Abstract
Background:
Growth hormone and insulin-like growth factor 1 (IGF-1) have recently been linked to temporal muscle thickness (TMT) in acromegaly; however, the relationship between treatment response and TMT remains unclear.
Objectives:
To evaluate whether TMT correlates with treatment response and may serve as a surrogate marker of disease control in patients with acromegaly.
Design:
Retrospective longitudinal two-center study.
Methods:
Patients with acromegaly and non-functioning pituitary adenomas (NFPA) were included. TMT was measured on magnetic resonance imaging scans obtained before treatment initiation and after a 3-year follow-up. Baseline TMT was compared between groups. In patients with acromegaly, TMT was correlated with IGF-1 levels at diagnosis and over time, as well as with treatment response. Mixed-effects regression models adjusted for covariates were used to assess associations.
Results:
Imaging studies from 58 subjects were analyzed (40 with acromegaly, 18 with NFPA). Pre-treatment TMT was significantly greater in patients with acromegaly compared with NFPA (mean 10.1 mm (9.3–10.7) vs 8.1 mm (8.0–9.2), p = 0.003). Higher baseline TMT was associated with higher IGF-1 levels at diagnosis (p < 0.01). Following treatment, mean TMT decreased from 9.6 mm at baseline to 8.8 mm at 36 months (p = 0.001). In covariate-adjusted mixed-effects models, higher pre-treatment TMT was independently associated with increased IGF-1 levels at diagnosis and longitudinally (β = 19.59 ng/mL, p = 0.022).
Conclusion:
TMT correlates with biochemical disease activity and decreases after treatment, suggesting it may be a useful imaging marker of clinical activity and prognosis in acromegaly.
Trial registration:
Not applicable.
Keywords: acromegaly, body composition, magnetic resonance imaging, temporal muscle thickness
Introduction
Acromegaly is a heterogeneous disorder caused by increased secretion of growth hormone (GH) and insulin-like growth factor 1 (IGF-1), with more than 95% of cases secondary to GH-secreting pituitary adenomas. 1 Excess GH and IGF-1 have multiple deleterious consequences, including impaired glucose regulation, increased cardiovascular risk, and greater mortality. Acromegaly is usually clinically suspected and thereafter diagnosed based on the abnormal growth of soft tissues and bones.2–7
Regarding muscle tissue, some studies have shown that muscle mass is increased in subjects with acromegaly.8–11 Body composition in these patients appears to vary according to disease activity, with most studies indicating that individuals with active acromegaly have higher lean body mass and total muscle mass compared with patients with controlled disease.8,9,12–15
In this context, the measurement of temporal muscle thickness (TMT) is a validated technique in both magnetic resonance imaging (MRI) and computed tomography (CT). 16 It is widely used in neuro-oncology as a surrogate parameter for a patient’s nutritional status and has been associated with mortality in patients with brain metastases, glioblastoma, and other intracranial tumors.16–18
To date, TMT has been evaluated in patients with acromegaly in only two previous studies,19,20 in which alterations in TMT were found, but no strong correlations were established with clinical status or disease control. One of these was a descriptive study that examined associations between TMT and patients’ biochemical and baseline parameters (e.g., age and sex) but did not assess IGF-1 evolution or compare results with a control group. 18 By contrast, the other study assessed changes in TMT over time, although the follow-up period was limited to 1 year, and did not examine longitudinal changes in IGF-1 levels 20 at long term. Given the known alterations in muscle mass in these individuals, the aim of our study was to assess whether changes in TMT were associated with the clinical and hormonal status of the disease and whether they could serve as a biomarker for disease progression and the likelihood of disease control.
Materials and methods
Study population and design
We conducted a retrospective, longitudinal, two-center study, including patients with acromegaly and non-functioning pituitary adenomas (NFPAs) followed up at the Endocrinology and Nutrition Units of two Spanish referral centers (Hospital Universitario de la Princesa and Hospital Universitario Ramón y Cajal).
A total of 40 patients with acromegaly diagnosed between 2005 and 2023 were included. In addition, 18 patients with NFPAs, matched by age, sex, and pituitary lesion size, were selected as controls.
The inclusion criteria were men and women ⩾18 years with a confirmed diagnosis of pituitary-origin acromegaly. Exclusion criteria included patients without a pituitary or cranial MRI prior to the initiation of medical or surgical treatment, those lacking MRI images suitable for TMT measurement, or those without baseline biochemical tests before treatment initiation. Subjects with conditions that could affect muscle mass—such as disease-related malnutrition, ongoing oncologic therapies or active neoplasms, chronic corticosteroid treatment at supraphysiologic doses, or the use of anabolic agents in the context of doping—were also excluded. In addition, patients who developed GH deficiency during follow-up were also excluded from the analysis, defined as those with panhypopituitarism and IGF-1 levels below the lower limit of normal or a peak GH <5 μg/L following insulin tolerance testing.21,22
This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines 23 (Supplemental Material S1). Ethics approval was granted by the Internal Ethics Committee of La Princesa University Hospital (code 5468), in accordance with the Declaration of Helsinki.
Procedures and definitions
The diagnosis of acromegaly was based on the current available guidelines at the time of the diagnosis.24–26 The remission of acromegaly was based on the Cortina definition (2000 criteria) (IGF-I level in age- and sex-adjusted normal range and random GH value <2.5 ng/mL and/or GH value <1 ng/mL during an oral glucose tolerance test (OGTT)) 27 and the 2010 criteria of the American Association of Clinical Endocrinologists and Endocrine Society guidelines (normal IGF-I level in age and sex and GH <0.4 ng/mL during OGTT and/or random GH <1.0 ng/mL). 25 Hormonal assays can be consulted in our previous publications 28 : serum IGF-1 and GH levels were determined locally in each center by immunochemiluminescence, immunoradiometric assay, or electrochemiluminescence using different assays (IMMULITE 2000 (Siemens Healthineers, Erlangen, Germany); Liaison XL (DiaSorin, Saluggia, Italy), ImmuliteXP (Siemens Healthineers, Erlangen, Germany). The precision of these measurements was evaluated in accordance with a protocol based on CLSI EP-5A2, “Evaluation of Precision Performance of Quantitative Measurement Methods.”
Clinical data (e.g., weight, height, body mass index (BMI)) were collected from the patients’ electronic medical records. Biochemical data were extracted from the electronic databases available at each center, based on blood tests conducted throughout the follow-up period.
Data on biochemical parameters and treatment response were evaluated at short- and long-term follow-up visits, specifically at 3, 12, 24, and 36 months. The dates of the MRI scans prior to surgery or medical treatment and at 3-year follow-up were recorded. Patients were categorized according to their disease status at every visit into three categories:
NFPA: Pituitary adenomas without biochemical evidence of hormone hypersecretion. The diagnosis was based on radiological confirmation of a sellar mass by MRI and the absence of elevated serum levels of pituitary hormones, including prolactin, GH, adrenocorticotropic hormone, and thyroid-stimulating hormone. Patients with hyperprolactinemia attributable to stalk effect rather than lactotroph hypersecretion—typically with prolactin levels below 100 ng/mL 29 —were also classified as having NFPAs.
Controlled acromegaly: normalization of age- and sex-adjusted serum IGF-1 concentrations was achieved following surgery, with or without adjunctive medical therapy. Response assessment included strict normalization of IGF-1 concentrations within the full reference range (both upper and lower limits).
Uncontrolled acromegaly: patients without achieving IGF-1 normalization despite medical/surgical therapy.
MRI image analysis (TMT assessment)
TMT was evaluated using axial sections from T1-weighted pituitary MRI scans performed with a 1.5 T scanner as part of routine clinical practice, with two measurements obtained—one prior to treatment initiation and another after 3 years of follow-up. Measurements were taken perpendicular to the long axis of the temporal muscle using the diagnostic imaging viewer tool (Centricity™ Universal Viewer Zero Footprint (GE HealthCare, Chicago, IL, USA)) available at each center. Measurements were made at the level of the Sylvian fissure and the superior margin of the orbit, as previously described in the literature 30 (Figure 1). A second trained neuroradiologist, blinded to the clinical and biochemical data of the patients, validated all measurements to ensure unbiased assessment. The right and left temporal muscles were evaluated separately, and the average of both measurements was calculated to obtain the mean TMT.
Figure 1.
TMT was measured on axial images at the level of the orbital roof, perpendicular to the long axis of the muscle. The measurement was obtained bilaterally from the outer surface of the temporal bone to the outer margin of the muscle. The mean value of both sides was used for analysis.
TMT, temporal muscle thickness.
Statistical analysis
Data analysis included evaluation of outliers and assessment of normality using the Shapiro–Wilk test and normal probability plots. Continuous variables with a normal distribution are presented as mean and standard deviation (SD), while non-normally distributed variables are expressed as median and percentiles (p25–p75). Categorical variables are reported as absolute frequencies and percentages.
To compare two independent groups, the Student’s t test or Mann–Whitney U test was employed, depending on the data distribution. The Chi-squared test was used to compare categorical variables. Differences in baseline variables between groups with non-functioning adenomas and acromegaly were assessed, as well as differences in TMT between non-functioning adenomas, controlled acromegaly, and uncontrolled acromegaly, using the Kruskal–Wallis test. Mixed-effects regression models were used to assess the relationship between preoperative TMT and acromegaly control status over repeated follow-up assessments. As a sensitivity analysis, the IGF-1 %ULN ratio was used as the outcome variable. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the discriminatory performance of baseline TMT for predicting biochemical disease control at 36 months of follow-up. The optimal threshold was determined using Youden’s index. Internal validation was conducted using bootstrap resampling with 1000 replications to assess model stability and estimate optimism-corrected performance.
Statistical analyses were performed using STATA 18.0 BE-Basic Edition (College Station, TX, USA). Tables and figures were generated using Microsoft Excel version 365 (2023; Microsoft Corp., Redmond, WA, USA) and Stata version 18.0 BE-Basic. A p-value of <0.05 was considered statistically significant.
Results
Patient characteristics
After applying the exclusion criteria, 21 patients with acromegaly and 4 with NFPA were excluded due to the lack of available baseline imaging for TMT assessment. Consequently, data and images from 58 subjects were analyzed, including 40 patients with acromegaly and 18 with NFPA. The results are presented in Table 1. The median age was 56.1 years (47.1–66.3) in the NFPA group and 56.7 years (48.1–65.3) in the acromegaly group, with no significant differences between groups. The proportion of women was 55.6% in the NFPA group and 55% in the acromegaly group. No significant differences were observed in BMI or comorbidities between NFPA and acromegaly patients, except for sleep apnea syndrome, which was more prevalent in the acromegaly group (30% vs 5.6%, p = 0.038).
Table 1.
Baseline characteristics.
| Variable | Obs (n = 8) | NFPA (n = 18) | Acromegaly (n = 40) | p Value |
|---|---|---|---|---|
| Age (years) | 56.5 (47.9–65.8) | 56.1 (47.1–66.3) | 56.7 (48.1–65.3) | 0.822 |
| Sex (women) (%) | 32 (55.2) | 10 (55.6) | 22 (55) | 0.969 |
| Size (mm) | 13.6 (10–16.2) | 14 (10–15) | 13 (10–17) | 0.724 |
| Disease duration (years) | 2 (2.4–10.0) | 3.2 (2.4–19.3) | 6.4 (2.6–9.8) | 0.897 |
| IGF-1 (ng/mL) | 670 (529–793) | – | 670 (529–793) | – |
| ULN IGF-1 (%) | 309 ± 109 | – | 309 ± 109 | – |
| GH (ng/mL) | 4.5 (2.8–15) | – | 4.5 (2.8–15) | – |
| BMI (kg/m2) | 29.1 (25.2–32.1) | 31.3 (27.0–33.9) | 28.7 (25.2–31.2) | 0.268 |
| Diabetes mellitus (%) | 9 (15.5) | 2 (11.1) | 7 (17.5) | 0.562 |
| Hypertension (%) | 20 (34.5) | 6 (33.3) | 14 (35.0) | 0.965 |
| Cardiopathy (%) | 1 (2.0) | 1 (5.6) | 0 | 0.131 |
| Sleep apnea syndrome (%) | 13 (22.4) | 1 (5.6) | 12 (30.0) | 0.038 |
Data are expressed as number and percentage, median and p25–75 interquartile range or mean ± standard deviation. Size (mm): adenoma size.
BMI, body mass index; GH, growth hormone; IGF-1, insulin-like growth factor 1; NFPA, non-functioning pituitary adenoma.
TMT in acromegaly and controls
The mean TMT at the time of acromegaly diagnosis was 9.2 mm (7.6–10.9 mm), with higher values in patients with acromegaly (10.1 mm (9.3–10.7)) compared to patients with NFPA (8.1 mm (8.0–9.2), p = 0.003; Figure 2).
Figure 2.
Differences in TMT between controls and patients with acromegaly. The present violin plot shows a higher baseline TMT in patients with acromegaly compared to controls with non-functioning macroadenomas.
NFPA, non-functioning pituitary adenoma; TMT, temporal muscle thickness.
TMT also differed by sex in patients with acromegaly, with higher values observed in men compared with women (10.9 ± 2.3 vs 9.2 ± 2.1 mm, p = 0.018). By contrast, no significant sex-related differences in TMT were observed in the NFPA group (8.04 ± 2.34 vs 8.08 ± 1.62 mm, p = 0.964).
Relationship between TMT and IGF1 at baseline and during follow-up
Significant associations were observed between TMT and IGF-1 levels adjusted for age and sex at the diagnosis of acromegaly using a mixed-effects regression model. Baseline TMT was analyzed as an absolute measurement. Higher baseline TMT was associated with higher IGF-1 levels in absolute values (coefficient 19.59 ng/mL, 95% CI: 2.81–36.37 ng/mL, p = 0.022), and with IGF-1 %ULN (coefficient 0.13 ng/mL, 95% CI: 0.06–0.20 ng/mL, p < 0.001).
In addition, TMT influenced the longitudinal evolution of IGF-1 over time, with higher baseline TMT predicting a greater decrease in both IGF-1 levels (interaction coefficient −10.24 ng/mL, 95% CI: −12.09 to −8.39 ng/mL, p < 0.001) and IGF-1 %ULN (interaction coefficient −0.05 ng/mL, 95% CI: −0.06 to −0.04 ng/mL, p < 0.001).
TMT dynamics in patients with acromegaly
TMT was measured at 36 months in subjects with available MRI at that time (n = 27). In the overall analysis, without adjusting for disease control, a decrease in mean TMT from 9.6 to 8.8 mm was observed from baseline to 36 months (p = 0.001). Patients who remained uncontrolled at 3 years also tended to have higher TMT at that time. Mean TMT was 8.50 mm in the controlled group and 10.23 mm in the uncontrolled group (p = 0.090; Figure 3).
Figure 3.
TMT over time according to disease control in acromegaly. Mean TMT decreased significantly from baseline (prior to treatment) to 3-year follow-up in the overall cohort (p = 0.001). Patients with uncontrolled acromegaly consistently showed a trend to higher TMT values at both time points compared with those who achieved disease control (p = 0.09).
TMT, temporal muscle thickness expressed in mm.
Comparative analysis of baseline TMT in controlled versus uncontrolled acromegaly
When patients with acromegaly were stratified by controlled versus uncontrolled status at follow-up, a trend toward higher baseline TMT was observed in the uncontrolled group across all follow-up assessments. Using the criterion of age- and sex-adjusted IGF-1 within the normal range (<1.0 × ULN without values below the lower limit of normal), we explored the temporal relationship of baseline TMT according to disease status control. At 36 months of follow-up, 25 patients achieved biochemical disease control, and 9 remained uncontrolled. Among the controlled patients, 14 achieved control with surgery alone, whereas 11 required medical therapy. Of these 11 patients, 9 received a single pharmacological agent (7 lanreotide, 1 pasireotide, and 1 cabergoline), and 2 required more than 1 medication.
At each follow-up point, baseline TMT (measured prior to treatment initiation) was compared according to the patients’ hormonal control status. At 3 months, the mean baseline TMT was 10.05 mm in patients who remained uncontrolled and 9.45 mm in those who achieved disease control (p = 0.473). At 12 months, the mean baseline TMT was 10.14 and 9.81 mm, respectively (p = 0.680). At 24 months, the mean baseline TMT was 10.86 and 9.75 mm, respectively (p = 0.224). At 36 months, a significant difference was observed, with a mean baseline TMT of 11.38 mm in uncontrolled patients versus 9.25 mm in controlled patients (p = 0.012), suggesting that patients who did not reach biochemical control had greater baseline TMT values, whereas patients achieving hormonal control tended to present lower baseline TMT.
In a multivariable logistic regression model including age, sex, tumor size, and preoperative IGF-1 as covariates, baseline TMT (analyzed as an absolute measurement) was independently associated with lower odds of achieving biochemical control at follow-up (odds ratio (OR) 0.58, 95% confidence interval (CI): 0.34–0.99, p = 0.045). On the contrary, age, sex, tumor size, and preoperative IGF-1 were not significantly associated with disease control (Figure 4).
Figure 4.
A multivariable logistic regression model demonstrates that baseline TMT independently predicts the degree of control at 3 years of follow-up.
Sex was not included in the graph due to the wide range of its confidence interval, although it was not associated with the lack of control for acromegaly (OR = 0.19, 95% CI: 0.018–1.99, p = 0.167). Size: tumor size in mm.
CI, confidence interval; IGF-1, insulin-like growth factor 1; OR, odds ratio; TMT, temporal muscle thickness.
Discriminatory performance of baseline TMT for the prediction of disease control
To further evaluate the potential clinical utility of baseline TMT in predicting biochemical disease control at 36 months of follow-up, a ROC curve analysis was performed. Baseline TMT demonstrated good discriminatory performance for identifying patients who remained uncontrolled during follow-up, with an area under the curve (AUC) of 0.78 (Figure 5).
Figure 5.
ROC curve evaluating the TMT for predicting biochemical disease control during follow-up in patients with acromegaly.
AUC, area under the curve; ROC, receiver operating characteristic; TMT, temporal muscle thickness.
The optimal cut-off value determined using Youden’s index was 11.5 mm (Figure 6). At this threshold, baseline TMT had a sensitivity of 66.7% and a specificity of 92% for predicting the lack of biochemical disease control. The positive predictive value was 74.5%, and the negative predictive value was 88.7%.
Figure 6.
ROC curve analysis evaluating the discriminatory performance of baseline TMT for prediction of biochemical disease control at 36 months of follow-up, with optimal threshold selection based on Youden’s index (cut-off: 11.5 mm).
ROC, receiver operating characteristic; TMT, temporal muscle thickness.
To assess the robustness of the model and reduce potential overfitting, an internal validation using bootstrap resampling with 1000 replications was performed. The bootstrap-corrected AUC was 0.778, demonstrating consistent discriminatory performance and confirming the stability of the initial model estimates.
Discussion
In this study, we found that TMT was significantly greater in patients with acromegaly compared with those with NFPA matched by age, sex, and tumor size. Importantly, TMT correlated with serum IGF-1 levels and decreased following treatment, supporting its potential role as a non-invasive surrogate marker of disease activity and treatment response in acromegaly.
The use of imaging techniques to assess body composition has become increasingly common in clinical research due to their higher validity compared to traditional anthropometric methods and bioelectrical impedance analysis (BIA).31,32 These imaging modalities provide valuable insights into changes in body composition over time in various pathologies, leveraging imaging studies conducted during clinical follow-ups to evaluate patient prognosis.33,34 In this context, TMT assessed by intracranial MRI has been evaluated as it correlates with body composition measures obtained from BIA, dual-energy X-ray absorptiometry (DXA), and other imaging techniques.35–37 TMT has been specifically studied in intracranial tumor pathology16,17 and stroke, 38 where a reduction in TMT serves as a prognostic or surrogate marker in both conditions; thus, in patients with intracranial tumors, lower TMT has been associated with higher mortality, whereas in stroke patients, it has been linked to poorer functional outcomes and the presence of dysphagia.
Previous studies on patients with acromegaly have consistently shown increased muscle and lean body mass compared with healthy individuals, using various methods of body composition assessment.9,14 In line with these findings, Sahin et al. 20 demonstrated that patients with acromegaly also exhibited greater TMT than healthy controls—a result consistent with our observation of higher TMT in patients with acromegaly compared to those with NFPA.
IGF-1 can influence body composition, as has been demonstrated using different techniques. In this regard, a previous prospective study 15 that assessed patients with acromegaly by DXA showed that IGF-1 levels could affect body composition. Regarding the relation between IGF-1 and TMT, our findings are consistent with those of Gatto et al. 19 and Sahin et al. 20 who reported a positive association between TMT and IGF-1 levels, expressed as both %ULN and baseline IGF-1. Moreover, we also found that baseline TMT was associated with the longitudinal evolution of IGF-1 over the years, as patients with higher baseline TMT tended to show a greater decrease in IGF-1 levels during follow-up—an association not previously described. This decrease may be explained by the fact that subjects with higher TMT values initially have higher IGF-1 levels, reflecting greater disease activity; consequently, the subsequent reduction in IGF-1 during treatment was more pronounced in these patients.
Interestingly, previous studies8,12,13 demonstrated that acromegaly treatment can impact body composition, specifically showing a reduction in lean/muscle mass. This is consistent with the findings of our study, as we observed a global decrease in TMT in patients with acromegaly after 36 months of follow-up, parallel to the degree of hormonal control achieved. This has also been previously reported by Sahin et al., 20 who observed differences in TMT according to the treatment received. Furthermore, we found that baseline TMT was higher in patients who ultimately remained uncontrolled compared with those who achieved disease control. Notably, although the difference did not reach statistical significance, TMT at 36 months remained higher in uncontrolled patients compared with those who achieved disease control. This observation aligns with the first study evaluating TMT in pituitary disease, 39 conducted in patients with Cushing’s disease, which reported an association between muscle thickness and the degree of disease control. Specifically, a greater increase in TMT was observed in patients who achieved remission of hypercortisolism compared with those with persistent disease. Moreover, patients who achieved disease control with surgery alone exhibited a more pronounced increase in TMT than those who required adjunctive medical therapy. 39
In addition to the longitudinal analyses, we explored the potential clinical utility of baseline TMT for identifying patients at risk of persistent biochemical activity at 36 months using ROC curve analysis. Baseline TMT showed good discriminatory ability, with an AUC of 0.78 and a similar bootstrap-corrected AUC of 0.778, indicating stable model performance. The exploratory cut-off value of 11.5 mm demonstrated high specificity, suggesting that higher baseline TMT values may help identify patients at higher risk of persistent disease activity. From a practical standpoint, TMT should not be considered a replacement for established biochemical markers such as GH or IGF-1, which remain the cornerstone of disease assessment in acromegaly. However, as cranial MRI is routinely performed during diagnosis and follow-up, TMT could represent a complementary imaging-derived parameter that reflects structural and metabolic changes associated with disease activity and treatment response when interpreted alongside clinical and biochemical data. Nevertheless, these findings should be interpreted cautiously, as the cut-off was derived from an internal cohort and requires external validation before clinical implementation.
Limitations
Our study has some limitations. Due to the low prevalence of acromegaly, the sample size is inherently limited, despite the multicenter design, which may reduce statistical power in some analyses. The retrospective design may also introduce selection bias. In addition, follow-up MRI was not routinely performed in patients cured by surgery, which may have limited the availability of longitudinal TMT measurements and influenced follow-up analyses. However, baseline TMT data were available for the full cohort and represent the most robust component of our study. In addition, although we performed internal validation using bootstrap resampling, the identified cut-off values should be considered exploratory and require confirmation in prospective multicenter cohorts before being applied in clinical decision-making.
Conclusion
In conclusion, our study suggests that baseline TMT in patients with acromegaly is associated with disease activity and treatment response and may have potential as a non-invasive imaging biomarker for risk stratification. Patients with higher baseline TMT were more likely to remain biochemically uncontrolled at follow-up. Given the widespread availability of MRI during routine follow-up, TMT may represent a practical adjunctive parameter for longitudinal assessment; however, further prospective studies and external validation are required to establish clinically actionable thresholds.
Supplemental Material
Supplemental material, sj-docx-1-tae-10.1177_20420188261441382 for Evaluation of temporal muscle thickness in subjects with acromegaly: a follow-up study by Víctor Navas-Moreno, Marta Araujo-Castro, María Sara Tapia-Sanchiz, Fernando Sebastián-Valles, Miguel Antonio Sampedro-Núñez, Nuria Sánchez de la Blanca, Rebeca Martínez-Hernández, Víctor Rodríguez-Laval, Concepción Blanco, Betina Biagetti, Manel Puig-Domingo and Mónica Marazuela in Therapeutic Advances in Endocrinology and Metabolism
Acknowledgments
None.
Footnotes
ORCID iDs: Víctor Navas-Moreno 
https://orcid.org/0009-0001-8138-4178
Marta Araujo-Castro
https://orcid.org/0000-0002-0519-0072
María Sara Tapia-Sanchiz
https://orcid.org/0009-0009-6046-6105
Fernando Sebastián-Valles
https://orcid.org/0000-0002-4127-0483
Nuria Sánchez de la Blanca
https://orcid.org/0009-0004-2188-0032
Rebeca Martínez-Hernández
https://orcid.org/0000-0003-2479-1882
Víctor Rodríguez-Laval
https://orcid.org/0000-0002-4581-0993
Manel Puig-Domingo
https://orcid.org/0000-0002-6744-7195
Supplemental material: Supplemental material for this article is available online.
Contributor Information
Víctor Navas-Moreno, Department of Endocrinology and Nutrition, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria de La Princesa, Universidad Autónoma de Madrid, Madrid, Spain.
Marta Araujo-Castro, Department of Endocrinology and Nutrition, Hospital Universitario Ramón y Cajal, Madrid, Spain; Instituto de Investigación Biomédica Ramón y Cajal, Madrid, Spain.
María Sara Tapia-Sanchiz, Department of Endocrinology and Nutrition, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria de La Princesa, Universidad Autónoma de Madrid, Madrid, Spain.
Fernando Sebastián-Valles, Department of Endocrinology and Nutrition, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria de La Princesa, Universidad Autónoma de Madrid, Madrid, Spain.
Miguel Antonio Sampedro-Núñez, Department of Endocrinology and Nutrition, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria de La Princesa, Universidad Autónoma de Madrid, Madrid, Spain.
Nuria Sánchez de la Blanca, Department of Endocrinology and Nutrition, Hospital Universitario de la Princesa, Instituto de Investigación Sanitaria Princesa, Universidad Autónoma de Madrid, and Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER GCV14/ER/12), Madrid, Spain.
Rebeca Martínez-Hernández, Department of Endocrinology and Nutrition, Hospital Universitario de la Princesa, Instituto de Investigación Sanitaria Princesa, Universidad Autónoma de Madrid, and Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER GCV14/ER/12), Madrid, Spain.
Víctor Rodríguez-Laval, Department of Radiology, Hospital Universitario de la Princesa, Madrid, Spain.
Concepción Blanco, Department of Endocrinology and Nutrition, Príncipe de Asturias University Hospital, Madrid, Spain.
Betina Biagetti, Endocrinology and Nutrition Department, Hospital Universitario Vall de Hebrón, CIBERER U747 (ISCIII), ENDO-ERN, Barcelona, Spain.
Manel Puig-Domingo, Endocrinology and Nutrition Department, Hospital Universitario Germans Trias i Pujol, CIBERER U747 (ISCIII), Universitat Autònoma de Barcelona, Badalona, Spain.
Mónica Marazuela, Department of Endocrinology and Nutrition, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria de La Princesa, Universidad Autónoma de Madrid, Madrid, Spain.
Declarations
Ethics approval and consent to participate: The Research Ethics Committee of Hospital Universitario de La Princesa, Madrid, Spain (Study number: 5468) approved this study and waived the requirement for informed consent due to the retrospective nature of the study and the use of anonymized data. All procedures were performed in accordance with the ethical standards of the institutional research committee and with the Declaration of Helsinki.
Consent for publication: Not applicable.
Author contributions: Víctor Navas-Moreno: Conceptualization; Data curation; Formal analysis; Investigation; Project administration; Visualization; Writing – original draft.
Marta Araujo-Castro: Investigation; Resources; Supervision; Writing – review & editing.
María Sara Tapia-Sanchiz: Data curation; Investigation; Visualization; Writing – review & editing.
Fernando Sebastián-Valles: Conceptualization; Formal analysis; Writing – review & editing.
Miguel Antonio Sampedro-Núñez: Formal analysis; Methodology.
Nuria Sánchez de la Blanca: Writing – review & editing.
Rebeca Martínez-Hernández: Writing – review & editing.
Víctor Rodríguez-Laval: Methodology; Supervision.
Concepción Blanco: Resources; Supervision; Writing – review & editing.
Betina Biagetti: Supervision; Writing – review & editing.
Manel Puig-Domingo: Supervision; Writing – review & editing.
Mónica Marazuela: Conceptualization; Funding acquisition; Project administration; Resources; Supervision; Writing – original draft.
Funding: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was funded by Proyectos de Investigación en Salud PI19/00584, PI22/01404 and PMP22/00021 (Instituto de Salud Carlos III from Horizon Europe), iTIRONET-P2022/BMD7379 (Comunidad de Madrid), and co-financed by European Regional Development Fund (ERDF) funds to M.M.
All authors take responsibility for all aspects of the reliability and freedom from bias of the data presented and their discussed interpretation.
Availability of data and materials: The data for this study were systematically collected and organized into a comprehensive database. Access to the data can be granted upon request from the corresponding author.
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Supplementary Materials
Supplemental material, sj-docx-1-tae-10.1177_20420188261441382 for Evaluation of temporal muscle thickness in subjects with acromegaly: a follow-up study by Víctor Navas-Moreno, Marta Araujo-Castro, María Sara Tapia-Sanchiz, Fernando Sebastián-Valles, Miguel Antonio Sampedro-Núñez, Nuria Sánchez de la Blanca, Rebeca Martínez-Hernández, Víctor Rodríguez-Laval, Concepción Blanco, Betina Biagetti, Manel Puig-Domingo and Mónica Marazuela in Therapeutic Advances in Endocrinology and Metabolism