https://orcid.org/0000-0002-2176-8516
Abstract
Cardiac magnetic resonance (CMR) parametric mapping is underexplored in cardiac tumours. To evaluate the contribution of mapping sequences on the characterization of paediatric tumours.
All paediatric patients referred for cardiac tumours at Bambino Gesù Children’s Hospital from June 2017 to November 2023, who underwent CMR with mapping sequences, were included. The diagnosis of tumour type was performed according to signal characteristics on different sequences. Mass parametric mapping for each subtype and interobserver variability was assessed. Sixteen patients were enrolled. The mean age at CMR was 7 ± 5 years. ‘Traditional’ mass type assessment diagnosed haemangioma (Group A) in three patients (19%), fibroma (Group B) in four patients (25%), rhabdomyoma (Group C) in six patients (37%), and lipoma (Group D) in three patients (19%). The analysis of variance analysis revealed significant differences in mass native T1 and mass extracellular volume (ECV) values among the four subgroups (P < 0.001 for both comparisons). The mean native T1 and ECV values were respectively 1465 ± 158 ms and 54 ± 4% for Group A, 860 ± 118 ms and 93 ± 4% for Group B, 1007 ± 57 ms and 23 ± 5% for Group C, and 215 ± 13 ms and 0 ± 0% for Group D.
Mass mapping analysis is feasible and reproducible in children. ECV values provide the most accurate differentiation. Mass ECV consistently resembles normal myocardium in rhabdomyoma, is extremely high (approaching 100%) in fibroma, equals to zero in lipoma, and matches blood pool ECV (1-Hct) in haemangioma.
Overview of extracellular volume (ECV) values of the most prevalent histotypes of paediatric cardiac tumours.
Introduction
Cardiac tumours represent a heterogenous group of lesions characterized by primary and secondary neoplasms, both benign and malignant.1 Primary cardiac tumours are exceptionally uncommon in children. The majority of these tumours in children is benign, while roughly 10% are identified as malignant. Among paediatric tumours, the most common ones are rhabdomyoma, teratoma, fibroma, and haemangioma.2
Cardiac magnetic resonance (CMR) imaging is considered the gold standard technique for non-invasive evaluation of cardiac masses.3 Specific cardiac MRI diagnostic criteria to predict paediatric tumour type have been established.4,5 These criteria rely on qualitative assessment through conventional signal intensity sequences. Recently, the advent of novel techniques such as parametric mapping has enabled the detection of myocardial and tissue abnormalities beyond the ability of conventional qualitative assessment.6 Consequently, T1 and T2 mapping and extracellular volume (ECV) quantification have swiftly integrated into standard CMR imaging protocols.7–9 Nevertheless, mapping sequences have been underexplored in characterizing cardiac tumours.10
Recently, there has been a suggestion to incorporate these techniques into the standard protocol for characterizing myocardial masses, despite the absence of significant data supporting their use in this setting.3
The objective of this study was to evaluate the contribution of mapping sequences in the CMR examination of a diverse cohort of primary paediatric tumours.
Methods
Study population and design
The study was structured as a retrospective single-centre investigation. All paediatric (<18 years old at CMR) patients referred for suspected cardiac tumours at Bambino Gesù Children’s Hospital from June 2017 to November 2023, who underwent CMR with parametric mapping sequences, were included in the study. Informed consent was obtained from all patients, and the study received approval from the ethics committee of Bambino Gesù Children’s Hospital.
Patients with very small masses, where obtaining a consistent mapping analysis was not feasible, were excluded from the study. Additionally, patients with teratoma were excluded due to the substantial heterogeneity of the mass, rendering it impossible to derive a singular mapping value.
The diagnosis of tumour type was performed according to previously published criteria4 based on signal characteristics on different sequences. Tumour characteristics were evaluated by two different investigators (Paolo Ciliberti. and A.P., a CMR-expert cardiologist with 9 years of experience and a CMR-focused radiology resident in training with 2 years of experience, respectively) blinded to clinical information. Additional details including size, location, presence of multiple masses, homogeneous or heterogeneous appearance, borders, as well as the presence of pericardial/pleural effusion and tissue infiltration, were assessed. Clinical history, potential genetic diagnosis of tuberous sclerosis, and, when accessible, histologic definitive diagnosis were also considered.
The enrolled patients were categorized into four distinct subgroups based on the type of mass. Following this classification, mass native T1, T2, and ECV values for each subgroup of patients were assessed.
Mass mapping values within the various subgroups were compared to assess the possibility of presence of typical values for each type of mass, potentially useful for tissue characterization of each cardiac tumour.
CMR protocol
All CMR imaging was performed on a 1.5 Tesla scanner (MAGNETOM Aera or Sola, Siemens Healthineers, Erlangen, Germany). A 32-element coil system for signal detection was used, consisting of posterior spine coils incorporated into the scan table and an anterior phased-array body coil. A vector electrocardiographic system was employed for cardiac gating. The imaging protocol comprised of as follows:
Cine steady-state free-precession (SSFP) sequences of conventional single-slice (LV and RV two-chamber, LV three-chamber, four-chamber, LV outflow tract, and RV outflow tract) and volumetric multi-slice (short-axis) views. If necessary, modified mass-customized planes were added and repeated for all subsequent imaging;
Pre-contrast black-blood turbo-spin-echo (BB-TSE) sequences, including T1-weighted images with and without fat saturation and T2-weighted images;
First pass perfusion (FPP) sequences during intravenous administration of 0.1 mmol/kg of gadolinium-based contrast medium;
Late gadolinium enhancement (LGE) sequences performed 8–10 min after contrast, typically preceded by a sequence (TI-scout) for correct selection of the inversion time;
Mapping sequences, including motion-corrected modified look locker inversion recovery (MOLLI) T1 mapping and true fast imaging (TRUFI) T2 mapping. T1 mapping was acquired both pre-contrast (native T1) with a 5(3)3 scheme and post-contrast with a 4(1)3(1)2 scheme (for ECV calculation).
More detailed sequence parameters are summarized in the Supplementary data online, Table S1.
ECV was calculated on synthetic ECV maps, provided either directly by the scanner or obtained through the software, without haematocrit sampling as described and validated in the literature.11,12
Parametric mapping analysis and interobserver variability
Mapping values (T1, T2, and ECV) were analysed for all tumours by the two readers. They were blinded to patient diagnosis and performed measurements in a random order using commercially available software (cvi42; Circle Cardiovascular Imaging). Both readers calculated the mean value obtained for each map by placing three non-overlapping regions of interest (ROI) of ∼50 mm² within the tumour, as well as an additional ROI encompassing the entire lesion. The agreement between the two readers was assessed.
Statistical analysis
Continuous variables were expressed as mean with standard deviation, while categorical variables were presented as number and percentage.
Interobserver variability in mapping parameters was evaluated through Bland–Altman plot analysis and intra-class correlation coefficients (ICC). Cut-off values for ICC were categorized as follows: <0.5 for poor agreement, between 0.5 and 0.75 for moderate agreement, between 0.75 and 0.9 for good agreement, and >0.9 for excellent agreement.
Variations in the means of T1 mapping, T2 mapping, and ECV among different lesions were examined through one-way analysis of variance (ANOVA). Following a positive ANOVA test, post hoc comparisons among subgroups were performed using the Scheffé test. Prior to conducting the ANOVA test, Levene’s Test for Equality of Variances was employed to evaluate the homogeneity of mapping values within each subgroup of the cohort.
P < 0.05 was considered statistically significant.
Statistical analysis was performed using Medcalc statistical software.
Results
Study population
Since mapping sequences became available at our centre (June 2017), 31 patients with cardiac masses have been studied in our laboratory. Four patients were excluded because they were adults, seven patients were excluded because the masses were too small (≤1 cm in maximum diameter) for adequate quantification with the mapping sequences, and four were excluded because they were not present in other patients in the case series (one cyst, one myxoma, one thrombus, one teratoma), which limited the possibility of statistical analysis. The patient with the teratoma was also excluded due to the extreme heterogeneity of the mass.
Sixteen patients were enrolled in the study. Nine patients were female (56%), and seven patients (44%) were male. Mean age at time of CMR was 7 ± 5 years. All patients had masses with well-defined margins, homogeneous appearance, and no signs of infiltration. Qualitative, ‘traditional’ mass type assessment diagnosed haemangioma in three patients (19%), fibroma in four patients (25%), rhabdomyoma in six patients (37%), and lipoma in three patients (19%). The agreement between the two readers was 100% for the ‘traditional’ mass type assessment, relying on signal characteristics. Among these, three patients (two with fibroma and one with haemangioma) had a confirmed histological bioptic diagnosis. The main demographic data of the entire cohort are summarized in Table 1.
Main characteristics of the entire cohort
| N = 16 | |
|---|---|
| Age at CMR, years | 7 ± 5 |
| Male/female sex, n (%) | 7 (44%)/9 (56%) |
| Weight, kg | 29 ± 24 |
| BSA, m2 | 1 ± 0.6 |
| Mass type | |
| Haemangioma, n (%) | 3 (19%) |
| Fibroma, n (%) | 4 (25%) |
| Rhabdomyoma, n (%) | 6 (37%) |
| Lipoma, n (%) | 3 (19%) |
| Mass max dimension, mm | 36 ± 21 |
| N = 16 | |
|---|---|
| Age at CMR, years | 7 ± 5 |
| Male/female sex, n (%) | 7 (44%)/9 (56%) |
| Weight, kg | 29 ± 24 |
| BSA, m2 | 1 ± 0.6 |
| Mass type | |
| Haemangioma, n (%) | 3 (19%) |
| Fibroma, n (%) | 4 (25%) |
| Rhabdomyoma, n (%) | 6 (37%) |
| Lipoma, n (%) | 3 (19%) |
| Mass max dimension, mm | 36 ± 21 |
Main characteristics of the entire cohort
| N = 16 | |
|---|---|
| Age at CMR, years | 7 ± 5 |
| Male/female sex, n (%) | 7 (44%)/9 (56%) |
| Weight, kg | 29 ± 24 |
| BSA, m2 | 1 ± 0.6 |
| Mass type | |
| Haemangioma, n (%) | 3 (19%) |
| Fibroma, n (%) | 4 (25%) |
| Rhabdomyoma, n (%) | 6 (37%) |
| Lipoma, n (%) | 3 (19%) |
| Mass max dimension, mm | 36 ± 21 |
| N = 16 | |
|---|---|
| Age at CMR, years | 7 ± 5 |
| Male/female sex, n (%) | 7 (44%)/9 (56%) |
| Weight, kg | 29 ± 24 |
| BSA, m2 | 1 ± 0.6 |
| Mass type | |
| Haemangioma, n (%) | 3 (19%) |
| Fibroma, n (%) | 4 (25%) |
| Rhabdomyoma, n (%) | 6 (37%) |
| Lipoma, n (%) | 3 (19%) |
| Mass max dimension, mm | 36 ± 21 |
Patients were then categorized into distinct groups based on their diagnoses as follows: Group A comprised individuals diagnosed with haemangioma, Group B included those with fibroma, Group C involved patients with rhabdomyoma, and Group D consisted of children with lipoma. Main demographic data of each subgroup are summarized in Table 2.
Main characteristics of each study subgroup
| Mass type | Haemangioma | Fibroma | Rhabdomyoma | Lipoma |
|---|---|---|---|---|
| Patients, n | 3 | 4 | 6 | 3 |
| Age at CMR, years | 6 ± 5.6 | 11 ± 2.1 | 2 ± 1.9 | 13 ± 1.7 |
| Male/female, n (%) | 1 (33%)/2 (67%) | 2 (50%)/2 (50%) | 2 (33%)/4 (67%) | 2 (66%)/1 (33%) |
| Weight, kg | 22 ± 20 | 43 ± 22 | 9 ± 5 | 56 ± 14 |
| BSA, m2 | 1 ± 0.6 | 1 ± 0.4 | 0.4 ± 0.2 | 1.6 ± 0.2 |
| Mass location, n (%) | ||||
| Left ventricle | 2 (66%) | 3 (75%) | 2 (33%) | 1 (33%) |
| Right ventricle | 1 (17%) | 1 (33%) | ||
| Interventricular septum | 1 (25%) | 3 (50%) | 1 (33%) | |
| Right atrium | 1 (33%) | |||
| Mass max dimension, mm | 33 ± 11 | 65 ± 14 | 21 ± 10 | 33 ± 11 |
| Mass type | Haemangioma | Fibroma | Rhabdomyoma | Lipoma |
|---|---|---|---|---|
| Patients, n | 3 | 4 | 6 | 3 |
| Age at CMR, years | 6 ± 5.6 | 11 ± 2.1 | 2 ± 1.9 | 13 ± 1.7 |
| Male/female, n (%) | 1 (33%)/2 (67%) | 2 (50%)/2 (50%) | 2 (33%)/4 (67%) | 2 (66%)/1 (33%) |
| Weight, kg | 22 ± 20 | 43 ± 22 | 9 ± 5 | 56 ± 14 |
| BSA, m2 | 1 ± 0.6 | 1 ± 0.4 | 0.4 ± 0.2 | 1.6 ± 0.2 |
| Mass location, n (%) | ||||
| Left ventricle | 2 (66%) | 3 (75%) | 2 (33%) | 1 (33%) |
| Right ventricle | 1 (17%) | 1 (33%) | ||
| Interventricular septum | 1 (25%) | 3 (50%) | 1 (33%) | |
| Right atrium | 1 (33%) | |||
| Mass max dimension, mm | 33 ± 11 | 65 ± 14 | 21 ± 10 | 33 ± 11 |
Main characteristics of each study subgroup
| Mass type | Haemangioma | Fibroma | Rhabdomyoma | Lipoma |
|---|---|---|---|---|
| Patients, n | 3 | 4 | 6 | 3 |
| Age at CMR, years | 6 ± 5.6 | 11 ± 2.1 | 2 ± 1.9 | 13 ± 1.7 |
| Male/female, n (%) | 1 (33%)/2 (67%) | 2 (50%)/2 (50%) | 2 (33%)/4 (67%) | 2 (66%)/1 (33%) |
| Weight, kg | 22 ± 20 | 43 ± 22 | 9 ± 5 | 56 ± 14 |
| BSA, m2 | 1 ± 0.6 | 1 ± 0.4 | 0.4 ± 0.2 | 1.6 ± 0.2 |
| Mass location, n (%) | ||||
| Left ventricle | 2 (66%) | 3 (75%) | 2 (33%) | 1 (33%) |
| Right ventricle | 1 (17%) | 1 (33%) | ||
| Interventricular septum | 1 (25%) | 3 (50%) | 1 (33%) | |
| Right atrium | 1 (33%) | |||
| Mass max dimension, mm | 33 ± 11 | 65 ± 14 | 21 ± 10 | 33 ± 11 |
| Mass type | Haemangioma | Fibroma | Rhabdomyoma | Lipoma |
|---|---|---|---|---|
| Patients, n | 3 | 4 | 6 | 3 |
| Age at CMR, years | 6 ± 5.6 | 11 ± 2.1 | 2 ± 1.9 | 13 ± 1.7 |
| Male/female, n (%) | 1 (33%)/2 (67%) | 2 (50%)/2 (50%) | 2 (33%)/4 (67%) | 2 (66%)/1 (33%) |
| Weight, kg | 22 ± 20 | 43 ± 22 | 9 ± 5 | 56 ± 14 |
| BSA, m2 | 1 ± 0.6 | 1 ± 0.4 | 0.4 ± 0.2 | 1.6 ± 0.2 |
| Mass location, n (%) | ||||
| Left ventricle | 2 (66%) | 3 (75%) | 2 (33%) | 1 (33%) |
| Right ventricle | 1 (17%) | 1 (33%) | ||
| Interventricular septum | 1 (25%) | 3 (50%) | 1 (33%) | |
| Right atrium | 1 (33%) | |||
| Mass max dimension, mm | 33 ± 11 | 65 ± 14 | 21 ± 10 | 33 ± 11 |
Interobserver variability for mass mapping analysis
The Bland–Altman plot (Figure 1), comparing mass mapping analysis between reader 1 and reader 2, demonstrated excellent agreement, as indicated by all differences falling within the limits (±1.96 times the standard deviation). Notably, the difference for mass native T1 reached the upper limit of the range in just one instance.
Bland–Altman plot comparing mass mapping analysis between the two observers. Bland–Altman plot comparing mass mapping analysis between reader 1 and reader 2. Horizontal lines are drawn at the mean difference (blue lines), at the limits of agreement (mean difference plus and minus 1.96 times the standard deviation of the differences; brick red dotted lines), at line of equality (orange dotted line) and at the 95% CI of mean of differences (green dotted lines).
Furthermore, the ICC analysis also demonstrated excellent agreement for all mapping analyses. ICC between the two readers for single measures and absolute agreement was 0.9995 for mass native T1, 0.9957 for mass ECV, and 0.9979 for mass T2 analysis.
Mass mapping analysis
Mean native T1 mapping value of the mass was 1465 ± 158 ms in haemangioma group, 860 ± 118 ms in fibroma group, 1007 ± 57 ms in rhabdomyoma group, and 215 ± 13 ms in lipoma group. Mean T2 mapping value of the mass was 84 ± 24 ms in haemangioma group, 43 ± 4 ms in fibroma group, 67 ± 17 ms in rhabdomyoma group, and 168 ± 115 ms in lipoma group. Mean ECV value of the mass was 54 ± 4% in haemangioma group, 93 ± 4 ms in fibroma group, 23 ± 5 ms in rhabdomyoma group, and 0 ± 0 ms in lipoma group. Values of mass mapping among the different subgroups are summarized in Table 3.
Main mass mapping characteristics among the four different groups
| Mass type | Haemangioma | Fibroma | Rhabdomyoma | Lipoma |
|---|---|---|---|---|
| Patients, n | 3 | 4 | 6 | 3 |
| T1, ms | 1465 ± 158 | 860 ± 118 | 1007 ± 57 | 215 ± 13 |
| T2, ms | 84 ± 24 | 43 ± 4 | 67 ± 17 | 168 ± 115 |
| ECV, % | 54 ± 4 | 93 ± 4 | 23 ± 5 | 0 ± 0 |
| Mass type | Haemangioma | Fibroma | Rhabdomyoma | Lipoma |
|---|---|---|---|---|
| Patients, n | 3 | 4 | 6 | 3 |
| T1, ms | 1465 ± 158 | 860 ± 118 | 1007 ± 57 | 215 ± 13 |
| T2, ms | 84 ± 24 | 43 ± 4 | 67 ± 17 | 168 ± 115 |
| ECV, % | 54 ± 4 | 93 ± 4 | 23 ± 5 | 0 ± 0 |
Main mass mapping characteristics among the four different groups
| Mass type | Haemangioma | Fibroma | Rhabdomyoma | Lipoma |
|---|---|---|---|---|
| Patients, n | 3 | 4 | 6 | 3 |
| T1, ms | 1465 ± 158 | 860 ± 118 | 1007 ± 57 | 215 ± 13 |
| T2, ms | 84 ± 24 | 43 ± 4 | 67 ± 17 | 168 ± 115 |
| ECV, % | 54 ± 4 | 93 ± 4 | 23 ± 5 | 0 ± 0 |
| Mass type | Haemangioma | Fibroma | Rhabdomyoma | Lipoma |
|---|---|---|---|---|
| Patients, n | 3 | 4 | 6 | 3 |
| T1, ms | 1465 ± 158 | 860 ± 118 | 1007 ± 57 | 215 ± 13 |
| T2, ms | 84 ± 24 | 43 ± 4 | 67 ± 17 | 168 ± 115 |
| ECV, % | 54 ± 4 | 93 ± 4 | 23 ± 5 | 0 ± 0 |
Remote myocardium mean values for the entire cohort were as follows: native T1 1031 ± 57 ms; T2 51 ± 4 ms; and ECV 27 ± 4%.
Comparison of mass mapping values among the subgroups
Prior to the ANOVA test, Levene’s Test for Equality of Variances was performed. The test was negative (P > 0.05) for both native T1 mapping (0078) and ECV (0,1), demonstrating the variances in the different subgroups were not significantly different. In contrast, for T2 mapping, the Levene’s test yielded a P-value of 0.007, indicating significant differences in variances for this measurement among the subgroups.
The ANOVA analysis revealed significant differences in mass native T1 mapping and mass ECV values among the four subgroups (P < 0.001 for both comparisons).
Despite Levene’s test indicating non-homogeneity of variances for T2 mass values, we proceeded with the ANOVA due to the small sample size, which yielded significant differences (P = 0.033). However, it is crucial to interpret the results cautiously, considering the violation of the homogeneity assumption. Figure 2 illustrates the primary comparisons for the three parameters and depicts the post hoc analyses conducted among the four different subgroups.
Parametric mapping values among the different histotypes. Comparison among the four different groups of mass mapping values, with bars representing the mean values. Error bars are set at a 95% confidence interval for the mean. The P-value in orange (above and in bigger font) shows the level of significance of the ANOVA primary comparison among all subgroups. In black (below) are highlighted the individual subgroup comparisons that reach significance (P < 0.05) in the post hoc analysis.
Discussion
CMR parametric mapping is a novel technique providing spatial visualization of quantitative changes in the myocardium based on variations in myocardial parameters (T1, T2, and ECV).6 Parametric mapping has been underutilized in characterizing cardiac tumours, primarily owing to the rarity of this condition. In our study, we tested parametric mapping in a cohort of most common benign paediatric cardiac masses. In particular, our series included the most common forms of paediatric tumours with the exception of teratoma, which was excluded due to its significant heterogeneity, which prevented the detection of reproducible values. In fact, the diagnosis of teratoma primarily relies on this heterogeneity, characterized by the presence of a variety of different tissues with solid and cystic components.4
We initially established that mass mapping analysis is reproducible among different observers, demonstrating excellent agreement between our two readers, thus ensuring reliable evaluation. In addition to excluding heterogeneous masses such as teratomas, we omitted small tumours where obtaining consistent parametric mapping values was not feasible. Undoubtedly, this has simplified and enhanced reproducibility.
We then demonstrated that each subtype of cardiac mass exhibits distinct typical T1 mapping and ECV values, significantly differing among various histotypes. Mean T2 values showed statistical differences among some of the subgroups, notably between lipoma and fibroma. However, significant variations in T2 values were also observed within the same group, such as among patients with lipoma, thus making T2 analysis unreliable in this setting.
The primary signal characteristics, as well as ECV and T1 map findings for all subtypes, are succinctly summarized in Figure 3.
Main CMR findings in benign cardiac tumours. Haemangioma (LV antero-lateral wall): hyperintense on CINE SSFP, isointense to normal myocardium on T1w, slight hyperintense on T2w, intense heterogenous FPP enhancement, and marked LGE. T1 native and ECV values comparable to the blood pool. Fibroma (LV inferior wall): heterogeneously isointense on CINE SSFP and T1w images, mildly hypointense on T2w, poor contrast uptake during FPP, and homogeneously hyperintense on LGE sequences. T1 native values lower than remote myocardium and extremely high ECV (approaching 100%). Rhabdomyoma (right side of the inferior interventricular septum): isointense to remote myocardium on CINE SSFP, T1w, and T2w sequences; no significant enhancement both on FFP and LGE images. Native T1 and ECV values comparable to remote myocardium. Lipoma (RV free wall): hyperintense on all non-fat saturated pre-contrast sequences, along with chemical shift artefacts on CINE SSFP images; no contrast enhancement on FPP and LGE sequences. Very low T1 native values and ECV (approaching to zero). CINE SSFP, cine steady-state free-precession; ECV, extracellular volume; FPP, first pass perfusion; LGE, late gadolinium enhancement; LV, left ventricle; RV, right ventricle.
In terms of native T1 values, as anticipated, rhabdomyomas exhibited values akin to the myocardium, haemangiomas demonstrated values comparable to the blood pool, and lipomas showed values similar to subcutaneous fat. On the other hand, fibromas did not have higher values compared with the myocardium, contrary to what one might expect given their primarily fibrotic nature, but instead quite the opposite with lower values, averaging around 860 ms. We do not have a definitive explanation for this finding, but it could be elucidated by examining the histological composition of these masses. They predominantly consist of fibroblasts and connective tissues with very limited vascularization.13 The hypo-vascularization compared with normal myocardium, as evidenced by the hypo-enhancement during FPP, could account for the lower native T1 values observed compared with the healthy heart muscle. However, the inherent fibrotic nature of these masses is distinctly apparent in the ECV analysis. As ECV considers both pre- and post-contrast behaviour, it is capable of overcoming the limited vascular component and of revealing the fibrous characteristics with markedly elevated ECV values.
Indeed, ECV is the mapping parameter that appears to be by far the most useful, providing characteristic values for each type of mass. Mass ECV is similar to normal myocardium for rhabdomyomas, extremely high for fibromas, equal to 0 for lipomas, and equivalent to the blood pool for haemangiomas. ECV findings in the different mass histotypes are summarized in the graphical abstract.
Rhabdomyomas show similar native T1 and ECV values to remote myocardium, likely due to their similar histological composition. They represent a subtype of hamartoma commonly identified in paediatric patients.14 As hamartomas, they are characterized by abnormal proliferation of normal tissues.
Haemangiomas are non-malignant vascular tumours consisting of blood vessels, composed of a benign proliferation of vascular endothelial cells. They can be compared with a tissue resembling blood, characterized by multiple vascular structures containing blood.15,16 Haemangiomas, in fact, exhibit an average ECV value of 54%, which is approximately equal to 100% minus the average haematocrit value. If we consider the ECV calculation formula17 (Mass ECV = (1 − haematocrit) × ((1/post-contrast mass T1-1/native mass T1)/(1/post-contrast T1 blood-1/native T1 blood))), given that the pre- and post-contrast T1 values of the blood pool and the mass are equivalent, the formula simplifies to Mass ECV = 1 − HCT, which indeed equals the blood pool ECV.
As with native T1 values in fibromas, the consistent result of mass ECV equal to zero in lipomas lacks a clear explanation. Perhaps, a preliminary general hypothesis lies in the nature of these masses, primarily composed of mature fat cells with increased intracellular fat deposits and limited extracellular volume. Native T1 mapping has been already demonstrated to be useful in identifying intra-myocardial fat regions, as seen in areas of post-infarction adipose metaplasia17,18 or in hypertrophy of the inter-atrial septum.19 Instead, there are scarce data on adipose tissue post-contrast T1 and ECV.
In our lipomas, an unexpected rise in T1 relaxation time was observed in the T1-enhanced map compared with the native T1. This elevation following the injection of the contrast agent results in mathematically negative ECV values. However, these values are virtually zero due to the inherent nature of the calculated percentage data. This paradoxical effect might be explained by the paradoxical suppression of signal intensity by gadolinium in fatty tissue.20 In subcutaneous or perivisceral adipose tissue, a comparable finding of a relative increase in T1 enhancement and virtually zero ECV was noted. This observation helps to define the characteristics of this subgroup of cardiac masses as being adipose in nature.
Finally, the extremely high ECV values observed in fibromas (approaching 100%) can be accounted for by the histological composition of these tumours, characterized by an aggregation of fibroblasts intermixed with substantial quantities of collagen, consequently resulting in a pronounced extracellular matrix content. Gadolinium permeates these interstitial compartments but does not cross cell membranes, leading to a delayed and persistent elevation in gadolinium concentration.21
Starting from the premise that in non-biopsy tissue characterization, any methodology does not provide diagnostic certainty but rather a suspicion about the nature of the mass, it could be argued that our data do not add significant information compared with what can be assessed using standard sequences. Nevertheless, our findings offer a straightforward quantitative assessment, enabling precise and well-defined categorization among various histotypes. This capability can be pivotal in the diagnostic workup, particularly for ambiguous cases, either confirming or refuting the diagnostic suspicion derived from standard sequences.
CMR is confirmed to be reference method for studying myocardial masses, even in children. However, in this context, it is crucial to emphasize that due to intrinsic limitations often stemming from low body weight, high heart rate, and reduced patient cooperation, these patients should always be examined in specialized paediatric imaging centres with high patient volume.22
As with congenital heart diseases in paediatric patients,23 CMR typically provides the opportunity for comprehensive and thorough evaluation. In some cases, however, additional computed tomography (CT) imaging may be necessary, particularly when assessing the relationship of the mass with the coronary branches, which can be visualized with greater accuracy using CT, especially in the mid to distal segments, even in paediatric patients.24
The main limitation of our study is the small sample size, a challenge inherent to any investigation regarding cardiac tumours due to their rarity. Indeed, our cohort is relatively extensive, particularly considering that we are dealing exclusively with paediatric cardiac masses. Nevertheless, our results represent initial data, which need further investigation and validation in a larger cohort.
Conclusions
Parametric mapping analysis is feasible and reproducible in children affected by cardiac tumours. Mass native T1 and ECV values significantly differ among various histotypes.
ECV values appear to provide the most accurate differentiation among the commonest subtypes of benign paediatric cardiac masses. Mass ECV consistently resembles normal myocardium in rhabdomyoma, is extremely high (approaching 100%) in fibroma, equals to zero in lipoma, and matches blood pool ECV (1-Hct) in haemangioma. These observations offer a straightforward quantitative assessment, facilitating categorization among various histotypes, which can complement standard sequences for tissue characterization of paediatric cardiac masses.
Supplementary data
Supplementary data are available at European Heart Journal - Cardiovascular Imaging online.
Acknowledgements
The authors express their gratitude to Dr Kelvin Chow and Dr Carmel Hayes for their invaluable technical contributions to the development of the sequences utilized in this study.
Funding
This work was supported by the Italian Ministry of Health with Current Research funds.
Data availability
The data underlying this article will be shared on reasonable request to the corresponding author.
References
Author notes
Conflict of interest: None declared.
