dGEMRIC (delayed gadolinium-enhanced MRI of cartilage)

Last revised by Samuel Holly on 9 Apr 2021

Citation, DOI, disclosures and article data

Citation:

Moore C, Holly S, Knipe H, dGEMRIC (delayed gadolinium-enhanced MRI of cartilage). Reference article, Radiopaedia.org (Accessed on 08 May 2024) https://doi.org/10.53347/rID-72217

DOI:

https://doi.org/10.53347/rID-72217

Permalink:

https://radiopaedia.org/articles/72217

rID:

72217

Article created:

16 Nov 2019, Candace Makeda Moore

Disclosures:

At the time the article was created Candace Makeda Moore had no recorded disclosures.

View Candace Makeda Moore's current disclosures

Last revised:

9 Apr 2021, Samuel Holly

Disclosures:

At the time the article was last revised Samuel Holly had no recorded disclosures.

View Samuel Holly's current disclosures

Revisions:

3 times, by 3 contributors - see full revision history and disclosures

Systems:

Musculoskeletal

Sections:

Imaging Technology

Tags:

cases

Synonyms:

dGEMRIM

dGEMRIC, or delayed gadolinium-enhanced MRI of cartilage is a technique that can be used quantitatively to assess glycosaminoglycan content of cartilage or qualitatively to asses the overall structures of cartilage. The dGEMRIC protocol consists of a T1-mapping sequence. When the technique is adapted and applied to menisci it is called dGEMRIM.

At a time point after an intravenous or intra-articular negatively charged gadolinium agent is injected. The technique enhances areas of glycosaminoglycan (GAG) depletion. In healthy cartilage, the negatively charged contrast agent is repulsed by an intact layer of negatively charged GAGs. However in lesions where the GAG structure is disrupted, the contrast agent is allowed to diffuse into the cartilage shortening the T1 relaxation time of the lesion.

Protocols may vary slightly in terms of precise timing after injection and the exact type of T1 sequences, however, the literature on dGEMRIC used as a quantitative tool is established, with researchers using similar protocols. The technique has been used to asses diseases such as osteoarthritis ^1,2 in terms of degeneration or repair of cartilage. The technique is also extremely useful to segment cartilage and menisci on MRI, therefore facilitating 3D modelling, whether through algorithms for 3D rendering or 3D printing.