Back

Maximum Wall Thickness and Papillary Muscle Hypertrophy as Complementary Cardiac Biomarkers in Fabry Disease

Schüttler, M.; Witte, J.; Nordbeck, P.; Schindehütte, M.; Ankenbrand, M.

2026-05-07 cardiovascular medicine
10.64898/2026.05.06.26352512 medRxiv
Show abstract

BackgroundFabry disease (O_SCPLOWFDC_SCPLOW) is a rare and severe disease affecting multiple organ systems. However, its non-specific and heterogeneous presentation poses a critical challenge for early diagnosis, often delaying necessary treatment. In re-cent years, imaging-based biomarkers have been increasingly proposed to improve the understanding of O_SCPLOWFDC_SCPLOW and aid its diagnosis. This study presents a comprehensive comparative analysis of several previously proposed imaging-based cardiac biomarkers to assess their potential for diagnostic use. MethodsWe have developed a fully automated image analysis pipeline for quantifying cardiac metrics based on short-axis cine O_SCPLOWCMRC_SCPLOW data available on the UK Biobank. ResultsBased on the UK Biobank cohort, our analyses confirm the diagnostic relevance of the maximum myocardial wall thickness, a metric that mimics the current clinical practice for diagnosing left ventricular hypertrophy. Initial evidence also suggests that the PM/LV ratio, which measures the papillary muscle hypertrophy as the ratio between the areas of the papillary muscles and the left ventricular cavity, has potential prognostic relevance. ConclusionThis study contributes towards a better understanding of the cardiac presentation of FD, which may support future research in improving the diagnostic process. Additionally, our analysis pipeline can serve as a valuable basis for additional data analysis of imaging-based biomarkers for O_SCPLOWFDC_SCPLOW and other diseases.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
Frontiers in Cardiovascular Medicine
49 papers in training set
Top 0.1%
19.0%
2
Orphanet Journal of Rare Diseases
18 papers in training set
Top 0.1%
8.5%
3
Scientific Reports
3102 papers in training set
Top 13%
6.9%
4
PLOS ONE
4510 papers in training set
Top 26%
6.5%
5
The American Journal of Cardiology
15 papers in training set
Top 0.6%
3.6%
6
Journal of Clinical Medicine
91 papers in training set
Top 1%
3.6%
7
Journal of the American Heart Association
119 papers in training set
Top 2%
3.6%
50% of probability mass above
8
Diagnostics
48 papers in training set
Top 0.5%
3.1%
9
Computers in Biology and Medicine
120 papers in training set
Top 1%
3.1%
10
Frontiers in Physiology
93 papers in training set
Top 1%
3.1%
11
BMJ Open
554 papers in training set
Top 7%
2.4%
12
BMC Cardiovascular Disorders
14 papers in training set
Top 0.8%
2.1%
13
Cureus
67 papers in training set
Top 2%
1.9%
14
Frontiers in Neurology
91 papers in training set
Top 3%
1.8%
15
Heart
10 papers in training set
Top 0.5%
1.7%
16
European Heart Journal - Digital Health
15 papers in training set
Top 0.4%
1.5%
17
Ultrasound in Medicine & Biology
10 papers in training set
Top 0.2%
1.5%
18
Open Heart
19 papers in training set
Top 0.8%
1.4%
19
European Heart Journal
16 papers in training set
Top 0.5%
1.4%
20
Genes
126 papers in training set
Top 2%
1.2%
21
Biomedicines
66 papers in training set
Top 2%
1.2%
22
Journal of Translational Medicine
46 papers in training set
Top 1%
1.2%
23
Frontiers in Cellular and Infection Microbiology
98 papers in training set
Top 4%
1.0%
24
Journal of Molecular and Cellular Cardiology
39 papers in training set
Top 0.7%
0.8%
25
Journal of Medical Virology
137 papers in training set
Top 4%
0.8%
26
Journal of Internal Medicine
12 papers in training set
Top 0.6%
0.8%
27
Biology Methods and Protocols
53 papers in training set
Top 3%
0.7%
28
BMC Medical Genomics
36 papers in training set
Top 1%
0.7%
29
Human Genomics
21 papers in training set
Top 0.5%
0.7%
30
Journal of the American College of Cardiology
12 papers in training set
Top 0.8%
0.7%