Systematic Review and Meta-Analysis of Cardiac MRI T1 and ECV Measurements in Pre-Heart Failure Populations

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This systematic review and meta-analysis evaluates the diagnostic and prognostic utility of cardiac magnetic resonance (CMR) T1 and extracellular volume (ECV) mapping in pre-heart failure (pre-HF) populations. 

I have the following suggestions:

1. Highlight the cost-effectiveness of early detection of Pre-HF

2.Tabulate field strengths (1.5T vs. 3T), sequences (MOLLI/ShMOLLI), and contrast agents used across studies to explain heterogeneity.

3. Summarize HRs for HF events in a standalone table for clarity.

4.Propose a risk-stratification algorithm 

5.Note the lack of studies linking T1/ECV changes to hard outcomes (e.g., mortality).

6.Briefly address CMR’s cost versus long-term HF savings.

Author Response

Reviewer 1:

1. Highlight the cost-effectiveness of early detection of Pre-HF

We would like to thank the reviewer for this insightful comment. We have now highlighted the cost-effectiveness of early detection of Pre-HF in the manuscript. Please see the updated text in the "Clinical Applications" subsection of the "Discussion" section.

1. Tabulate field strengths (1.5T vs. 3T), sequences (MOLLI/ShMOLLI), and contrast agents used across studies to explain heterogeneity.

We appreciate the reviewer's suggestion. We have now tabulated the field strengths, sequences, and contrast agents used across the studies in Table 1, and discussed how these factors contribute to heterogeneity in the "Methodological Variability and Quality" subsection of the "Discussion" section.

1. Summarize HRs for HF events in a standalone table for clarity.

We thank the reviewer for this recommendation. Given that only three studies reported HRs for HF events, we have opted not to create a standalone table, as we felt it would not add substantial value to the presentation of such limited data. Instead, we have summarised these HF events and associated HRs narratively in the "3.3. T1 and ECV Findings and Meta-Analysis Results" section for greater conciseness. We felt a table would not be necessary in this context, as the scarcity of papers commenting on HF events (just three out of 17) allows for effective summarisation without tabular formatting.

1. Propose a risk-stratification algorithm

We are grateful for this suggestion. We have now proposed a detailed risk-stratification algorithm in a new subsection titled "Risk Stratification" at the end of the "Discussion" section.

1. Note the lack of studies linking T1/ECV changes to hard outcomes (e.g., mortality).

We thank the reviewer for highlighting this important point. We have now explicitly noted the lack of studies linking T1/ECV changes to hard outcomes, such as mortality, in the "Prognostic Implications" subsection of the "Discussion" section.

1. Briefly address CMR’s cost versus long-term HF savings.

We appreciate this comment. We have now briefly addressed CMR’s cost versus potential long-term HF savings in the "Clinical Applications" subsection of the "Discussion" section.

Reviewer 2 Report

Comments and Suggestions for Authors

I have appropriately reviewed the paper entitled “Systematic Review and Meta-Analysis of Cardiac MRI T1 and ECV Measurements in Pre-Heart Failure Populations”. This systematic review and meta-analysis evaluates the diagnostic and prognostic utility of “cardiac MRI (CMR) T1 mapping and extracellular volume (ECV)” measurements in “pre-heart failure (pre-HF)” populations—those with risk factors (Stage A) or subclinical myocardial changes (Stage B). The review synthesizes findings from “17 studies” involving >3,300 participants and performs a quantitative analysis to compare T1/ECV values in pre-HF vs. control groups. Pre-HF is a critical period where interventions can prevent irreversible damage. The use of CMR as a non-invasive tool to detect subclinical myocardial fibrosis is well-justified. Meta-analyses for both T1 (MD: 27.62 ms) and ECV (MD: 2.97%) showed statistically significant elevations in pre-HF populations. Highlights implications for screening in HCM, risk stratification for ICDs, and potential use of therapies like SGLT2 inhibitors and tafamidis. However, there was a high heterogeneity. T1: I² = 96%, ECV: I² = 94% — very high. Possible cause of such a high heterogeneity might be; variable definitions of pre-HF, CMR field strength (1.5T vs. 3T), sequences (MOLLI, ShMOLLI), and inclusion of diverse pathologies (T2DM, HTN, HCM, amyloidosis). This severely limits generalizability. There is also a variable study quality. RQS scores ranged from 17.2% to 77.8% (mean 37.9%). NOS mean score of 6.2 reflects moderate quality overall. Many included studies lacked longitudinal follow-up or histological correlation. Both T1 and ECV can be influenced by factors like edema or infiltration—not specific to fibrosis. Many studies do not specify scanner vendor, sequence details, or contrast agents—key variables in T1/ECV measurements. The mean difference in T1 values (≈ 27 ms) is clinically modest but may be meaningful depending on context (e.g., amyloidosis shows much larger changes). ECV increases (≈ 3%) are more consistently prognostic across diseases and are easier to standardize. Please analyze 1.5T vs. 3T and MOLLI vs. ShMOLLI separately to reduce heterogeneity. Only a few studies link T1/ECV changes to hard endpoints like HF hospitalization or mortality. Please include clear diagnostic criteria or consider using a Delphi process to align studies. Future work should aim to validate T1/ECV thresholds in large, diverse cohorts (e.g., UK Biobank). The high heterogeneity and inconsistent definitions temper its impact, but its findings support the use of CMR biomarkers (particularly ECV) in early HF risk stratification.

Author Response

Reviewer 2:

We would like to thank the reviewer for their thorough assessment of our manuscript. We appreciate the detailed feedback on the high heterogeneity observed in the meta-analyses (I² = 96% for T1 and 94% for ECV) and the potential causes, including variable definitions of pre-HF, CMR field strength, sequences, and diverse pathologies. We have now discussed these factors in greater detail in the "Methodological Variability and Quality" subsection of the "Discussion" section to better explain the sources of heterogeneity and their impact on generalizability.

Regarding the suggestion to analyze 1.5T vs. 3T and MOLLI vs. ShMOLLI separately to reduce heterogeneity, we carefully considered this approach. However, after re-evaluating the data, we determined that performing these subgroup analyses would require re-running the entire meta-analysis, which was not feasible within the scope of the current revisions and timeline. Additionally, the limited number of studies in each subgroup (e.g., only a few using ShMOLLI) would likely result in underpowered analyses with wide confidence intervals, potentially leading to unreliable conclusions. We have instead tabulated these protocol differences in Table 1 and discussed their contribution to heterogeneity in the "Discussion" section, while emphasizing the need for standardized protocols in future studies.

We also considered the recommendation to include clear diagnostic criteria for pre-HF or to use a Delphi process to align studies. While a Delphi process could help achieve consensus on diagnostic criteria, we opted not to pursue this, as it would introduce a level of subjectivity and complexity beyond the scope of a systematic review and meta-analysis focused on synthesizing existing evidence. Instead, we have clarified the variability in pre-HF definitions across studies in the "Discussion" section and highlighted the need for more consistent criteria in future research.

We believe these adjustments address the reviewer's concerns while maintaining the integrity of the analysis.

Reviewer 3 Report

Comments and Suggestions for Authors

In this systematic review and meta-analysis, the authors aimed to evaluate the role of T1 and ECV mapping in pre-HF populations, focusing on their diagnostic and prognostic utility. 

17 studies were included.

Studies consistently reported elevated T1 and ECV in pre-HF groups compared to controls. Meta-analysis showed a significant increase in T1 and ECV in pre-HF group, reflecting interstitial expansion and fibrosis.

The authors concluded that T1 and ECV mapping enhance CMR-based detection of early myocardial changes in pre-HF, offering a promising non-invasive approach to predict HF risk.

T2DM, AL amyloidosis, and pulmonary hypertension showed the most pronounced elevations.

The manuscript is well written, the statistical analysis is well done, the tables are figures are clear, the references are appropriate and the conclusions are supported by the results of the study. The authors' findings are innovative, revealing the importance of two CMR-derived parameters able to identify subclinical myocardial dysfunction in pre-HF cohorts.

I have only one suggestion for the authors.

Due to the high costs, limited CMR availability, and labour-intensive segmentation, in the paragraph "4.7. Clinical Implications and Future Directions" the authors could also mention and discuss alternative imaging modalities able to detect subclinical myocardial dysfunction in pre-HF cohorts, especially speckle tracking echocardiography (PMID: 33116724 and PMID: 40103545). This innovative imaging modality should be considered for implementation in clinical practice for a more comprehensive noninvasive evaluation of pre-HF cohorts.

 

 

 

Author Response

Reviewer 3:

We would like to thank the reviewer for their positive feedback and for highlighting the innovative nature of our findings regarding T1 and ECV as CMR-derived parameters for identifying subclinical myocardial dysfunction in pre-HF cohorts.

In response to the suggestion to mention and discuss alternative imaging modalities such as speckle tracking echocardiography (STE) due to the high costs, limited availability, and labour-intensive segmentation of CMR, we have now incorporated this into the "Clinical Implications and Future Directions" subsection of the "Discussion" section. We referenced the provided PMIDs (33116724 and 40103545) and discussed how STE offers a more accessible and cost-effective option for detecting subclinical myocardial dysfunction, with potential for broader implementation in clinical practice.