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Name:
UMIN ID:

Recruitment status No longer recruiting
Unique ID issued by UMIN UMIN000031548
Receipt No. R000035991
Scientific Title Computer-aided diagnosis system for breast ultrasound images using deep learning
Date of disclosure of the study information 2018/03/03
Last modified on 2019/03/04

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Basic information
Public title Computer-aided diagnosis system for breast ultrasound images using deep learning
Acronym Computer-aided diagnosis system for breast ultrasound images using deep learning
Scientific Title Computer-aided diagnosis system for breast ultrasound images using deep learning
Scientific Title:Acronym Computer-aided diagnosis system for breast ultrasound images using deep learning
Region
Japan

Condition
Condition Breast cancer
Classification by specialty
Breast surgery
Classification by malignancy Malignancy
Genomic information NO

Objectives
Narrative objectives1 Developing the algorithm for deep learning to classify the breast mass as benign or malignant from ultra sound images, and evaluate it's usefulness.
Basic objectives2 Others
Basic objectives -Others Usefulness
Trial characteristics_1 Exploratory
Trial characteristics_2 Others
Developmental phase Not applicable

Assessment
Primary outcomes Accuracy, sensitivity, specificity and area under the curve of the algorithm which classifying lesion as benign or malignant.
Key secondary outcomes Accuracy and sensitivity of the algorithm which classifying lesion as 3 categories by.

Base
Study type Observational

Study design
Basic design
Randomization
Randomization unit
Blinding
Control
Stratification
Dynamic allocation
Institution consideration
Blocking
Concealment

Intervention
No. of arms
Purpose of intervention
Type of intervention
Interventions/Control_1
Interventions/Control_2
Interventions/Control_3
Interventions/Control_4
Interventions/Control_5
Interventions/Control_6
Interventions/Control_7
Interventions/Control_8
Interventions/Control_9
Interventions/Control_10

Eligibility
Age-lower limit

Not applicable
Age-upper limit

Not applicable
Gender Male and Female
Key inclusion criteria Patients who were within the image database managed by Japan Association of Breast and Thyroid Sonology, and received a breast ultrasound examination from November 2011 to December 2015. And satisfied the following rules.

1.Mass lesions had already been assessed.
2.Associating with definitive diagnosis or category diagnosed by B-mode

Key exclusion criteria 1.Typical cysts
2. Mass lesions >= 4.5cm diameter
Target sample size 1543

Research contact person
Name of lead principal investigator
1st name
Middle name
Last name Takuhiro Yamaguchi
Organization Tohoku University Graduate School of Medicine
Division name Biostatistics
Zip code
Address 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, JAPAN
TEL 022-717-7659
Email yamaguchi@med.tohoku.ac.jp

Public contact
Name of contact person
1st name
Middle name
Last name Takuhiro Yamaguchi
Organization Tohoku University Graduate School of Medicine
Division name Biostatistics
Zip code
Address 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, JAPAN
TEL 022-717-7659
Homepage URL
Email yamaguchi@med.tohoku.ac.jp

Sponsor
Institute Tohoku University Graduate School of Medicine, Biostatistics
Institute
Department

Funding Source
Organization SAS Institute Japan Ltd
Organization
Division
Category of Funding Organization Profit organization
Nationality of Funding Organization

Other related organizations
Co-sponsor Japan Association of Breast and Thyroid Sonology
Name of secondary funder(s)

IRB Contact (For public release)
Organization
Address
Tel
Email

Secondary IDs
Secondary IDs NO
Study ID_1
Org. issuing International ID_1
Study ID_2
Org. issuing International ID_2
IND to MHLW

Institutions
Institutions

Other administrative information
Date of disclosure of the study information
2018 Year 03 Month 03 Day

Related information
URL releasing protocol
Publication of results Unpublished

Result
URL related to results and publications
Number of participants that the trial has enrolled
Results
Results date posted
Results Delayed
Results Delay Reason
Date of the first journal publication of results
Baseline Characteristics
Participant flow
Adverse events
Outcome measures
Plan to share IPD
IPD sharing Plan description

Progress
Recruitment status No longer recruiting
Date of protocol fixation
2018 Year 01 Month 24 Day
Date of IRB
Anticipated trial start date
2018 Year 02 Month 05 Day
Last follow-up date
Date of closure to data entry
Date trial data considered complete
Date analysis concluded

Other
Other related information Collect the maximum number of cases that can be collected

Management information
Registered date
2018 Year 03 Month 02 Day
Last modified on
2019 Year 03 Month 04 Day


Link to view the page
URL(English) https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000035991

Research Plan
Registered date File name

Research case data specifications
Registered date File name

Research case data
Registered date File name


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