is a promising tool that may have a role in characterizing colon epithelial lesions (CADx), helping to get a reliable optical diagnosis regardless of the endoscopist experience. Performances of the different CADx systems are variable but it seems that, in most cases, high accuracy and sensitivities are achieved. However, these CADx systems have been developed and validated using still pictures or videos, and a real-world accurate test is lacking. No clinical trials have tested this technology in clinical practice and, therefore, performance in real colonoscopies, practical problems, applicability, and cost are unknown.

The resect-and-discard (R\&D) and diagnose-and-leave (D\&L) strategies have been proposed as a means to reduce costs in the evaluation of colorectal polyps avoiding a substantial number of pathology evaluations. A pre-requisite for this paradigm shift is an accurate optical diagnosis (HOD). However, performance results for HOD have been highly variable among endoscopists representing a barrier for the adoption of the R\&D and the D\&L strategies.

Artificial intelligence is a promising tool that may have a role in characterizing colon epithelial lesions (CADx), helping to get a reliable optical diagnosis regardless of the endoscopist experience. Performances of the different CADx systems are variable but it seems that, in most cases, high accuracy and sensitivities are achieved. However, these CADx systems have been developed and validated using still pictures or videos, and a real-world accurate test is lacking. No clinical trials have tested this technology in clinical practice and, therefore, performance in real colonoscopies, practical problems, applicability, and cost are unknown.

Methods and analysis: The ODDITY trial is a European multicenter randomized, parallel-group superiority trial comparing GI-Genius artificial intelligence optical diagnosis (AIOD) to human optical diagnosis (HOD) of colon lesions ≤ 5 mm performed by endoscopists, using histopathology as the gold standard. A total of 643 patients attending a colonoscopy within a CRC screening program (either FIT- or colonoscopy-based) or because of post-polypectomy surveillance will be randomized to the ADI group or the HOD (control) group. A computer-generated 1:1 blocking randomization scheme stratified for center and endoscopist will be used.

The ODDITY trial is a European multicenter randomized, parallel-group superiority trial comparing GI-Genius artificial intelligence optical diagnosis (AIOD) to human optical diagnosis (HOD) of colon lesions ≤ 5 mm performed by endoscopists, using histopathology as the gold standard. A total of 643 patients attending a colonoscopy within a CRC screening program (either FIT- or colonoscopy-based) or because of post-polypectomy surveillance will be randomized to the ADI group (group 1) or the HOD (control, group 2) group. A computer-generated 1:1 blocking randomization scheme stratified for center and endoscopist will be used.

Patients will be blinded to group allocation. The endoscopist in group 2 will be blinded to the AIOD. However, the endoscopist in group 1 will not be blinded to the CADx diagnosis because the output helps the endoscopist to focus the lesion properly for a AIOD diagnosis. In group 2, the person in charge of handling the GI-Genius output will communicate with the endoscopist when the AIOD of a particular lesion has been obtained. There is no need to mask personnel who enters HOD or AIOD data on the CRD because at that point results of pathology are not available.

Artificial Intelligence for Diminutive Polyp Characterization

Efficacy and Cost-effectiveness of an Artificial Intelligence System (GI-Genius) on the Characterization of Diminutive Colorectal Polyps Within a Colorectal Cancer Screening Program: a Multicenter Randomized Controlled Trial (ODDITY Trial)

A surveillance interval will be assigned using optical diagnosis of ≤ 5 mm polyps (Arm 1: AIOD; Arm 2: HOD of polyps diagnosed with high confidence) plus histopathology of \> 5 mm polyps and polyps ≤ 5 mm diagnosed with low confidence. For each patient included, the optical-diagnosis surveillance assignment will be matched with the histology-directed one, and a concordance rate will be calculated. The post-polypectomy surveillance interval will be calculated using the ESGE 2020 and the USMSTF 2020 guidelines. Per-patient analysis.

The optical diagnosis of ≤ 5 mm rectosigmoid polyps (Arm 1: AIOD; Arm 2: HOD, only high-confidence diagnosis) reliability on ruling out the presence of an adenoma will be calculated using histopathology as the gold standard. Per-lesion analysis. NPV = number of confirmed hyperplastic polyps/number of hyperplastic optical diagnosis

Operative characteristics (sensitivity, specificity, positive and negative predictive value and positive likely hood ratio) using histopathology as the gold standard. Per-lesion analysis

The economic burden of applying the AIOD and HOD to assign the post-polypectomy surveillance intervals compared to the histology-driven strategy. A direct cost evaluation will be performed including medical and non-medical costs. Per-patient analysis.

The occurrence and severity of adverse events in colonoscopies with and without the AIOD device will be monitored during the 30-days period after the procedure. Adverse events are defined as: abdominal pain or discomfort, post-polypectomy bleeding, perforation, post-polypectomy syndrome and infection. Per-patient analysis

The proportion of patients willing to have their polyps diagnosed by an AI system or HOD will be assessed using a structured questionnaire. Per-patient analysis.

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Ultrasound Imaging and Spectroscopy as Early Indicators of Locally-Advanced Breast Cancer Response	NCT04134780	Breast Cancer		18 Years -	Sunnybrook Health Sciences Centre
Investigation of Ultrasound Imaging and Spectroscopy for Characterizing Breast Masses	NCT04050423	Breast Cancer		-	Sunnybrook Health Sciences Centre
Interest of Indocyanine Green in Neoplastic Prostatic Tissue	NCT02260349	Prostatic Neopl...	indocyanine gre...	18 Years -	Centre Hospitalier Universitaire de Saint Etienne
Ultrasound Imaging and Spectroscopy as Early Indicators of Locally-Advanced Breast Cancer Response	NCT04134780	Breast Cancer		18 Years -	Sunnybrook Health Sciences Centre
Interest of Indocyanine Green in Neoplastic Prostatic Tissue	NCT02260349	Prostatic Neopl...	indocyanine gre...	18 Years -	Centre Hospitalier Universitaire de Saint Etienne
Artificial Intelligence for Diminutive Polyp Characterization	NCT05391477	Colorectal Neop...	GI-Genius artif...	-	Hospital Universitario La Fe
Ultrasound Imaging and Spectroscopy as Early Indicators of Locally-Advanced Breast Cancer Response	NCT04134780	Breast Cancer		18 Years -	Sunnybrook Health Sciences Centre

Spots Global Cancer Trial Database for characterization