Analysis of Related Factors of Tumor Recurrence or Progression After Transnasal Sphenoidal Surgical Treatment of Large and Giant Pituitary Adenomas and Establish a Nomogram to Predict Tumor Prognosis

MRI based radiomics nomogram for predict recurrence of non functioning pituitary macroadenomas post surgery

OBJECTIVE

To establish and validate a comprehensive predictive model combining clinical data and radiomics features to improve the accuracy of predicting recurrence within five years after surgery in patients with non-functioning pituitary macroadenomas (NFMA).

METHODS

This retrospective study included 292 NFMA patients who underwent surgery between January 2012 and January 2018, with an additional 123 patients as an external test set. Clinical, pathological, and conventional imaging features were collected and analyzed using univariate and multivariate logistic regression to identify independent risk factors for postoperative recurrence. Radiomic features were extracted from preoperative T1-weighted (T1WI), T2-weighted (T2WI), and T1-enhanced images using 3D Slicer software. A radiomics prediction model was developed, and a combined model integrating clinical and radiomics features was established. The predictive performance of the models was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).

RESULTS

The clinical model (Cli-score), radiomics model (Rad-score) and combined model were developed. The diagnostic performance of the clinical model in the external test set, showed an AUC of 0.757 (95%CI: 0.671-0.830), with SEN, SPE, and ACC of 82.5%, 59.04%, and 71.54%, respectively. The diagnostic performance of the radiomics model in the external test set showed an AUC of 0.835 (95% CI: 0.757-0.896), with 80%, 79.52% and 63.41% for SEN, SPE and ACC%, respectively. The diagnostic performance of the combined model in the external test set showed an AUC of 0.863 (95% CI: 0.790-0.919), with SEN, SPE, and ACC of 80%, 81.93%, and 68.30%, respectively. The calibration curve indicated good predictive performance, and DCA confirmed the high clinical utility of the combined model.

CONCLUSION

The combined model provides a more accurate prediction of NFMA recurrence. This model can guide postoperative follow-up strategies and aid in early initiation of adjuvant therapy for high-risk patients.

Comparative analysis of the effects of microscopic vs. neuroendoscopic transsphenoidal surgery on visual and pituitary function and postoperative recurrence factors in patients with pituitary tumors

OBJECTIVE

To compare the effects of microscopic and neuroendoscopic transsphenoidal surgeries on visual function, pituitary function, and factors influencing postoperative recurrence in patients with pituitary tumors.

METHODS

A retrospective analysis was conducted on 164 patients with pituitary tumors who underwent surgery at The First People's Hospital of Xianyang from March 2020 to March 2022. Based on the surgical approach, patients were divided into an observation group (n=93) and a control group (n=71). The observation group underwent neuroendoscopic transsphenoidal pituitary tumor resection, while the control group underwent microscopic transsphenoidal pituitary tumor resection. General clinical data, perioperative indicators, hormone levels, quality of life, and olfactory function were compared between the two groups. Postoperative recurrence was recorded, and logistic regression analysis was performed to identify factors influencing postoperative recurrence in the patients.

RESULTS

The control group exhibited a greater amount of intraoperative bleeding and a longer postoperative hospital stay compared to the observation group (P<0.0001). The total tumor resection rate was significantly lower in the control group than that in the observation group (P=0.002). Additionally, the numbers of patients in the control group who experienced improvements in vision (P=0.013), headache (P=0.004), and sexual dysfunction (P=0.047) were lower than those in the observation group. One month after surgery, levels of prolactin, human growth hormone, adrenocorticotropic hormone, and thyroid-stimulating hormone were higher in the observation group than those in the control group. The quality of life score one month after surgery was higher in the observation group than that in the control group (P<0.0001). In addition, the olfactory function score one month after surgery was lower in the observation group compared to the control group (P<0.0001). The overall incidence of postoperative complications was higher in the control group (P=0.034). There was no statistically significant difference in recurrence rates between the two groups (P=0.102). Multivariate logistic regression analysis identified tumor size (P=0.001, OR=7.227), Knosp classification (P=0.005, OR=0.238), and Ki-67 index (P=0.001, OR=4.969) as independent risk factors for recurrence within two years in patients with pituitary tumors.

CONCLUSION

For patients with pituitary tumors, neuroendoscopic transsphenoidal surgery is more effective than microscopic transsphenoidal surgery in reducing operative time and improving postoperative visual and pituitary function, and therefore, should be promoted in clinical practice.

Concomitant Prediction of the Ki67 and PIT-1 Expression in Pituitary Adenoma Using Different Radiomics Models

OBJECTIVES

To preoperatively predict the high expression of Ki67 and positive pituitary transcription factor 1 (PIT-1) simultaneously in pituitary adenoma (PA) using three different radiomics models.

METHODS

A total of 247 patients with PA (training set: n = 198; test set: n = 49) were included in this retrospective study. The imaging features were extracted from preoperative contrast-enhanced T1WI (T1CE), T1-weighted imaging (T1WI), and T2-weighted imaging (T2WI). Feature selection was performed using Spearman's rank correlation coefficient and least absolute shrinkage and selection operator (LASSO). The classic machine learning (CML), deep learning (DL), and deep learning radiomics (DLR) models were constructed using logistic regression (LR), support vector machine (SVM), and multi-layer perceptron (MLP) algorithms. The area under the receiver operating characteristic (ROC) curve (AUC), sensitivity, specificity, accuracy, negative predictive value (NPV) and positive predictive value (PPV) were calculated for the training and test sets. In addition, combined with clinical characteristics, the best CML and the best DL models (SVM classifier), the DL radiomics nomogram (DLRN) was constructed to aid clinical decision-making.

RESULTS

Seven CML features, 96 DL features, and 107 DLR features were selected to construct CML, DL and DLR models. Compared to CML and DL model, the DLR model had the best performance. The AUC, sensitivity, specificity, accuracy, NPV and PPV were 0.827, 0.792, 0.800, 0.796, 0.800 and 0.792 in the test set, respectively.

CONCLUSIONS

Compared with CML and DL models, the DLR model shows the best performance in predicting the Ki67 and PIT-1 expression in PAs simultaneously.

DNA Methylation in Pituitary Adenomas: A Scoping Review

Pituitary adenomas are a diverse group of neoplasms with variable clinical behavior. Despite advances in genetic analysis, understanding the role of epigenetic modifications, particularly DNA methylation, remains an area under investigation. This scoping review aimed to update and synthesize the current body of literature on DNA methylation in pituitary adenomas, focusing on methodological advancements and clinical correlations. A systematic search conducted across multiple databases, including Embase, Scopus, MEDLINE, and CENTRAL, identified 107 eligible studies. Early methods, such as methylation-restricted digestion and methylation-specific PCR (MSP), have evolved into more comprehensive approaches, such as chip-based DNA methylation analysis. Key findings suggest that genes like POMC, SOCS-1, and RASSF1A show a significant association between methylation and clinical behavior. However, methylation patterns alone are insufficient to fully explain tumorigenesis. Emerging data suggest that DNA methylation might serve as a prognostic marker for invasive growth and recurrence, but further longitudinal studies are needed. This review highlights the need for future research to explore the methylome more thoroughly and to better define the clinical impact of epigenetic modifications in pituitary adenomas.

Pathological characteristics of reoperated regrowing clinically nonfunctioning pituitary tumor cases in comparison with initial surgical cases

Objective

Postoperative nonfunctioning pituitary tumor (NFPT) regrowth is a significant concern, but its predictive factors are not well established. This study aimed to elucidate the pathological characteristics of NFPTs indicated for reoperation for tumor regrowth.

Methods

Pathological, radiological, and clinical data were collected from patients who underwent repeat operation for NFPT at Moriyama Memorial Hospital (MMH) between April 2018 and September 2023. For comparison, we also gathered data from patients who underwent initial surgery for NFPT during the same period at MMH.

Results

Overall, 61 and 244 NFPT patients who respectively underwent reoperation and initial operation were evaluated. The mean period between the previous operation and reoperation was 113 months. Immunonegativity for any adenohypophyseal hormone was significantly more frequent in the reoperation group than in the initial operation group. In addition, the rate of hormone-negative but transcription factor-positive (H-/TF+) tumors among silent gonadotroph tumors was significantly higher in the reoperation group than in the initial operation group. Furthermore, seven silent corticotroph tumors (SCTs) in the reoperation group were ACTH-negative but TPIT-positive. Because most of the previous surgeries were performed in other hospitals a long time ago, we could procure the previous pathological results with immunohistochemistry (IHC) only from 21 patients. IHC for TF had not been performed in all the previous specimens. IHC for adenohypophyseal hormone was almost the same as the current results, and many H-/TF+ tumors were previously diagnosed as NCT. In addition, the reoperated patients were classified into 3 groups on the basis of the condition of the previous operation: gross total resection (GTR), 12 patients; subtotal resection (STR), 17 patients; and partial resection (PR), 32 patients. The mean Ki-67 LI in the GTR, STR, and PR subgroups were 1.82, 1.37, and 0.84, respectively, with the value being significantly higher in the GTR subgroup than in the PR subgroup (P < 0.05).

Conclusions

The ratio of H-/TF+ tumors is significantly higher in symptomatically regrown tumors than in the initial cases, which used to be diagnosed as NCT. PR cases tend to grow symptomatically in a shorter period, even with lower Ki-67 LI than GTR cases.

Intraoperative cerebrospinal fluid leakage and residual tumors in endoscopic transsphenoidal surgery for pituitary adenoma: risk analysis and nomogram development

BACKGROUND

Endoscopic transsphenoidal surgery is the primary method used to treat pituitary adenomas (PAs) at present; however, this technique is associated with certain risks, including cerebrospinal fluid leakage (CFL) and residual tumors (RTs). In this study, we aimed to identify specific risk factors for intraoperative CFL (ioCFL) and postoperative RT in patients with pituitary adenoma and construct a corresponding nomogram for risk assessment.

METHODS

We collected a range of information from 782 patients who underwent endoscopic transsphenoidal PA resection in the Department of Neurosurgery at Beijing Tiantan Hospital between 2019 and 2021. Patients were then randomly assigned to training and validation groups (in a 8:2 ratio) with R software. Univariate and multivariable logistic regression models were then used to screen variables related to ioCFL and RT. These variables were then used to construct a predictive nomogram. Finally, the accuracy of the nomogram was validated by receiver operating characteristic curve (ROC) analysis, calibration plots, and decision curve analysis (DCA).

RESULTS

Univariate and multivariable logistic regression models identified four risk factors for ioCFL (Hardy grade, tumor size, position, and consistency) and five risk factors for RT (operation time, tumor size, consistency, Knosp grade, and primary/recurrence type). The area under the ROC curve (AUC) for the ioCFL risk model was 0.666 and 0.697 for the training and validation groups, respectively. For RT, the AUCs for the two groups were 0.788 and 0.754, respectively. The calibration plots for the ioCFL and RT models showed high calibration quality and DCA analysis yielded excellent efficiency with regards to clinical decision making.

CONCLUSION

Tumor size, growth characteristics, and invasion location were identified as the main factors affecting intraoperative CFL and RT. With our novel nomogram, surgeons can identify high-risk patients according to preoperative and intraoperative tumor performance and reduce the probability of complications.

The Value of ER∝ in the Prognosis of GH- and PRL-Secreting PitNETs: Clinicopathological Correlations

Pituitary neuroendocrine tumors (PitNETs) are divided into multiple histological subtypes, which determine their clinical and biological variable behavior. Despite their benign evolution, in some cases, prolactin (PRL) and growth hormone (GH)-secreting PitNETs may have aggressive behavior. In this study, we investigated the potential predictive role of ER∝, alongside the clinicopathological classification of PitNETs (tumor diameter, tumor type, and tumor grade). A retrospective study was conducted with 32 consecutive cases of PRL- and mixed GH- and PRL-secreting PitNETs (5 patients with prolactinomas and 27 with acromegaly, among them, 7 patients with GH- and PRL- co-secretion) who underwent transsphenoidal intervention. Tumor specimens were histologically and immunohistochemical examined: anterior pituitary hormones, ki-67 labeling index, CAM 5.2, and ER∝; ER∝ expression was correlated with basal PRL levels at diagnosis (rho = 0.60, p < 0.01) and postoperative PRL levels (rho = 0.58, p < 0.001). In our study, the ER∝ intensity score was lower in female patients. Postoperative maximal tumor diameter correlated with Knosp grade (p = 0.02); CAM 5.2 pattern (densely/sparsely granulated/mixed densely and sparsely granulated) was correlated with postoperative PRL level (p = 0.002), and with ki-67 (p < 0.001). The IGF1 level at diagnosis was correlated with the postoperative GH nadir value in the oral glucose tolerance test (OGTT) (rho = 0.52, p < 0.05). Also, basal PRL level at diagnosis was correlated with postoperative tumor diameter (p = 0.63, p < 0.001). At univariate logistic regression, GH nadir in OGTT test at diagnostic, IGF1, gender, and invasion were independent predictors of remission for mixed GH- and PRL-secreting Pit-NETs; ER∝ can be used as a prognostic marker and loss of ER∝ expression should be considered a sign of lower differentiation and a likely indicator of poor prognosis. A sex-related difference can be considered in the evolution and prognosis of these tumors, but further studies are needed to confirm this hypothesis.

Prognostic Models in Growth-Hormone- and Prolactin-Secreting Pituitary Neuroendocrine Tumors: A Systematic Review

Growth-hormone (GH)- and prolactin (PRL)-secreting PitNETs (pituitary neuroendocrine tumors) are divided into multiple histological subtypes, which determine their clinical and biological variable behavior. Proliferation markers alone have a questionable degree of prediction, so we try to identify validated prognostic models as accurately as possible. (1) Background: The data available so far show that the use of staging and clinical-pathological classification of PitNETs, along with imaging, are useful in predicting the evolution of these tumors. So far, there is no consensus for certain markers that could predict tumor evolution. The application of the WHO (World Health Organisation) classification in practice needs to be further evaluated and validated. (2) Methods: We performed the CRD42023401959 protocol in Prospero with a systematic literature search in PubMed and Web of Science databases and included original full-text articles (randomized control trials and clinical trials) from the last 10 years, published in English, and the search used the following keywords: (i) pituitary adenoma AND (prognosis OR outcome OR prediction), (ii) growth hormone pituitary adenoma AND (prognosis OR outcome OR prediction), (iii) prolactin pituitary adenoma AND (prognosis OR outcome OR prediction); (iv) mammosomatotroph adenoma AND (prognosis OR outcome OR prediction). (3) Results: Two researchers extracted the articles of interest and if any disagreements occurred in the selection process, these were settled by a third reviewer. The articles were then assessed using the ROBIS bias assessment and 75 articles were included. (4) Conclusions: the clinical-pathological classification along with factors such as GH, IGF-1, prolactin levels both preoperatively and postoperatively offer valuable information.

Analysis of neuroendoscopy for the treatment of macroadenomas and giant pituitary adenomas

Objective

This study investigated the use and effectiveness of endoscopic transnasal, transsphenoidal surgery, a minimally invasive method for the treatment of macroadenomas and giant pituitary a denomas, in a medical setting. The surgical results of 429 patients who received neuroendoscopic treatment of macroadenomas or giant pituitary adenomas were evaluated, and the experiences and lessons learned from treatment complications were assessed.

Patients and methods

From January 2012 to December 2021, 429 patients with macroadenomas or giant pituitary adenomas, including 60 patients with giant adenomas (diameter ≥4 cm) and 369 patients with macroadenomas (diameter 1–4 cm), received a 3D head CT, a MRI with contrast enhancement, and an endocrinology examination prior to surgery. Preoperative clinical and radiological features, visual measurements, hormone levels, length of stay, length of surgery, postoperative stay, visual and hormone outcomes, resection range, complication and recurrence rates, and routine patient information were recorded. The patients were followed up for 6–72 months (median = 40 months).

Results

Of 429 patients with macroadenomas or giant pituitary adenomas who received neuroendoscopic treatment, 348 (81.12%) had gross-total resections (GTR), 53 (12.35%) had near-total resections (NTR), and 28 (6.53%) had subtotal resections. There were 138 cases of post-operative diabetes insipidus (32.17%), including 7 cases of permanent diabetes insipidus (1.63%), 16 cases of nasal hemorrhage (3.73%), 39 cases of intraoperative cerebrospinal fluid leakage (9.09%), 4 cases of intracranial infection (0.9%), 16 cases of hypophysis (3.7%), and 15 cases of anosmia (3.50%). The clinical symptoms and endocrinology indices of the patients improved after surgery, and all patients were discharged 5–18 days (8.36 ± 2.65) postop.

Conclusion

Neuroendoscopy is a safe operation with a short recovery period and hospital stay and is thus an effective method to treat macroadenomas and giant pituitary adenomas. Preoperative evaluation and prediction can help to accurately address possible intraoperative situations and improve GTR.

Development and Validation of a Prognostic Model for Post-Operative Recurrence of Pituitary Adenomas

Background

We aimed to assess clinical factors associated with tumor recurrence and build a nomogram based on identified risk factors to predict postoperative recurrence in patients with pituitary adenomas (PAs) who underwent gross-total resection (GTR).

Methods

A total of 829 patients with PAs who achieved GTR at Tongji Hospital between January 2013 and December 2018 were included in this retrospective study. The median follow-up time was 66.7 months (range: 15.6-106.3 months). Patients were randomly divided into training (n = 553) or validation (n = 276) cohorts. A range of clinical characteristics, radiological findings, and laboratory data were collected. Uni- and multivariate Cox regression analyses were applied to determine the potential risk factors for PA recurrence. A nomogram model was built from the identified factors to predict recurrence. Concordance index (C-index), calibration curve, and receiver operating characteristic (ROC) were used to determine the predictive accuracy of the nomogram. Decision curve analysis (DCA) was performed to evaluate the clinical efficacy of the nomogram.

Results

Pseudocapsule-based extracapsular resection (ER), cavernous sinus invasion (CSI), and tumor size were included in the nomogram. C-indices of the nomogram were 0.776 (95% confidence interval [CI]: 0.747-0.806) and 0.714 (95% CI: 0.681-0.747) for the training and validation cohorts, respectively. The area under the curve (AUC) of the nomogram was 0.770, 0.774, and 0.818 for 4-, 6-, 8-year progression-free survival (PFS) probabilities in the training cohort, respectively, and 0.739, 0.715 and 0.740 for 4-, 6-, 8-year PFS probabilities in the validation cohort, respectively. Calibration curves were well-fitted in both training and validation cohorts. DCA revealed that the nomogram model improved the prediction of PFS in both cohorts.

Conclusions

Pseudocapsule-based ER, CSI, and tumor size were identified as independent predictors of PA recurrence. In the present study, we developed a novel and valid nomogram with potential utility as a tool for predicting postoperative PA recurrence. The use of the nonogram model can facilitate the tailoring of counseling to meet the individual needs of patients.

Prognostic Factors for Recurrence in Pituitary Adenomas: Recent Progress and Future Directions

Pituitary adenomas (PAs) are benign lesions; nonetheless, some PAs exhibit aggressive behaviors, which lead to recurrence. The impact of pituitary dysfunction, invasion-related risks, and other complications considerably affect the quality of life of patients with recurrent PAs. Reliable prognostic factors are needed for recurrent PAs but require confirmation. This review summarizes research progress on two aspects—namely, the clinical and biological factors (biomarkers) for recurrent PAs. Postoperative residue, age, immunohistological subtypes, invasion, tumor size, hormone levels, and postoperative radiotherapy can predict the risk of recurrence in patients with PAs. Additionally, biomarkers such as Ki-67, p53, cadherin, pituitary tumor transforming gene, matrix metalloproteinase-9, epidermal growth factor receptor, fascin actin-bundling protein 1, cyclooxygenase-2, and some miRNAs and lncRNAs may be utilized as valuable tools for predicting PA recurrence. As no single marker can independently predict PA recurrence, we introduce an array of comprehensive models and grading methods, including multiple prognostic factors, to predict the prognosis of PAs, which have shown good effectiveness and would be beneficial for predicting PA recurrence.

Transsphenoidal Surgery of Giant Pituitary Adenoma: Results and Experience of 239 Cases in A Single Center

BACKGROUND

Transsphenoidal surgery (TSS) is first-line treatment for giant pituitary adenomas (PAs). Although PA is a benign neuroendocrine tumor that originates from adenohypophysial cells, the surgical outcomes and prognosis of giant PAs differ significantly due to multiple factors such as tumor morphology, invasion site, pathological characteristics and so on. The aim of this study was to evaluate surgical outcomes of giant PAs in a single-center cohort.

METHODS

The clinical features and outcomes of 239 patients with giant PA who underwent sphenoidal surgery at the Second Affiliated Hospital of Zhejiang University School of Medicine from January 2015 to October 2021 were collected from medical records. The basic clinical information (age, gender, function etc.), surgical procedure, imaging features (maximum diameter, invasion characteristics, tumor shape etc.) and histopathological characteristics (pathological results, Ki-67, P53 etc.) were retrospectively reviewed. SPSS 25.0 and Stata 12.0 software were used for statistical analysis.

RESULTS

A total of 239 patients with giant PAs underwent TSS, of which 168 surgeries (70.29%) were endoscopic endonasal transsphenoidal (EETS) and 71 (29.71%) were microscopic transsphenoidal (MTS). The mean preoperative maximum diameter in the cohort was 45.64 mm. Gross-total resection was achieved in 46 patients (19.25%), near-total in 56 (23.43%), subtotal in 68 (28.45%), and partial in 69 (28.87%) patients. The maximum tumor diameter and Knosp grade were the significant factors that limited the extent of the resection of giant PAs. A total of 193 patients (80.75%) experienced surgical complications, and the most common complications were postoperative diabetes insipidus (DI) (91, 38.08%), intracranial infection (36, 15.06%) and cerebrospinal fluid (CSF) leaks (37, 15.48%). In addition, there was a significant difference in the incidence of CSF leaks between the neuroendoscopy group and the microscopic group (P < 0.05).

CONCLUSION

The management of giant PAs remains a therapeutic challenge due to their large size and postoperative complications. The maximum diameter and Knosp grade of giant PAs significantly limited the extent of resection, which warrants a reasonable surgical plan.