Purpose |
Detect and measure midline shift |
Tag(s) |
|
Panel |
Neuroradiology |
Define-AI ID |
18030001 |
Originator |
Sumit Niogi |
Panel Chair |
Alex Norbash |
Panel Reviewers |
Neuroradiology Panel |
License |
|
Status | Published |
Related RadElement Sets | RDES39 |
The patient receives CT for head trauma. An algorithm receives the entire CT data set. If the algorithm can determine a result (the presence or absence of midline shift, distance of midline shift, and direction of shift), it is returned. A reliability metric, assessing the accuracy of the measurement, would also be helpful. If the midline shift is significant (larger than 5 mm), a modest alert should notify the user.
Additional considerations are as follows: The algorithm executes after the exam is verified on PACS. The algorithm optimally integrates on PACS and dictation or reporting software. The user is then able to automatically populate the report or manually input the results. An indicator image may save to PACS as part of the medical record.
Procedures(s): CT, Head
Sex at Birth: {Male, Female}
Age: [16,90]
Comorbidities: {Hematoma, tumor, abscess}
Procedure |
CT, Head |
Data Type |
DICOM |
Modality |
CT |
Body Region |
Head |
Anatomic Focus |
Brain |
RadElement ID |
RDE237 |
Definition |
Measurement of midline shift at maximum (septum pellucidum) and at level of foramen of Monro. |
Data Type |
Numeric |
Value Set |
[0,10] |
Units |
mm |
RadElement ID |
RDE238 |
Definition |
The direction of midline shift, if present |
Data Type |
Categorical |
Value Set |
0–Unknown 1–No midline shift 2–Left |
Units |
N/A |