Neoplasms

All Conditions

Carcinoma

All patients are undergoing radiotherapy in Tata Medical Center

In this pilot project Investigators propose to create annotated image data bank of patients suffering from cancer. The system will provide India's first comprehensive platform to upload annotated images with associated medical and demographic information of a patient. It will support flexible query from the users with appropriate choice from a set of attributes and design of various query filters using a GUI. Over the proposed period of 18 months, images and records related to radiation oncology including pretreatment images of at least 500 patients would be annotated and archived in the data bank. The imaging modalities to be covered are X-RAY mammograms, SPECT, CT, CBCT, MR, PET-CT, Ultrasound, digital histopathology, etc. In this phase, this study will include data sets of five types of cancers namely, breast, head and neck, brain, cervix and lung cancer.

Investigator propose to demonstrate the application of this data set in cancer research. Investigator will work on serial PET-CT based radiomics of breast and cervix cancer patients to extract appropriate features and correlate them with clinico-pathological variants.

Comprehensive Digital Archive of Cancer Imaging-Radiation Oncology( CHAVI-RO )

Count of patients with complete radiological, pathological and demographic information in the CHAVI RO database.

Tata Medical Center

Urinary Tract, Sexual Organs, and Pregnancy Conditions

Uterine Cervical Neoplasms

Uterine Cervical Dysplasia

Uterine Neoplasms

Genital Neoplasms, Female

Urogenital Neoplasms

Uterine Cervical Diseases

Uterine Diseases

Genital Diseases, Female

Genital Diseases

Urogenital Diseases

Female Urogenital Diseases

Pregnancy Complications

Female Urogenital Diseases and Pregnancy Complications

Anti-Infective Agents

All Drugs and Chemicals

Antineoplastic Agents

Micronutrients

Coagulants

Pharmaceutical Solutions

Vitamins

Acetic Acid

Retinol acetate

Iodine

Lugol's solution

Cadexomer iodine

Hemostatics

The AVC test will be performed during VIA by local midwives: 120 second videos focused on the cervix will be taken right after the application of acetic acid on the cervix. The recording smartphone will be fixed on a tripod situated 15cm away from the cervix.

AVC test

Patrick Petignat, Pr

Inès Baleydier

Bruno Kenfack, Pr

Patrick Petignat

Cervical cancer remains a major public health challenge in low- and middle-income countries (LMICs) due to financial and logistical issues. The World Health Organization (WHO) recommendation for cervical cancer screening in LMICs includes Human Papillomavirus (HPV) testing as primary screening followed by visual inspection with acetic acid (VIA) and treatment. However, VIA is a subjective procedure dependent on the healthcare provider's experience. Therefore, an objective approach based on quantitative diagnostic algorithms is desirable to improve performance of VIA.

With this objective and in a collaboration between the Gynecology and Obstetrics Department of the Geneva University Hospital (HUG) and the Swiss Institute of Technology (EPFL), our group started the development of an automated smartphone-based image classification device called AVC (for Automatic VIA Classifier). Two-minute videos of the cervix are recorded during VIA and classified using an artificial neural network (ANN) and image processing techniques to differentiate precancer and cancer from non-neoplastic cervical tissue. The result is displayed on the smartphone screen with a delimitation map of the lesions when appropriate. The key feature used for classification is the dynamic of cervical acetowhitening during the 120 second following the application of acetic acid. Precancerous and cancerous cells whiten more rapidly than non-cancerous ones and their whiteness persists stronger overtime.

Our aim is to assess the diagnostic performance of the AVC and to compare it with the performance of current triage tests (VIA and cytology). Histopathological examination will serve as reference standard. Participants' and providers' acceptability will also be considered as part of the study.

The study will be nested in an ongoing cervical cancer screening program called "3T-approach" (for Test, Triage and Treat) which includes HPV self-sampling for women aged 30 to 49 years, followed by VIA triage and treatment if needed. The AVC will be evaluated in this context.

The study's risk category is A according to swiss ethical guidelines. This decision is based on the fact that the planned measures for sampling biological material or collecting personal data entail only minimal risks and burdens.

Automated Cervical Cancer Screening Using a Smartphone-based Artificial Intelligence Classifier

Study Protocol for a Two-site Clinical Trial to Validate a Smartphone-based Artificial Intelligence Classifier Identifying Cervical Precancer and Cancer in HPV-positive Women in Cameroon

by including metrics such as sensitivity, specificity, positive predictive value and negative predictive value using histologic assessment as reference standard.

by women and healthcare providers using qualitative and quantitative methods.

Prof. Patrick Petignat

Director of the gynaecology department

Heart and Blood Diseases

Diseases and Abnormalities at or Before Birth

Symptoms and General Pathology

Aneurysm

Arteriovenous Malformations

Congenital Abnormalities

Constriction, Pathologic

Hemangioma

Vascular Diseases

Vascular Malformations

Cardiovascular Abnormalities

Neoplasms, Vascular Tissue

Neoplasms by Histologic Type

Low dose DSA (75% reduction compared to normal dose) with novel X-ray imaging technology

Normal dose DSA with conventional X-ray technology.

Digital substraction angiography (DSA) with reduced dose settings (75% reduction expected) in combination with conventional X-ray imaging technology.

Low dose DSA (75% reduction compared to normal dose) with novel X-ray imaging technology.

Digital substraction angiography (DSA) with normal dose settings in combination with conventional X-ray imaging technology.

Normal dose DSA with conventional X-ray technology

Michael Söderman, MD, PhD

Tommy Andersson, MD, PhD

Staffan Holmin, MD, PhD

ClarityIQ is a novel X-ray imaging technology, that combines advanced real-time image noise reduction algorithms, with state-of-the-art hardware to reduce patient entrance dose significantly. This is realized by anatomy-specific optimization of the full acquisition chain (grid switch, beam filtering, pulse width, spot size, detector and image processing engine) for every clinical task individually. Furthermore, smaller focal spot sizes and shorter pulses are used, which are known to positively influence image quality . The final effect on the clinical image quality is investigated in this study.

The advent of interventional neuroradiology (INR) has changed the treatment of neurovascular diseases by reducing the procedural invasiveness and the recovery time needed by patients, thus improving clinical outcome. However, INR procedures often require many high-quality digital substraction angiography (DSA) runs and long total fluoroscopy times, which can result in patients being exposed to considerable radiation doses levels.

In order to introduce a dose reduction technology the most important aspect is to validate the diagnostic image information. Philips has developed a real-time noise reduction algorithm for DSA in neuroradiology that is capable to reduce the patient entrance dose by 75% without loss of image quality.

Image Quality and Radiation Dose in Angiography

XRES4 Neuro Claim Study

Percentage of dose reduction of ClarityIQ vs. AlluraXper in Air Kerma (AK) calculated by AK/frame.

The images were evaluated in randomized, blinded, offline readings. The anonymized images were displayed in pairs, i.e. the reference image run on one monitor (randomly left or right side) with the corresponding quarter-dose image run on the adjacent monitor. Three neuroradiologists graded the arterial, capillary, and venous phases separately. For each characteristic the images quality (IQ) were rated on a scale of 1 to 5 as 1 (very poor), 2 (mediocre), 3 (average), 4 (good), 5 (very good/excellent). An overall IQ score (3-15) was calculated as the sum of the score for these characteristics.

A paired Student's t test is used to compare the overall IQ score between the 2 imaging techniques. If the upper limit of the 97.5% one-sided CI for the difference overall IQ between the two treatment groups does not exceed the pre-defined non-inferiority margin of 2.5 Clarity will be declared non-inferior to the current image acquisition settings for DSA.

Percentage of dose reduction of ClarityIQ vs. AlluraXper in Dose Area Product (DAP) calculated by DAP/frame.

Philips Medical Systems

Karolinska University Hospital

MD, PhD

Angiogram with AlluraXper subsequently followed by angiogram with ClarityIQ

AlluraXper - ClarityIQ

Angiogram with AlluraXper followed by angiogram with ClarityIQ

Age, Continuous

Sex: Female, Male

Sweden

Region of Enrollment

Dr. Söderman

Investigator 1

Investigator 2

Investigator 3

AlluraXper

Allura Clarity

Image Quality. For Each Included Participant 2 Images (1 AlluraXper; 1 AlluraClarity) Were Evaluated.

All patients with recorded dose information and images for both angiograms were included (n=20)

Radiation Dose Measurements: Dose Area Product (DAP)

Radiation Dose Measurements: Air Kerma (AK)

Overall Study

Respiratory Tract (Lung and Bronchial) Diseases

Lung Neoplasms

Respiratory Tract Neoplasms

Thoracic Neoplasms

Lung Diseases

Respiratory Tract Diseases

Radiologists who have certification by the American Board of Radiology

This is an observer performance study. Radiologists will interpret chest radiographs without and then with the Riverain software, both SoftView (TM) OnGuard (TM) CADe Software with be tested

Software

Matthew T. Freedman, MD, MBA

Ben Lo, Ph.D.

This is a clinical trial using retrospective data of two different software devices developed by Riverain Medical Group: Softview and OnGuard 5.0. The two studies will be run concurrently. Riverain Medical Group's computer systems are designed to assist radiologists in their identification of lung cancer on chest radiographs. The current machine received FDA Pre-Market Approval. This is to test two new software approaches.

In 2000, data was presented to the FDA to demonstrate that a new system for computer analysis could assist radiologists in the detection of small lung cancers on chest radiographs. Radiologists using the system showed a statistically significant improvement in lung cancer detection rate when they used the system, compared to their interpretation of chest radiographs when they did not use the computer system. This study, along with other supporting data, resulted in the FDA giving Pre-Market Approval for the system.

The system has undergone several improvements in software and hardware, and it is now intended to test two different software systems to determine whether radiologists using the systems can improve their detection of lung cancer on chest radiographs.

One of these systems processes the chest radiograph to decrease the emphasis given to the shadow of the ribs and thereby enhances the ability of radiologists to detect disease in the lungs. The second system performs a series of evaluations on chest radiographs and, based on a complex system of analysis, points to locations on the chest radiograph that contain solitary pulmonary nodules having the characteristics of primary lung cancer or solitary metastases of cancer to the lungs.

This will be a test of radiologists to determine the degree of improvement, if any, that results when they interpret chest radiographs that may or may not have cancer, first interpreted without the computer and, second, with the images output by the software.

Testing of Computer Aided Detection Software for Riverain Medical Group

This reports the comparison of the detection of lung nodules that were proven to represent lung cancers. It compares the results of two versions of computer-aided detection software: OnGuard 1.0 from 2001 and OnGuard 5.1 from 2009. The results represent the responses of radiologists when they use one or the other types of software. To compare radiologists' results with the two types of software, the measurement analyzed was the difference in the areas under the localized receiver operating characteristic curve (LROC). The results from the 15 participating radiologists were averaged (mean value). The area under the LROC curve is a measure of the trade-offs between sensitivity and 1-specificity that occurs as the level of certainty of a positive finding changes. It is normally reported as a decimal without units. In this study dsign, a lower number indicates that the new method (OnGuard 5.1), if statistically significant, if better.

Standard methods for LROC methodology and statistical analysis were used. We are testing two different types of software using different cases, but the same radiologists to control for radiologist differences. LROC is Localized Receiver Operating Characteristic. LROC measures the trade-offs between sensitivity and specificity as radiologists use different levels of suspicion of disease. This analysis is for the software that decreases the visibility of the ribs and clavicles while preserving (and potentially enhancing) the visibility of the lungs and lung diseases. In this case, the level of suspicion recorded was for the radiologist's concern that a finding did or did not represent cancer. Please note that the FDA approved indications for use is to detected nodules that may represent cancer, but in our study scoring for a true finding was based on whether or not the nodule did represent cancer.

A larger number, if statistically significant, indicates that that method is better.

Sensitivity and specificity were calculated using the radiologists' responses of recommendations for follow-up with CT or biopsy. Truth was whether or not the nodule identified was found to be cancer. Sensitivity is the percentage of correct identification of a positive case (a case with cancer). Specificity is the percentage of negative cases (those without cancer) that were correctly identified as not having cancer. The mean values of 15 radiologists are used.

Riverain Technologies

Georgetown University

Associate Professor Oncology, Adjunct (Pending)

Participants

Radiologists who have certification by the American Board of Radiology

Riverain OnGuard CAD Software : This is an observer performance study. Radiologists will interpret chest radiographs without and then with the Riverain software, both SoftView (TM) OnGuard (TM) CADe Software with be tested

Radiologists

number of participants

Age, Customized

United States

Power calculation was performed to determine the number of participants

No adverse events occurred. Study was subject to the following potential biases: Sample bias; Majority rule bias; Referral Bias, bias from knowledge that this is an experiment; reader order bias; learning bias; Bias from use of new technology, et al

Matthew T. Freedman

The sample size of 351 patients, in a 2:1 ratio of nodule absent to present patients was selected to provide 80% power to detect a difference in areas under the curve of 0.10 or greater. This sample size was calculated using PASS software (Hintze, 2008). Settings: • α = 0.025. • one-sided test • AUCA = 0.80 and AUCSV = 0.90.• 2:1 ratio of patients with nodules to those without • areas calculated for the entire curves • correlation 0.3\* • discrete data. • standard deviation ratios of 1\*.

Control image interpretation unaided by software of either type. This is the control for the SoftView experiment. It uses the same radiologists (to avoid a bias that might result from using different radiologists) as the OnGuard Computer-aided detection software, but different cases.

Radiologists Control for SoftView

This software suppresses the visibility of the ribs and clavicles potentially revealing non-calcified nodules make less conspicuous by the bones projected on top of the nodules

Radiologists Using Softview Software

122 subjects had cancer that potentially could be detected on their chest radiograph. Power analysis showed that sample size of 351 patients, in a 2:1 ratio of nodule absent to present patients was selected to provide 80% power to detect a difference in areas under the curve of 0.10 or greater.

Improvement in Cancer Detection as Measured by Localized Receiver Operating Characteristic) LROC Changes Under the LROC Curve.

Radiologists using OnGuard software. Two different versions were tested. OnGuard 1.0 and OnGuard 5.1. This software uses a computer algorithm to identify non-calcified lung nodules consistent with lung cancer. The value presented is the average difference in the areas under the LROC curve as demonstrated for the participating radiologists. The value for OnGuard 5.1 was subtracted from that of OnGuard 1.0, so a negative value indicates that OnGuard 5.1 had a higher value than OnGuard 1.0. The 95% confidence interval indicates that the OnGuard 5.1 was significantly improved.

Radiologists Using OnGuard Software: Difference of 1.0 and 5.1

81 of the 263 radiographs contained a non-calcified nodule that had been diagnosed as lung cancer. Power calculation showed 246 patients, in a 2:1 ratio of nodule absent to present would provide 80% power to detect a difference in areas under the curve of 0.10 or greater.

Difference in the Area Under the LROC Curve Comparing OnGuard 1.0 and OnGuard 5.1

Sensitivity

Specificity

Sensitivity and Specificity Using SoftView Software

Radiologists who have certification by the American Board of Radiology

Riverain OnGuard and SoftView Software : This is an observer performance study. Radiologists will interpret chest radiographs without and then with the Riverain software, Two types of software are tested: SoftView (TM). SoftView decreases the visibility of the ribs and clavicles on chest radiographs. OnGuard marks locations on chest radiographs meeting some of the software signs of lung nodules, a method often called Computer Aided Detection (CADe).

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Comprehensive Digital Archive of Cancer Imaging-Radiation Oncology( CHAVI-RO )	NCT04249895	All Cancer		-	Tata Medical Center
Comprehensive Digital Archive of Cancer Imaging-Radiation Oncology( CHAVI-RO )	NCT04249895	All Cancer		-	Tata Medical Center
Automated Cervical Cancer Screening Using a Smartphone-based Artificial Intelligence Classifier	NCT04859530	Cervical Cancer HPV	AVC test	30 Years - 49 Years	University Hospital, Geneva
Image Quality and Radiation Dose in Angiography	NCT01381952	Arteriovenous M... Aneurysm Stenosis Dural Arteriove...	Low dose DSA (7... Normal dose DSA...	18 Years - 80 Years	Karolinska University Hospital
Testing of Computer Aided Detection Software for Riverain Medical Group	NCT00906789	Lung Cancer	Software	-	Georgetown University
Testing of Computer Aided Detection Software for Riverain Medical Group	NCT00906789	Lung Cancer	Software	-	Georgetown University

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