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Use Case Description:

Diagnostic aids based upon analysis of neuroimaging are rapidly advancing into clinical use. These tools frequently either employ sex and age classified databases, or algorithms trained upon sex and age classified datasets. An example would be tools for volumetric analysis of structural MRI scans, currently available world-wide with regulatory clearance for clinical use in the assessment of memory disorders, dementia, epilepsy, and traumatic brain injury.

Actors:


Referring Px (GP etc.)

Ordering Px (Neurologist, Neuropsychologist)

Reading Px (Neuroradiologist)

Scope Statement:

The software in scope must rely upon sex-gender in its calculations. Software that is gender-insensitive (e.g. the image reconstruction software of the scanner) would be out of scope.

Precondition(s):

Based upon symptoms, a patient is referred to a clinic or specialist for neuro assessment, which may include ordering of imaging with post-processing analysis.

The analytical software relies upon the sex-gender field(s) of the DICOM imaging to categorize the patient (e.g., the normal range of hippocampal volume by sex at a given age).

Postcondition(s):

The analysis software creates a report containing the assessment and identifying the sex-gender assumed in processing for the patient.

Workflow/Storyboard:

The patient, family members, etc., identify changes in health or behavior suggesting a neuro disorder. The patient's personal px refers the patient to a neuro / memory clinic or practice where they are seen by a neurologist, neuropsychologist, etc. The workup may include ordering neuroimaging with additional post-processing to extract diagnostically relevant information. (E.g. whole-brain T1 structural MRI scan with volumetric analysis including a comparison to normative data.) The post-processing produces an analysis comprised of derived images, numerical/graphical analysis results, and/or narrative reports.

Alternative and/or related Workflow(s):

In some scenarios, a neuroradiologist may read the images and qualitatively characterize findings (e.g., noting atrophy of a brain structure in the brain MRI) and may even quantify them (e.g. manually measuring a volume from image slices). (In this case, the influence of sex-gender on the assessment is inherent in the reader's clinical judgment and may be difficult to characterize.) This initial reading may prompt subsequent ordering of one or more post-processing workflows (above).

Alignment and/or Misalignment with Gender Harmony Model:

Consensus is needed on the relative impact of sex at birth, age and progress of transition, etc. on the proper 'normative value' for a given algorithm on a given transgender patient.

Current Standard Support:

  •  HL7 V2.x   
V2.x Resource: 

...

  •  

    Other (please specify standard and resource below)

Other:

Required Additional Standard Support: