Long term follow-up of growth hormone-secreting pituitary adenomas submitted to endoscopic endonasal surgery

Leopoldo, Caroline Martins dos Santos; Leopoldo, Felippe Martins dos Santos; Santos, Américo Rubens Leite dos; Veiga, José Carlos Esteves; Lima, Jose Viana; Scalissi, Nilza Maria; Lazarini, Paulo Roberto; Dolci, Ricardo Landini Lutaif

doi:10.1590/0004-282x20170035

Cited by 13 publications

(9 citation statements)

References 26 publications

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“…Na via transesfenoidal o modo de acesso à sela túrcica pode ser microscópico ou endoscópico. A cirurgia transesfenoidal endoscópica endonasal é a mais indicada na otorrinolaringologia e neurocirurgia e, assim como toda cirurgia, também pode ocasionar algumas potenciais complicações, a exemplo de fístulas liquóricas, lesões das artérias carótidas, hemorragias intracranianas, diabetes insipidus, hipopituitarismo, etc (Leopoldo, 2017).…”

Section: Introductionunclassified

Complicações pós-operatórias no tratamento cirúrgico da Acromegalia: uma revisão de literatura da última década

Borges

Cardoso

et al. 2021

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Introdução: A acromegalia é uma síndrome manifestada pela hipersecreção de GH e do IGF-1, que possui consequências sobre o fechamento de cartilagens, alterações metabólicas, como a intolerância à glicose e alterações cardiovasculares a exemplo da hipertensão arterial. Na maioria dos casos, essa síndrome está ligada a somatotropinomas na Glândula Mestra e possui diagnóstico difícil, por ter início insidioso, geralmente notado após 5 anos do seu início. Tal condição afeta a qualidade e a duração média da vida de quem a possui. O diagnóstico laboratorial pode ser feito através da dosagem de GH e IGF-1 basais. Quanto à conduta, a terapia de primeira escolha é cirúrgica, porém, como todo procedimento, apresenta complicações. Assim, objetiva-se um melhor tratamento e conduta diferenciada, por meio do esclarecimento dessa conjuntura no que tange o período pós-operatório. Metodologia: Foi realizada uma revisão de literatura na BVS, com a utilização dos descritores: “Acromegaly” AND “Postoperative Complications” de 2011 a 2021, sendo 16 artigos selecionados. Resultados e discussão: Dentre os achados, observa-se que a abordagem transesfenoidal endoscópica apresenta-se mais vantajosa em relação às demais. Além disso, as complicações pós operatórias foram classificadas em quatro categorias: Complicações ligadas ao procedimento cirúrgico, como infecções e hemorragias; complicações isquêmicas; complicações hormonais, como diabetes insipidus e complicações ligadas ao tumor de GH, como a Apneia obstrutiva do sono. Conclusão: É necessário um melhor manejo do paciente com acromegalia após a cirurgia, por esta possuir a particularidade relacionada aos distúrbios do sono, para que assim a conduta seja individualizada e aperfeiçoada.

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Section: Introductionunclassified

Complicações pós-operatórias no tratamento cirúrgico da Acromegalia: uma revisão de literatura da última década

Borges

Cardoso

et al. 2021

RSD

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“…Acromegaly is a rare chronic disease caused by pituitary somatotroph adenoma that causes high growth hormone (GH)/insulin-like growth factor 1 (IGF1) levels and reduced life expectancy (1, 2). The aim of treatment is to normalize the level of IGF1, which usually reflects appropriate disease control, reduces the risk of complications, and reduces mortality (3–5).…”

Section: Introductionmentioning

confidence: 99%

Machine Learning-Based Radiomics Predicts Radiotherapeutic Response in Patients With Acromegaly

et al. 2019

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Background: Prediction of radiotherapeutic response before radiotherapy could help determine individual treatment strategies for patients with acromegaly. Objective: To develop and validate a machine-learning-based multiparametric MRI radiomics model to non-invasively predict radiotherapeutic response in patients with acromegaly. Methods: This retrospective study included 57 acromegaly patients who underwent postoperative radiotherapy between January 2008 and January 2016. Manual lesion segmentation and radiomics analysis were performed on each pituitary adenoma, and 1561 radiomics features were extracted from each sequence. A radiomics signature was built with a support vector machine using leave-one-out cross-validation for feature selection. Multivariable logistic regression analysis was used to select appropriate clinicopathological features to construct a clinical model, which was then combined with the radiomics signature to construct a radiomics model. The performance of this radiomic model was assessed using receiver operating characteristics (ROC) analysis and its calibration, discriminating ability, clinical usefulness. Results: At 3-years after radiotherapy, 25 patients had achieved remission and 32 patients had not. The clinical model incorporating seven clinical features had an area under the ROC (AUC) of 0.86 for predicting radiotherapeutic response, and performed better than any single clinical feature. The radiomics signature constructed with six radiomics features had a significantly higher AUC of 0.92. The radiomics model showed good discrimination abilities and calibration, with an AUC of 0.96. Decision curve analysis confirmed the clinical utility of the radiomics model. Conclusion: Using pre-radiotherapy clinical and MRI data, we developed a radiomics model with favorable performance for individualized non-invasive prediction of radiotherapeutic response, which may help in identifying acromegaly patients who are likely to benefit from radiotherapy.

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“…Acromegaly [overproduction of growth hormone (GH) by the PA in adult patients] is associated with numerous complications (4). Typically, the increased GH level will induce cardiovascular and cerebrovascular diseases, and acromegaly will increase the mortality by ≥2-fold compared with that among normal individuals (5, 6).…”

Section: Introductionmentioning

confidence: 99%

Preoperative Noninvasive Radiomics Approach Predicts Tumor Consistency in Patients With Acromegaly: Development and Multicenter Prospective Validation

et al. 2019

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Background: Prediction of tumor consistency before surgery is of vital importance to determine individualized therapeutic schemes for patients with acromegaly. The present study was performed to noninvasively predict tumor consistency based on magnetic resonance imaging and radiomics analysis. Methods: In total, 158 patients with acromegaly were randomized into the primary cohort ( n = 100) and validation cohort ( n = 58). The consistency of the tumor was classified as soft or firm according to the neurosurgeon's evaluation. The critical radiomics features were determined using the elastic net feature selection algorithm, and the radiomics signature was constructed. The most valuable clinical characteristics were then selected based on the multivariable logistic regression analysis. Next, a radiomics model was developed using the radiomics signature and clinical characteristics, and 30 patients with acromegaly were recruited for multicenter validation of the radiomics model. The model's performance was evaluated based on the receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), accuracy, and other associated classification measures. Its calibration, discriminating capacity, and clinical usefulness were also evaluated. Results: The radiomics signature established according to four radiomics features screened in the primary cohort exhibited excellent discriminatory capacity in the validation cohort. The radiomics model, which incorporated both the radiomics signature and Knosp grade, displayed favorable discriminatory capacity and calibration, and the AUC was 0.83 (95% confidence interval, 0.81–0.85) and 0.81 (95% confidence interval, 0.78–0.83) in the primary and validation cohorts, respectively. Furthermore, compared with the clinical characteristics, the as-constructed radiomics model is more effective in prediction of the tumor consistency in patients with acromegaly. Moreover, the multicenter validation and decision curve analysis suggested that the radiomics model was clinically useful. Conclusions: This radiomics model can assist neurosurgeons in predicting tumor consistency in patients with acromegaly before surgery and facilitates the determination of individualized therapeutic schemes.

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Long term follow-up of growth hormone-secreting pituitary adenomas submitted to endoscopic endonasal surgery

Cited by 13 publications

References 26 publications

Complicações pós-operatórias no tratamento cirúrgico da Acromegalia: uma revisão de literatura da última década

Complicações pós-operatórias no tratamento cirúrgico da Acromegalia: uma revisão de literatura da última década

Machine Learning-Based Radiomics Predicts Radiotherapeutic Response in Patients With Acromegaly

Preoperative Noninvasive Radiomics Approach Predicts Tumor Consistency in Patients With Acromegaly: Development and Multicenter Prospective Validation

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