Malignancy of breast lesions on diffusion weighted images


Purpose

Detect breast lesions and determine malignancy of breast lesions on diffusion weighted images using ADC values

Tag(s)


Panel

Breast Imaging

Define-AI ID

19060010

Originator

Vandana Dialani

Lead

Vandana Dialani

Panel Chair

Elizabeth Burnside

Panel Reviewers

Breast Imaging

License

Creative Commons 4.0 

Status

Public Comment

 RadElement Set RDES132

Clinical Implementation


Value Proposition


Breast MRI is commonly used to detect and diagnose breast cancer, though there are some limitations with T1/T2 weighted images to describe lesions. Use of diffusion in triaging biopsies would be more robust with AI and could help reduce biopsies and increase specificity of breast MRI, thus reducing overdiagnosis.

In addition the current application of DWI is in staging, and evaluation of treatment response. The lower the ADC values the higher the grade of IDC. AI could bring uniformity in obtaining to ADC values and improve the specificity of DWI — empowering its use as a non contrast MRI noninferior to DCE MRI. Eventually DWI could be widely utilized as a non contrast screening modality.

Narrative(s)


Patient has a breast mass which is indeterminate on MRI( Birads 4a or 4b) and biopsy recommended. With this technique clinician could increase specificity of masses which undergo biopsy and potentially save some biopsies.

Workflow Description


The image is obtained from modality and sent to PACS and the AI engine. The image is analyzed by the engine. The system then detects breast lesion and estimates malignancy. An alert message is sent to PACS from the engine with the information, identification, and graphic highlighting the malignant components.

Diagnostic MRI
1) Breast mass indeterminate on MRI( Birads 4a, 4b, 4c) and biopsy recommended.
2) Patient on neoadjuvant chemotherapy, adc obtained at different points of treatment for assessing treatment response

Screening MRI
1) identify breast lesion/ breast cancer
2) obtain adc maps/values

Considerations for Dataset Development



Age

>30 years

malignant lesion

invasive ductal carcinomas, Ductal carcinoma in situ, invasive lobular carcinoma, lobular carcinoma in situ, angiosarcomas, inflammatory breast cancer, paget disease of the breast, phyllodes tumors

Lesion size

varied

Technical Specifications


Inputs

  

DICOM Study

Procedure

Diffusion weighted MRI

Views

axial, coronal, sagittal

Data Type

DICOM

Modality

MR

Body Region

Chest

Anatomic Focus

Breast

Pharmaceutical

N/A

Scenario

Diffusion weighted MRI



Primary Outputs


Malignant breast lesion detection

RadElement ID

RDE872

Definition

Detection of malignant breast lesion

Data Type

Categorical

Value Set

  • Benign Lesion

  • Malignant Lesion

  • Unknown

Units

N/A


ADC values on ROI

RadElement ID

RDE873

Definition

ADC value on ROI

Data Type

Numeric

Value Set

N/A

Units

mm2/s


Future Development Ideas


Segment the malignant component of a lesion


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