| Title |
Extracellular volume fraction measurements derived from the longitudinal relaxation of blood-based synthetic hematocrit may lead to clinical errors in 3 T cardiovascular magnetic resonance
|
|---|---|
| Published in |
Critical Reviews in Diagnostic Imaging, August 2018
|
| DOI | 10.1186/s12968-018-0475-6 |
| Pubmed ID | |
| Authors |
Yongning Shang, Xiaochun Zhang, Xiaoyue Zhou, Jian Wang |
| Abstract |
The extracellular volume (ECV), derived from cardiovascular magnetic resonance (CMR) T1 mapping, is a biomarker of the extracellular space in the myocardium. The hematocrit (HCT), measured from venipuncture, is required for ECV measurement. We test the clinic values of synthetic ECV, which is derived from the longitudinal relaxation of blood-based (T1blood) synthetic hematocrit in 3 T CMR. A total of 226 subjects with CMR T1 mapping and HCT measurement taken on the same day as the CMR were retrospectively enrolled and randomly split into derivation (n = 121) and validation (n = 105) groups, comprising healthy subjects (n = 45), type 2 diabetes mellitus (T2DM) patients (n = 60), hypertrophic cardiomyopathy (HCM) patients (n = 93), and 28 other patients. Correlation of T1blood with the measured HCT (HCTm) was established in the derivation group and used in both the derivation and the validation groups. The relationships between the ECV values derived from both the synthetic HCT (HCTsyn) and HCTm were explored. In addition, the differences in the ECV values among the HC, T2DMs, and HCMs were compared. Regression between the HCTm and 1/T1blood was linear (R2 = 0.19, p < 0.001), and the regression equation was: HCTsyn = [561.6*(1/T1blood)] + 0.098 in the derivation group. The measured ECV (ECVm) was strongly correlated with the synthetic ECV (ECVsyn) (R2 = 0.87, p < 0.001) and mildly correlated with the difference between the ECVsyn and ECVm (R2 = 0.10, p < 0.001) in the derivation group. Also in this group, the ECVm was larger in T2DMs than that in healthy cohort (29.1 ± 3.1% vs. 26.4 ± 2.4%, p = 0.002), whereas, the ECVsyn did not differ between T2DMs and healthy cohort (28.3 ± 2.9% vs. 26.9 ± 2.2%, p = 0.064). Compared with the healthy cohort, the HCMs were associated with higher ECVsyn and ECVm of the mid-ventricle in both the derivation and the validation groups. Using our center's normal cut-off of 31.8%, the use of ECVsyn would lead to a 6-25% incorrect categorization of patients in the derivation and validation groups. ECVsyn derived from HCTsyn may lead to clinical errors in 3 T CMR, especially for patients who have only a subtle elevation in ECV. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 20% |
| Unknown | 4 | 80% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Science communicators (journalists, bloggers, editors) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 40 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 5 | 13% |
| Student > Ph. D. Student | 5 | 13% |
| Researcher | 5 | 13% |
| Student > Bachelor | 4 | 10% |
| Student > Postgraduate | 4 | 10% |
| Other | 5 | 13% |
| Unknown | 12 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 17 | 43% |
| Engineering | 3 | 8% |
| Biochemistry, Genetics and Molecular Biology | 1 | 3% |
| Nursing and Health Professions | 1 | 3% |
| Immunology and Microbiology | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 14 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 August 2018.
All research outputs
#8,681,963
of 25,728,855 outputs
Outputs from Critical Reviews in Diagnostic Imaging
#717
of 1,386 outputs
Outputs of similar age
#136,747
of 342,331 outputs
Outputs of similar age from Critical Reviews in Diagnostic Imaging
#23
of 25 outputs
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