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Heterogeneity In Regional Myocardial T2* Improvement After Deferiprone Therapy,

2011· article· en· W2549897972 on OpenAlexaffabout
Sharon Chih, Heather J. Ross, Elsie T. Nguyen, Richard Ward

Bibliographic record

VenueBlood · 2011
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineDeferiproneCardiac magnetic resonanceThalassemiaInternal medicineNuclear medicineCardiologySiderosisMagnetic resonance imagingRadiology

Abstract

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Abstract Abstract 3176 Myocardial siderosis is a major cause of death in Thalassemia Major (TM). Intensification of iron chelation therapy (ICT) can reverse cardiac toxicity and improve survival. Cardiac magnetic resonance (CMR) imaging with T2* analysis of a single region of interest (ROI) within the mid septum has been shown to be representative of overall myocardial iron concentration. Histological studies, however, demonstrate heterogeneity in myocardial iron. To date, dynamics of cardiac iron removal by ICT has not been well studied. Deferiprone (DFP) is an effective oral myocardial iron chelator. This study aims to examine patterns of myocardial iron removal by DFP using a 4 segmental CMR T2* approach. All patients receiving DFP for myocardial iron overload at Toronto General Hospital, up until March 2011 were evaluated retrospectively. CMR was performed on a 1.5 Tesla scanner (Siemans, Germany) before and after DFP treatment using a gradient-multi-echo sequence and cardiac gating. 4 to 5 short-axis slices were acquired at 8 echo times (TE) in a single end-expiratory breath hold. T2* analysis was performed using CMR 42 software (Circle software, Calgary, Canada). A basal- and mid-ventricular short axis slice was chosen for analysis. CMR were analyzed by a single observer who remained blinded to the timing of the scans in relation to therapy. CMR were performed on 19 TM patients (37% (n=7) males, mean age 31 years) at an average of 83 days before and 205 days after the commencement of DFP. The average daily dose of DFP was 87mg/kg. 42% (n=8) of patients were on DFP alone and 58% (n=11) were on combination therapy with Deferoxamine (n=10) or Deferasirox (n=1). There was significant variation in myocardial T2* across the 4 regions assessed both before (P<0.001) and after (P=0.001) treatment. Prior to treatment, T2* values were lowest in the mid anteroseptum and highest in the basal inferoseptum (P<0.050) (Figure 1). Following treatment with DFP, T2* values improved significantly across all myocardial regions (P<0.030 for all). The overall median increase in T2* value was 1.6 ms (IQR: −0.2 to 4.5 ms). In the patient subgroup with severe iron overload (baseline T2* ≤10ms; n=11), the improvement in T2* varied across all 4 myocardial regions and showed a trend towards statistical significance (P=0.091). The greatest improvement was observed in the basal inferoseptum (median T2* change 4.8 ms; IQR: 0.0 to 7.2 ms) and the least improvement in the mid anteroseptum (median T2* change 1.1 ms; IQR 0.3 to 4.3 ms) (Figure 2). In this patient subgroup, trends towards significance were also demonstrated for greater improvement in median T2* in the basal (4.5 ms; IQR: 0.6 to 5.9 ms) versus mid septum (2.0 ms; IQR: −0.1 to 5.4 ms, P=0.075) and in the inferoseptum (3.9 ms; IQR: 0.0 to 6.3 ms) versus the anteroseptum (3.1 ms; IQR: 0.4 to 4.4 ms, P=0.084). The data indicate variable regional response to DFP chelation therapy that trended towards statistical significance in patients with severe myocardial iron overload (T2* ≤10 ms). The greatest increase in T2* values was observed in the myocardial region with the highest baseline T2* (basal inferoseptum) while the smallest improvement was seen in the region with the lowest baseline T2* (mid anteroseptum). This suggests that effective chelation may be more challenging in areas with more severe iron deposition. However, there was a non-significant trend to greater increase in T2* across all myocardial regions after treatment in patients with an overall baseline T2* ≤10 ms, versus T2* >10ms. Regional variability in T2* change following DFP therapy has not been previously investigated. Further studies using a multi-segmental T2* analysis approach may improve understanding of the dynamics of iron removal and provide new avenues for optimizing iron chelating regimens to maximize iron removal and improve patient-outcomes. Figure 1. Median T2* measurements before (clear bar) and after (shaded bar) DFP treatment in each myocardial region (n=19). P<0.001 before treatment and P=0.001 after treatment by Friedman's test. *P<0.050 compared with basal inferoseptum and mid anteroseptum before treatment, †P<0.050 compared with basal inferoseptum after treatment by Dunn's multiple comparisons test. Error bars indicate interquartile ranges. Figure 1. Median T2* measurements before (clear bar) and after (shaded bar) DFP treatment in each myocardial region (n=19). P<0.001 before treatment and P=0.001 after treatment by Friedman's test. *P<0.050 compared with basal inferoseptum and mid anteroseptum before treatment, †P<0.050 compared with basal inferoseptum after treatment by Dunn's multiple comparisons test. Error bars indicate interquartile ranges. Figure 2. Median change in T2* measurements after DFP for patients with an overall baseline T2* ≤10 ms (n=11). P=0.091 by Friedman's test. Error bars indicate interquartile ranges. Figure 2. Median change in T2* measurements after DFP for patients with an overall baseline T2* ≤10 ms (n=11). P=0.091 by Friedman's test. Error bars indicate interquartile ranges. Disclosures: Off Label Use: Deferiprone is an unlicensed drug in Canada and USA. It is an oral iron chelator.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.288
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2011
Admission routes2
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