Prediction of Consistency of Pituitary Adenomas by Magnetic Resonance Imaging

The role of preoperative MRI in endoscopic transnasal transsphenoidal hypophysectomy of pituitary adenoma

BACKGROUND

The trans-sphenoidal approach, commonly used for removing pituitary adenomas, has become a widely accepted and successful method. In recent years, the endoscopic trans-sphenoidal technique has emerged as a minimally invasive surgical approach for pituitary adenoma removal. The majority of pituitary adenomas exhibit a soft consistency and can be successfully extracted with aspiration and curettage using the trans-sphenoidal approach. However, a subset of around 5-15% of these adenomas possess a solid and fibrous texture. The occurrence of firm and fibrous adenomas is relatively common; unfortunately, there are no reliable predictors to identify them preoperatively.

OBJECTIVES

The ability to forecast the reliability of magnetic resonance imaging (MRI) holds promise for improving prior preparation and impacts the extent of resection.

DESIGN

A cross-sectional analysis of the investigation of magnetic resonance imaging (MRI) in relation to cancer histology was performed on 68 patients who had endoscopic trans-nasal excision for nonfunctional adenomas.

MATERIALS AND METHODS

The determination of an intensity ratio was performed by employing quantitative estimates of MRI signal intensity obtained from both the adenoma and pons. During the surgical procedure, a series of sequential-graded procedures were used for the removal of tumours with varying consistencies. Softer tumours were addressed using the Suction technique (R1), while tumours of intermediate consistency were treated using curettes (R2). In order to evaluate the fibrotic content of firmer tumours, the utilization of Cavitron Ultrasound Surgical Aspirator (CUSA), and/or other micro-instruments (R3) was employed, with the histologic collagen fraction being quantified. In order to investigate and analyse the data, a statistical analysis was conducted. A predictive relationship between resection category and both intensity ratio, and collagen percentage was noted. The primary objective of this study was to determine the appropriate cutoff criteria for clinical utilization, as well as to investigate the association between intensity ratios and collagen percentage.

RESULTS

Tumors with ratios ≤ 1.6 on the T2-weighted image and collagen content > 5.3% required more meticulous and sharp dissection for resection.

CONCLUSIONS

The utilization of MRI analysis may offer some assistance, but not conclusive, in the prediction of tumour consistency.

Diffusion-weighted imaging does not seem to be a predictor of consistency in pituitary adenomas

PURPOSE

To prospectively evaluate the usefulness of T1-weighted imaging (T1WI) and diffusion-weighted imaging (DWI) sequences in predicting the consistency of macroadenomas. In addition, to determine their values ​​as prognostic factors of surgical outcomes.

METHODS

Patients with pituitary macroadenoma and surgical indication were included. All patients underwent pre-surgical magnetic resonance imaging (MRI) that included the sequences T1WI before and after contrast administration and DWI with the apparent diffusion coefficient (ADC) map. Post-surgical MRI was performed at least 3 months after surgery. The consistency of the macroadenomas was evaluated at surgery, and they were grouped into soft and intermediate/hard adenomas. Mean ADC values, signal on T1WI and the ratio of tumor ADC values ​​to pons (ADCR) were compared with tumor consistency and grade of surgical resection.

RESULTS

A total of 80 patients were included. A softened consistency was found at surgery in 53 patients and hardened in 27 patients. The median ADC in the soft consistency group was 0.532 × 10-3 mm2/sec (0.306 - 1.096 × 10-3 mm2/sec), and in the intermediate/hard consistency group was 0.509 × 10-3 mm2/sec (0.308 - 0.818 × 10-3 mm2/sec). There was no significant difference between the median values ​​of ADC, ADCR and signal on T1W between the soft and hard tumor groups, or between patients with and without tumor residue.

CONCLUSION

Our results did not show usefulness of the DWI and T1WI for assessing the consistency of pituitary macroadenomas, nor as a predictor of the degree of surgical resection.

Radiomic Analysis in Pituitary Tumors: Current Knowledge and Future Perspectives

Radiomic analysis has emerged as a valuable tool for extracting quantitative features from medical imaging data, providing in-depth insights into various contexts and diseases. By employing methods derived from advanced computational techniques, radiomics quantifies textural information through the evaluation of the spatial distribution of signal intensities and inter-voxel relationships. In recent years, these techniques have gained considerable attention also in the field of pituitary tumors, with promising results. Indeed, the extraction of radiomic features from pituitary magnetic resonance imaging (MRI) images has been shown to provide useful information on various relevant aspects of these diseases. Some of the key topics that have been explored in the existing literature include the association of radiomic parameters with histopathological and clinical data and their correlation with tumor invasiveness and aggressive behavior. Their prognostic value has also been evaluated, assessing their role in the prediction of post-surgical recurrence, response to medical treatments, and long-term outcomes. This review provides a comprehensive overview of the current knowledge and application of radiomics in pituitary tumors. It also examines the current limitations and future directions of radiomic analysis, highlighting the major challenges that need to be addressed before a consistent integration of these techniques into routine clinical practice.

Radiomic analysis of preoperative magnetic resonance imaging for the prediction of pituitary adenoma consistency

BACKGROUND

The consistency of pituitary adenomas affects the course of surgical treatment.

PURPOSE

To evaluate the diagnostic capabilities of radiomics based on T1-weighted (T1W) and T2-weighted (T2W) magnetic resonance imaging (MRI) in conjunction with two machine-learning (ML) techniques (support vector machine [SVM] and random forest classifier [RFC]) for assessing the consistency of pituitary adenomas.

MATERIAL AND METHODS

The institutional database was retrospectively scanned for patients who underwent surgical excision of pituitary adenomas. Surgical notes were accepted as a reference for the adenoma consistency. Radiomics analysis was performed on preoperative coronal 3.0T T1W and T2W images. First- and second-order parameters were calculated. Inter-observer reproducibility was assessed with Spearman's Correlation (ρ) and intra-observer reproducibility was evaluated with the intraclass correlation coefficient (ICC). Least absolute shrinkage and selection operator (LASSO) was used for dimensionality reduction. SVM and RFC were used as ML methods.

RESULTS

A total of 52 patients who produced 206 regions of interest (ROIs) were included. Twenty adenomas that produced 88 ROIs had firm consistency. There was both inter-observer and intra-observer reproducibility. Ten parameters that were based on T2W images with high discriminative power and without correlation were chosen by LASSO. The diagnostic performance of SVM and RFC was as follows: sensitivity = 95.580% and 92.950%, specificity = 83.670% and 88.420%, area under the curve = 0.956 and 0.904, respectively.

CONCLUSION

Radiomics analysis based on T2W MRI combined with various ML techniques, such as SVM and RFC, can provide preoperative information regarding pituitary adenoma consistency with high diagnostic accuracy.

Otolaryngology Considerations of Pituitary Surgery: What an Endocrinologist Should Know

Endoscopic endonasal skull base surgery is the preferred surgical approach for the management of pituitary adenomas. Perioperative management of pituitary lesions requires multidisciplinary care and typically includes a dual surgeon team consisting of a neurosurgeon and an otolaryngologist. The involvement of the otolaryngologist allows for a safe surgical approach with excellent intraoperative visualization of the tumor to enable an effective resection of the tumor by the neurosurgeon. Detection and treatment of sinonasal pathology is essential prior to surgery. Patients may experience sinonasal complaints following endoscopic transsphenoidal surgery, although this is typically temporary. Sinonasal care in the postoperative period can expedite recovery to baseline. Here we discuss the perioperative factors of endoscopic pituitary surgery that endocrinologists should be aware of, ranging from preoperative patient selection and optimization to postoperative care, with a particular emphasis on anatomic and surgical factors.

Pituitary adenoma consistency affects postoperative hormone function: a retrospective study

BACKGROUND

Tumor consistency recently emerged as a key factor in surgical planning for pituitary adenomas, but its impact on postoperative endocrine function is still unclear. Our study aimed to evaluate the impact of tumor consistency on the development of postoperative pituitary deficiencies.

METHODS

Single-center, retrospective analysis of consecutive pituitary surgeries performed between January 2017 and January 2021 at Policlinico Umberto I in Rome. All patients underwent radiological and biochemical evaluations at baseline, and hormone assessments 3 and 6 months after pituitary surgery. Postoperative MRI studies were used to determine resection rates following surgery. Data on tumor consistency, macroscopic appearance, neurosurgical approach, and intraoperative complications were collected.

RESULTS

Fifty patients [24 women, mean age 57 ± 13 years, median tumor volume 4800 mm³ [95% CI 620-8828], were included. Greater tumor volume (χ² = 14.621, p = 0.006) and male sex (χ² = 12.178, p < 0.001) were associated with worse preoperative endocrine function. All patients underwent transsphenoidal adenomectomy. Fibrous consistency was observed in 10% of patients and was associated with a Ki-67 greater than 3% (χ² = 8.154, p = 0.04), greater risk of developing postoperative hormone deficiencies (χ² = 4.485, p = 0.05, OR = 8.571; 95% CI: 0.876-83.908), and lower resection rates (χ2 = 8.148, p = 0.004; OR 1.385, 95% CI; 1.040-1.844). Similarly, worse resection rates were observed in tumors with suprasellar extension (χ2 = 5.048, p = 0.02; OR = 6.000, 95% CI; 1.129-31.880) and CSI (χ2 = 4.000, p = 0.04; OR = 3.857, 95% CI; 0.997-14.916).

CONCLUSIONS

Tumor consistency might provide useful information about postoperative pituitary function, likely due to its impact on surgical procedures. Further prospective studies with larger cohorts are needed to confirm our preliminary findings.

Imaging of pituitary tumors: an update with the 5th WHO Classifications-part 1. Pituitary neuroendocrine tumor (PitNET)/pituitary adenoma

The pituitary gland is the body's master gland of the endocrine glands. Although it is a small organ, many types of tumors can develop within it. The recently revised fifth edition of the World Health Organization (WHO) classifications (2021 World Health Organization Classification of Central Nervous System Tumors and 2022 World Health Organization Classification of Endocrine and Neuroendocrine Tumors) revealed significant changes to the classification of pituitary adenomas, the most common type of pituitary gland tumor. This change categorized pituitary adenomas as neuroendocrine tumors and proposed the name to be revised to pituitary neuroendocrine tumor (PitNET). The International Classification of Diseases for Oncology behavior code for this tumor was previously "0" for benign tumor. In contrast, the fifth edition WHO classification has changed this code to "3" for primary malignant tumors as same to neuroendocrine tumor in other organs. Because the WHO classification made an important and significant change in the fundamental concept of the disease, in this paper, we will discuss the imaging diagnosis (magnetic resonance imaging, computed tomography, and positron emission tomography) of PitNET/pituitary adenoma in detail, considering these revisions as per the latest version of the WHO classification.

Predicting tumor consistency and extent of resection in non-functioning pituitary tumors

PURPOSE

To (1) identify a radiological parameter to predict non-functioning pituitary tumor (NFPT) consistency, (2) examine the relationship between NFPT consistency and extent of resection (EOR), (3) investigate if tumor consistency predictors can anticipate EOR.

METHODS

The ratio (T2SIR) between the T2 min signal intensity (SI) of the tumor and the T2 mean SI of the CSF was the main radiological parameter, being determined through a radiomic-voxel analysis and calculated using the following formula: T2SIR = [(T2 tumor mean SI - SD)/T2 CSF SI]. The tumor consistency was pathologically estimated as collagen percentage (CP). EOR of NFPTs was evaluated by exploiting a volumetric technique and its relationship with the following explanatory variables was explored: CP, Knosp-grade, tumor volume, inter-carotid distance, sphenoidal sinus morphology, Hardy-grade, suprasellar tumor extension.

RESULTS

A statistically significant inverse correlation between T2SIR and CP was demonstrated (p = 0.0001), with high diagnostic power of T2SIR in predicting NFPT consistency (ROC curve analysis' AUC = 0.88; p = 0.0001). The following predictors of EOR were identified in the univariate analysis: CP (p = 0.007), preoperative volume (p = 0.045), Knosp grade (p = 0.0001), tumor suprasellar extension (p = 0.044). The multivariate analysis demonstrated two variables as unique predictors of EOR: CP (p = 0.002) and Knosp grade (p = 0.001). The T2SIR was a significant predictor of EOR both in the univariate (p = 0.01) and multivariate model (p = 0.003).

CONCLUSION

This study offers the potential to improve NFPT preoperative surgical planning and patient counseling by employing the T2SIR as a preoperative predictor of tumor consistency and EOR. Meanwhile, tumor consistency and Knosp grade were found to play an important role in predicting EOR.

The HACKD Score-Predicting Extent of Resection of Pituitary Macroadenomas Through an Endoscopic Endonasal Transsphenoidal Approach

BACKGROUND

Predicting extent of resection before pituitary surgery is imperative for operative planning and patient counseling. In the era of endoscopic endonasal transsphenoidal surgery (EEA), a specific, reliable tool for predicting resection of macroadenomas would have widespread applications.

OBJECTIVE

To identify factors that predict resection of pituitary macroadenomas through the EEA.

METHODS

A prospectively maintained, multicenter database of 277 consecutive macroadenomas resected through the EEA was analyzed. Multivariate logistic regression identified predictors of gross total resection (GTR). A simple scoring system, the Hardy, Age, Clival, Knosp, Depth (HACKD) Score, was developed and tested.

RESULTS

GTR was achieved in 82.3% (228/277) of cases. Older than 50 years (odds ratio [OR] 2.96, P = .01), clival extension (OR 5.87, P < .01), Hardy grade C or D suprasellar extension (OR 3.91, P = .01), Knosp grade 3 or 4 cavernous sinus invasion (OR 7.62, P < .01), and tumor depth >20 mm (OR 5.14, P < .01) were all associated with subtotal resection. The HACKD score, awarding 1 point each for Hardy grade C or D, and older than 50 years, and 2 points each for clival extension, Knosp grades 3 or 4, and tumor depth >20 mm, demonstrated excellent discriminative ability (AUROC 0.887, 95% CI: 0.839-0.934). The rate of GTR progressively decreased with a higher HACKD score. Rates of GTR were 95.8% (182/190) for low (HACKD ≤2), 59.5% (44/74) for moderate (HACKD 3-5), and 15.4% (2/13) for high (HACKD 6+) HACKD scores.

CONCLUSION

The HACKD score is a simple and accurate tool based on the largest study analyzing predictors of GTR in pituitary macroadenomas operated through the EEA.

Methods of preoperative prediction of pituitary adenoma consistency: a systematic review

This study aims to review the current literature on methods of preoperative prediction of pituitary adenoma consistency. Pituitary adenoma consistency may be a limiting factor for successful surgical removal of tumors. Efforts have been made to investigate the possibility of an accurate assessment of the preoperative consistency to allow for safer and more effective surgery planning. We searched major scientific databases and systematically analyzed the results. A total of 54 relevant articles were identified and selected for inclusion. These studies evaluated methods based on either MRI intensity, enhancement, radiomics, MR elastometry, or CT evaluation. The results of these studies varied widely. Most studies used the average intensity of either T2WI or ADC maps. Firm tumors appeared hyperintense on T2WI, although only 55% of the studies reported statistically significant results. There are mixed reports on ADC values in firm tumors with findings of increased values (28%), decreased values (22%), or no correlation (50%). Multiple contrast enhancement-based methods showed good results in distinguishing between soft and firm tumors. There were mixed reports on the utility of MR elastography. Attempts to develop radiomics and machine learning-based models have achieved high accuracy and AUC values; however, they are prone to overfitting and need further validation. Multiple methods of preoperative consistency assessment have been studied. None demonstrated sufficient accuracy and reliability in clinical use. Further efforts are needed to enable reliable surgical planning.

A Scoring System That Predicts Difficult Lipoma Resection: Logistic Regression and Tenfold Cross-Validation Analysis

Introduction

Most lipomas are readily dissected and removed. However, some cases can pose surgical difficulties. This retrospective study sought to identify clinical and radiological risk factors that predict difficult lipoma resection and can be used in a clinically useful scoring system that predicts difficulty preoperatively.

Methods

The study cohort consisted of all consecutive patients who underwent resection of pathology-confirmed lipoma during 2016–2018 at a tertiary care referral center in Tokyo, Japan. Surgical difficulty was defined as difficulty separating some/all of the tumor from the surrounding tissue by hand and inability to extract the tumor in one piece. Descriptive, univariate, and multivariate logistic regression analyses were conducted to identify predictive factors. The predictive accuracy of the scoring system that included these factors was assessed by tenfold cross-validation analysis. Receiver-operating curve (ROC) analysis was conducted to identify the optimal cutoff score for predicting surgical difficulty.

Results

Of the 86 cases, 36% involved surgical difficulty. Multivariate analysis showed that subfascial intramuscular location (odds ratio 42.7, 95% confidence interval 3.0–608.0), broad touching of underlying structures (46.5, 3.7–586.0), in-flowing blood vessels (9.3, 1.1–78.5), and unclear boundaries (109.0, 1.1–1110.0) significantly predicted surgical difficulty. These factors were used to construct a 0–4 point scoring system (with one point per variable). On cross-validation, the accuracy of the scoring system was 82.4% (Cohen’s kappa of 0.57). ROC analysis showed that scores ≥ 2 predicted surgical difficulty with sensitivity and specificity of 55% and 98%, respectively.

Conclusions

Our scoring system accurately predicted lipoma resection difficulty and may help operators prepare, thereby facilitating surgery.

Application of “mosiac sign” on T2-WI in predicting the consistency of pituitary neuroendocrine tumors

Purpose

Tumor consistency is important for pituitary neuroendocrine tumors (PitNETs) resection to improve surgical outcomes. In this study, we evaluated the T2-WI of PitNETs and defined a specific T2-WI signaling manifestation, the “Mosaic sign,” to predict tumor consistency and resection of PitNETs.

Design

A retrospective review of MRI and tumor histology of 137 consecutive patients who underwent endoscopic endonasal resection for PitNETs was performed.

Methods

The “Mosaic sign” was defined by the ratio of the tumor itself T2-WI signals, and characterized by multiple intratumor hyperintense dots. The degree of tumor resection was an assessment by postoperative MRI examination. The presence of the “Mosaic sign” was compared with patients' basic information, tumor consistency, tumor pathological staining, and surgical result. To determine whether the presence or absence of “Mosaic sign” could predict tumor consistency and guide surgical resection of tumors.

Results

Statistical analysis showed that the consistency of the tumor and the degree of resection were correlated with the “Mosaic sign”. In the 137 cases of T2-WI, 43 had “Mosaic sign”, 39 cases had soft tumor consistency, and 4 were classified as fibrous, of which 42 were completely resected and 1 was subtotal resected. Of the 94 patients without “Mosaic sign”, the consistency of tumor of 54 cases were classified as soft, the remaining 40 cases were fibrous, 80 cases were completely resected, and 14 cases were subtotal resected. Postoperative cerebrospinal fluid leakage occurred in 1 patient. The number of corticotroph adenomas in the group of “Mosaic sign” was higher, with the statistical difference between the two groups (P = 0.0343).

Conclusions

The presence of the “Mosaic sign” in T2-WI may provide preoperative information for pituitary adenomas consistency and effectively guide surgical approaches.

Predicting pituitary adenoma consistency with preoperative magnetic resonance elastography

OBJECTIVE

Pituitary adenoma is one of the most common primary intracranial neoplasms. Most of these tumors are soft, but up to 17% may have a firmer consistency. Therefore, knowing the tumor consistency in the preoperative setting could be helpful. Multiple imaging methods have been proposed to predict tumor consistency, but the results are controversial. This study aimed to evaluate the efficacy of MR elastography (MRE) in predicting tumor consistency and its potential use in a series of patients with pituitary adenomas.

METHODS

Thirty-eight patients with pituitary adenomas (≥ 2.5 cm) were prospectively evaluated with MRI and MRE before surgery. Absolute MRE stiffness values and relative MRE stiffness ratios, as well as the relative ratio of T1 signal, T2 signal, and diffusion-weighted imaging apparent diffusion coefficient (ADC) values were determined prospectively by calculating the ratio of those values in the tumor to adjacent left temporal white matter. Tumors were classified into three groups according to surgical consistency (soft, intermediate, and firm). Statistical analysis was used to identify the predictive value of the different radiological parameters in determining pituitary adenoma consistency.

RESULTS

The authors included 32 (84.21%) nonfunctional and 6 (15.79%) functional adenomas. The mean maximum tumor diameter was 3.7 cm, and the mean preoperative tumor volume was 16.4 cm3. Cavernous sinus invasion was present in 20 patients (52.63%). A gross-total resection was possible in 9 (23.68%) patients. The entire cohort's mean absolute tumor stiffness value was 1.8 kPa (range 1.1-3.7 kPa), whereas the mean tumor stiffness ratio was 0.66 (range 0.37-1.6). Intraoperative tumor consistency was significantly correlated with absolute and relative tumor stiffness (p = 0.0087 and 0.007, respectively). Tumor consistency alone was not a significant factor for predicting gross-total resection. Patients with intermediate and firm tumors had more complications compared to patients with soft tumors (50.00% vs 12.50%, p = 0.02) and also had longer operative times (p = 0.0002).

CONCLUSIONS

Whereas other MRI sequences have proven to be unreliable in determining tumor consistency, MRE has been shown to be a reliable tool for predicting adenoma consistency. Preoperative knowledge of tumor consistency could be potentially useful for surgical planning, counseling about potential surgical risks, and estimating the length of operative time.

Machine Learning in Pituitary Surgery

Machine learning applications in neurosurgery are increasingly reported for diverse tasks such as faster and more accurate preoperative diagnosis, enhanced lesion characterization, as well as surgical outcome, complications and healthcare cost prediction. Even though the pertinent literature in pituitary surgery is less extensive with respect to other neurosurgical diseases, past research attempted to answer clinically relevant questions to better assist surgeons and clinicians. In the present chapter we review reported ML applications in pituitary surgery including differential diagnosis, preoperative lesion characterization (immunohistochemistry, cavernous sinus invasion, tumor consistency), surgical outcome and complication predictions (gross total resection, tumor recurrence, and endocrinological remission, cerebrospinal fluid leak, postoperative hyponatremia). Moreover, we briefly discuss from a practical standpoint the current barriers to clinical translation of machine learning research. On the topic of pituitary surgery, published reports can be considered mostly preliminary, requiring larger training populations and strong external validation. Thoughtful selection of clinically relevant outcomes of interest and transversal application of model development pipeline-together with accurate methodological planning and multicenter collaborations-have the potential to overcome current limitations and ultimately provide additional tools for more informed patient management.

Radiomic Features on Multiparametric MRI for Preoperative Evaluation of Pituitary Macroadenomas Consistency: Preliminary Findings

BACKGROUND

Preoperative assessment of the consistency of pituitary macroadenomas (PMA) might be needed for surgical planning.

PURPOSE

To investigate the diagnostic performance of radiomics models based on multiparametric magnetic resonance imaging (mpMRI) for preoperatively evaluating the tumor consistency of PMA.

STUDY TYPE

Retrospective.

POPULATION

One hundred and fifty-six PMA patients (soft consistency, N = 104 vs. hard consistency, N = 52), divided into training (N = 108) and test (N = 48) cohorts. The tumor consistency was determined on surgical findings.

FIELD STRENGTH/SEQUENCE

T1-weighted imaging (T1WI), contrast-enhanced T1WI (T1CE), and T2-weighted imaging (T2WI) using spin-echo sequences with a 3.0-T scanner.

ASSESSMENT

An automated three-dimensional (3D) segmentation was performed to generate the volume of interest (VOI) on T2WI, then T1WI/T1CE were coregistered to T2WI. A total of 388 radiomic features were extracted on each VOI of mpMRI. The top-discriminative features were identified using the minimum-redundancy maximum-relevance method and 0.632+ bootstrapping. The radiomics models based on each sequence and their combinations were established via the random forest (RF) and support vector machine (SVM), and independently evaluated for their ability in distinguishing PMA consistency.

STATISTICAL TESTS

Mann-Whitney U-test and Chi-square test were used for comparison analysis. The area under the receiver operating characteristic curve (AUC), accuracy (ACC), sensitivity (SEN), specificity (SPE), and relative standard deviation (RSD) were calculated to evaluate each model's performance. ACC with P-value<0.05 was considered statistically significant.

RESULTS

Eleven mpMRI-based features exhibited statistically significant differences between soft and hard PMA in the training cohort. The radiomics model built on combined T1WI/T1CE/T2WI demonstrated the best performance among all the radiomics models with an AUC of 0.90 (95% confidence interval [CI]: 0.87-0.92), ACC of 0.87 (CI: 0.84-0.89), SEN of 0.83 (CI: 0.81-0.85), and SPE of 0.87 (CI: 0.85-0.99) in the test cohort.

DATA CONCLUSION

Radiomic features based on mpMRI have good performance in the presurgical evaluation of PMA consistency.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Clinical relevance of tumor consistency in pituitary adenoma

PURPOSE

To review the clinical relevance of pituitary adenoma (PA) consistency and its relationship to clinical presentation, radiologic and histopathological characteristics, and surgical outcomes.

BACKGROUND

PA consistency is a critical factor influencing operative planning, surgical outcomes, and patient counseling. There is no validated classification of PA consistency in the literature, and there are no current preoperative variables capable of predicting it.

REVIEW

We conducted a thorough literature review of the Medline, Embase, Web of Science, and Cochrane Library databases. The inclusion criteria were all articles that described PA consistency and correlated it with preoperative aspects, radiological, pathological, and operative findings, or clinical outcomes.

DISCUSSION

Although most authors differentiate easily aspirated (soft) tumors from those that are not (fibrous, might require prior fragmentation), there is no universally accepted PA consistency classification. Fibrous PA tends to be hypointense on T2WI and has lower apparent diffusion coefficient (ADC) values. Fibrous tumors seemed to present higher invasion into neighboring structures, including the cavernous sinus. Several articles suggest that dopamine agonists could increase PA consistency and that prior surgery and radiotherapy also make PA more fibrous. The anatomopathological studies identify collagen as being mainly responsible for fibrous consistency of adenomas.

CONCLUSIONS

Preoperative knowledge of PA consistency affords the neurosurgeon substantial benefit, which clearly appears to be relevant to surgical planning, risks, and surgery outcomes. It could also encourage the centralization of these high complexity tumors in reference centers. Further studies may be enhanced by applying standard consistency classification of the PA and analyzing a more extensive and prospective series of fibrous PA.

Development and clinical validation of a grading system for pituitary adenoma consistency

OBJECTIVE

Pituitary adenoma (PA) consistency, or texture, is an important intraoperative characteristic that may dictate operative dissection techniques and/or instruments used for tumor removal during endoscopic endonasal approaches (EEAs). The impact of PA consistency on surgical outcomes has yet to be elucidated.

METHODS

The authors developed an objective 5-point grading scale for PA consistency based on intraoperative characteristics, including ease of tumor debulking, manipulation, and instrument selection, ranging from cystic/hemorrhagic tumors (grade 1) to calcified tumors (grade 5). The proposed grading system was prospectively assessed in 306 consecutive patients who underwent an EEA for PAs, and who were subsequently analyzed for associations with surgical outcomes, including extent of resection (EOR) and complication profiles.

RESULTS

Institutional database review identified 306 patients who underwent intraoperative assessment of PA consistency, of which 96% were macroadenomas, 70% had suprasellar extension, and 44% had cavernous sinus invasion (CSI). There were 214 (69.9%) nonfunctional PAs and 92 functional PAs (31.1%). Distribution of scores included 15 grade 1 tumors (4.9%), 112 grade 2 tumors (36.6%), 125 grade 3 tumors (40.8%), 52 grade 4 tumors (17%), and 2 grade 5 tumors (0.7%). Compared to grade 1/2 and grade 3 PAs, grade 4/5 PAs were significantly larger (22.5 vs 26.6 vs 27.4 mm, p < 0.01), more likely to exhibit CSI (39% vs 42% vs 59%, p < 0.05), and trended toward nonfunctionality (67% vs 68% vs 82%, p = 0.086). Although there was no association between PA consistency and preoperative headaches or visual dysfunction, grade 4/5 PAs trended toward preoperative (p = 0.058) and postoperative panhypopituitarism (p = 0.066). Patients with preoperative visual dysfunction experienced greater improvement if they had a grade 1/2 PA (p < 0.05). Intraoperative CSF leaks were noted in 32% of cases and were more common with higher-consistency-grade tumors (p = 0.048), although this difference did not translate to postoperative CSF leaks. Gross-total resection (%) was more likely with lower PA consistency score as follows: grade 1/2 (60%), grade 3 (50%), grade 4/5 (44%; p = 0.045). Extracapsular techniques were almost exclusively performed in grade 4/5 PAs. Assignment of scores showed low variance and high reproducibility, with an intraclass correlation coefficient of 0.905 (95% CI 0.815-0.958), indicating excellent interrater reliability.

CONCLUSIONS

These findings demonstrate clinical validity of the proposed intraoperative grading scale with respect to PA subtype, neuroimaging features, EOR, and endocrine complications. Future studies will assess the relation of PA consistency to preoperative MRI findings to accurately predict consistency, thereby allowing the surgeon to tailor the exposure and prepare for varying resection strategies.

Analysis of 7-tesla diffusion-weighted imaging in the prediction of pituitary macroadenoma consistency

OBJECTIVE

Endoscopic surgery is an effective treatment strategy for pituitary adenomas; however, intrinsic tumor properties such as tumor consistency can challenge or preclude gross-total resection. Preoperative characterization of tumor consistency may help to guide the surgical approach and to predict the extent of resection that is possible. Advanced radiological modalities such as 7T diffusion-weighted imaging (DWI) may be useful in probing biological tissue properties of pituitary adenomas. The objective of the present study was to examine 7T DWI as a novel method of measuring the consistency of pituitary adenomas.

METHODS

Thirteen patients with pituitary macroadenomas underwent 7T MRI, including a DWI image acquisition. Tumor apparent diffusion coefficient (ADC) was normalized to the adjacent temporal gray matter ADC. All patients underwent resection, and a single neurosurgeon blinded to ADC values rated tumor firmness from 1 (least firm) to 5 (most firm) using objective criteria. The tumor specimens were evaluated histopathologically for cellularity, collagen content, and vascularity by a neuropathologist who was also blinded to ADC values. The tumor ADC was correlated with intraoperative consistency rating, histopathology, and extent of resection. Receiver operating characteristic (ROC) curve analyses were performed to identify thresholds to predict tumor consistency.

RESULTS

Corrected ADC values were significantly correlated with both tumor firmness (r = -0.60, p = 0.029) and the extent of trichrome staining (r = -0.72, p = 0.009) such that greater ADC values were associated with both decreased tumor firmness and decreased collagen staining. Correlations between ADC values and tumor vascularity were not significant (r = -0.09, p = 0.78). Corrected ADC values in totally resected tumors (1.54) were greater than those in subtotally resected tumors (0.85) (p = 0.02), and ADC values were greater with moderate tumor cellularity (1.51) than with high tumor cellularity (0.8) (p = 0.035). There was a trend-level association for partial resections to exhibit greater tumor firmness rating (3 vs 1.7; p = 0.051). Finally, the degree of trichrome staining positively correlated with tumor firmness (r = 0.60, p = 0.04). The optimal threshold for predicting intraoperative consistency rating was an ADC ratio of 0.87 (sensitivity 80%, specificity 100%, area under the curve [AUC] 0.90; p = 0.043). The optimal cutoff for distinguishing the extent of resection was 1.19 (sensitivity 85.7%, specificity 83.3% AUC 0.833; p = 0.046).

CONCLUSIONS

The authors' results suggest that a high-resolution ADC of pituitary adenomas is a sensitive measure of tumor consistency. 7T DWI may hold clinical value in the preoperative workup and surgical management of patients with pituitary macroadenomas.

Proposal and Validation of a Simple Grading Scale (TRANSSPHER Grade) for Predicting Gross Total Resection of Nonfunctioning Pituitary Macroadenomas After Transsphenoidal Surgery

BACKGROUND

A simple, reliable grading scale to better characterize nonfunctioning pituitary adenomas (NFPAs) preoperatively has potential for research and clinical applications.

OBJECTIVE

To develop a grading scale from a prospective multicenter cohort of patients that accurately and reliably predicts the likelihood of gross total resection (GTR) after transsphenoidal NFPA surgery.

METHODS

Extent-of-resection (EOR) data from a prospective multicenter study in transsphenoidal NFPA surgery were analyzed (TRANSSPHER study; ClinicalTrials.gov NCT02357498). Sixteen preoperative radiographic magnetic resonance imaging (MRI) tumor characteristics (eg, tumor size, invasion measures, tumor signal characteristics, and parameters impacting surgical access) were evaluated to determine EOR predictors, to calculate receiver-operating characteristic curves, and to develop a grading scale. A separate validation cohort (n = 165) was examined to assess the scale's performance and inter-rater reliability.

RESULTS

Data for 222 patients from 7 centers treated by 15 surgeons were analyzed. Approximately one-fifth of patients (18.5%; 41 of 222) underwent subtotal resection (STR). Maximum tumor diameter > 40 mm; nodular tumor extension through the diaphragma into the frontal lobe, temporal lobe, posterior fossa, or ventricle; and Knosp grades 3 to 4 were identified as independent STR predictors. A grading scale (TRANSSPHER grade) based on a combination of these 3 features outperformed individual variables in predicting GTR (AUC, 0.732). In a validation cohort, the scale exhibited high sensitivity and specificity (AUC, 0.779) and strong inter-rater reliability (kappa coefficient, 0.617).

CONCLUSION

This simple, reliable grading scale based on preoperative MRI characteristics can be used to better characterize NFPAs for clinical and research purposes and to predict the likelihood of achieving GTR.

Prediction of pituitary adenoma surgical consistency: radiomic data mining and machine learning on T2-weighted MRI

Purpose

Pituitary macroadenoma consistency can influence the ease of lesion removal during surgery, especially when using a transsphenoidal approach. Unfortunately, it is not assessable on standard qualitative MRI. Radiomic texture analysis could help in extracting mineable quantitative tissue characteristics. We aimed to assess the accuracy of texture analysis combined with machine learning in the preoperative evaluation of pituitary macroadenoma consistency in patients undergoing endoscopic endonasal surgery.

Methods

Data of 89 patients (68 soft and 21 fibrous macroadenomas) who underwent MRI and transsphenoidal surgery at our institution were retrospectively reviewed. After manual segmentation, radiomic texture features were extracted from original and filtered MR images. Feature stability analysis and a multistep feature selection were performed. After oversampling to balance the classes, 80% of the data was used for hyperparameter tuning via stratified 5-fold cross-validation, while a 20% hold-out set was employed for its final testing, using an Extra Trees ensemble meta-algorithm. The reference standard was based on surgical findings.

Results

A total of 1118 texture features were extracted, of which 741 were stable. After removal of low variance (n = 4) and highly intercorrelated (n = 625) parameters, recursive feature elimination identified a subset of 14 features. After hyperparameter tuning, the Extra Trees classifier obtained an accuracy of 93%, sensitivity of 100%, and specificity of 87%. The area under the receiver operating characteristic and precision-recall curves was 0.99.

Conclusion

Preoperative T2-weighted MRI texture analysis and machine learning could predict pituitary macroadenoma consistency.

Electronic supplementary material

The online version of this article (10.1007/s00234-020-02502-z) contains supplementary material, which is available to authorized users.

Hemorrhagic Presentation of Rathke Cleft Cysts: A Surgical Case Series

BACKGROUND

Rathke cleft cysts (RCCs) are benign sellar and suprasellar lesions commonly presenting as asymptomatic incidental findings. Rarely, RCCs hemorrhage and mimic pituitary apoplexy on presentation.

OBJECTIVE

To review a series of hemorrhagic RCCs for physicians encountering this rare presentation.

METHODS

A database review of >1700 transsphenoidal pituitary operations was performed at the USC Pituitary Center to identify patients with pathologically confirmed RCCs presenting with acute symptoms and evidence of hemorrhage at the time of surgery. Surgical treatment involved transsphenoidal RCC fenestration and drainage. Clinical, endocrine, and imaging outcomes were reviewed.

RESULTS

A total of 119 RCCs were identified, and 6 (5.0%) presented with hemorrhage mimicking pituitary apoplexy. Presenting symptoms included acute onset headaches (5/6), vision loss (2/6), and oculomotor nerve palsy (n = 1). Endocrine disturbances at presentation included pre-existing amenorrhea in all female patients (3/3), hypothyroidism (n = 2), panhypopituitarism (n = 2), and one with profound hyponatremia (Na 116 meq/L). All patients underwent endonasal transsphenoidal fenestration and drainage with no major complications. Over mean follow-up of 38.4 mo, 2/2 patients with vision loss reported improvement, and 2/5 patients with headaches reported improvement. Although all women resumed menses, patients with preoperative hypopituitarism did not experience pituitary axis improvement. Follow-up magnetic resonance imaging showed no instances of RCC recurrence with a mean imaging follow-up of 38.6 mo.

CONCLUSION

RCCs occasionally present with hemorrhage and clinical symptoms that may be confused with apoplexy. Outcomes following hemorrhagic RCC treatment are excellent when treated at tertiary pituitary centers. Although hyperprolactinemia often improves following surgery, other pituitary axis deficits typically do not.

Pituitary adenoma consistency: Direct correlation of ultrahigh field 7T MRI with histopathological analysis

PURPOSE

Tumor consistency is a critical factor in surgical planning that influences ease of resection and risk of operative morbidity. The ability of MRI to predict tumor consistency tumor consistency has been shown to increase with higher field strength. The present study examined the utility of 7 T (7 T) MRI in predicting the tumor consistency of pituitary adenomas.

METHOD

Fifteen patients with pituitary adenomas were preoperatively scanned at 7 T MRI. Regions of interest were drawn around lesions for voxel-based signal intensity (SI) analysis. The percentage of tumor voxels with intensity higher than local gray matter was calculated on T2-weighted imaging. A single neurosurgeon rated tumor firmness for all patients. Histopathological analysis was performed. Radiological tumor features were correlated with intraoperative tumor consistency measurements and histopathology.

RESULTS

Tumors rated as 'soft' intraoperatively were hyperintense to local gray matter on T2-weighted imaging. 'Firm' tumors were hypointense to local gray matter. There was no significant difference in SI ratio between soft and firm tumors (p = 0.098). Soft tumors had a significantly higher percentage of tumor voxels greater than local gray matter compared to firm tumors (p = 0.035, Cohen's D-effect size = 1.208). Soft tumors had higher vascularity than firm tumors, p = 0.015.

CONCLUSIONS

The signal and contrast advantage conferred by 7 T MRI may provide valuable preoperative information regarding pituitary tumor consistency and physiology. The use of granular, voxel-based analysis maximizes the potential afforded by the high resolution of 7 T imaging, and may be a valuable method of predicting consistency of pituitary adenoma.

Relationship Between Pituitary Adenoma Consistency and Extent of Resection Based on Tumor/Cerebellar Peduncle T2-Weighted Imaging Intensity (TCTI) Ratio of the Point on Preoperative Magnetic Resonance Imaging (MRI) Corresponding to the Residual Point on Postoperative MRI

Background

Controversies exist in imaging modalities for predicting adenoma consistency. In this study, we proposed a method of predicting consistency by magnetic resonance T2-sequence imaging based on adenoma to cerebellar peduncle signal (TCTI) ratio.

Material/Methods

Between January 2013 and May 2017, 191 consecutive patients with pituitary adenoma diagnosed at our institution were retrospectively studied. The consistency grade for each lesion was assigned. And the TCTI ratio based on preoperative and postoperative T2-weighted imaging was calculated.

Results

The median TCTI ratio was 1.55, 1.28, and 1.25 for soft, fibrous, and hard adenomas, respectively. The differences were significant for all groups (p<0.001). A cutoff value of 1.38 for soft adenomas was found to be 80.2% sensitive and 88.7% specific. The median ratio of the outermost layer of residual tumor was 1.25 (SD±0.408, 95% CI 1.27–1.42). It was less than that ratio of the upper, lower quarter, and middle region of adenoma, respectively, and the inter-group differences were all statistically significant with p≤0.001. The extent of resection for the soft group was significantly greater than that of the hard group (85.3% vs. 70.6%, p=0.011). Analysis of Variance (ANOVA) revealed that the consistency grade was the influencing factor of degree of resection. p=0.003.

Conclusions

The TCTI ratio showed a good correlation with pituitary adenoma consistency. We also determined the optimal ratio of the residual adenoma.

Texture Analysis of High b-Value Diffusion-Weighted Imaging for Evaluating Consistency of Pituitary Macroadenomas

BACKGROUND

Preoperative evaluation of the consistency of pituitary macroadenomas is important for neurosurgeons to prepare the surgical plan.

PURPOSE

To evaluate the diagnostic performance of texture analysis (TA) of diffusion-weighted imaging (DWI) at a standard b-value (b = 1000 s/mm² ) and a high b-value (b = 2000 s/mm² ) for their ability to assess the tumor consistency of pituitary macroadenomas.

STUDY TYPE

Retrospective.

POPULATION/SUBJECTS

Fifty patients with histologically confirmed pituitary macroadenomas were classified as soft (n = 37) or hard (n = 13) types.

FIELD STRENGTH/SEQUENCE

Coronal T₂ -weighted imaging (T₂ WI), Readout Segmentation of Long Variable Echo-trains (RESOLVE) DWI at b = 1000 s/mm² and b = 2000 s/mm² were acquired with 3.0T MRI.

ASSESSMENT

The corresponding apparent diffusion coefficient (ADC) maps (ADC₁₀₀₀ and ADC₂₀₀₀ ) were registered to T₂ WI. Regions of interest (ROIs) were manually drawn along the solid part of the tumor from the coregistered T₂ WI-ADC images. The texture parameters from T₂ WI, ADC₁₀₀₀ , and ADC₂₀₀₀ were acquired.

STATISTICAL TESTS

The texture parameters were compared between the two types by using unpaired Student's t-test. Receiver operating characteristic (ROC) curves and logistic regression analyses were used to assess their diagnostic performance.

RESULTS

Significant differences in TA parameters of ADC₁₀₀₀ and ADC₂₀₀₀ were observed between soft and hard types (P &lt; 0.05 for all), whereas the TA of T₂ WI resulted in no significant difference (P &gt; 0.05 for all). TA of ADC₂₀₀₀ provided a superior diagnostic performance compared with that of ADC₁₀₀₀ (P = 0.038). A combination of mean value and entropy of ADC₂₀₀₀ yielded an AUC, a sensitivity, and a specificity of 0.911, 78.4% and 92.3%, respectively.

DATA CONCLUSION

TA of ADC values were useful for assessing the tumor consistency of pituitary macroadenomas. ADC₂₀₀₀ may facilitate better type discrimination.

LEVEL OF EVIDENCE

3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1507-1513.

The Microenvironment of Pituitary Tumors-Biological and Therapeutic Implications

The tumor microenvironment (TME) includes resident and infiltrative non-tumor cells, as well as blood and lymph vessels, extracellular matrix molecules, and numerous soluble factors, such as cytokines and chemokines. While the TME is now considered to be a prognostic tool and a therapeutic target for many cancers, little is known about its composition in pituitary tumors. This review summarizes our current knowledge of the TME within pituitary tumors and the strong interest in TME as a therapeutic target. While we cover the importance of angiogenesis and immune infiltrating cells, we also address the role of the elusive folliculostellate cells, the emerging literature on pituitary tumor-associated fibroblasts, and the contribution of extracellular matrix components in these tumors. The cases of human pituitary tumors treated with TME-targeting therapies are reviewed and emerging concepts of vascular normalization and combined therapies are presented. Together, this snapshot overview of the current literature pinpoints not only the underestimated role of TME components in pituitary tumor biology, but also the major promise it may offer for both prognosis and targeted therapeutics.

The Utility of Using Preoperative MRI as a Predictor for Intraoperative Pituitary Adenoma Consistency and Surgical Resection Technique

Objective  Most pituitary adenomas are of soft consistency and can be resected during surgery with routine suction instruments. However, fibrous adenomas may require more aggressive techniques. The ability to predict consistency on magnetic resonance imaging (MRI) would improve preoperative preparation and may have implications on the extent of resection. Design  A retrospective review of MRI and tumor histology of 50 consecutive patients who underwent endoscopic endonasal resection for nonfunctional adenomas was performed. Methods  An intensity ratio was calculated based on quantitative MRI signal intensity of the adenoma and pons. Intraoperatively, a sequentially graded technique required for resection ranged from suction (R1) for softer tumors, curettes (R2) for tumors with intermediate consistency, and aspirators and/or other microinstruments (R3) for firmer tumors. Fibrotic content was determined from histologic collagen percentage, and rates of gross total resection (GTR) were calculated from postoperative imaging. Statistical analyses were performed to determine if resection classification could be predicted by intensity ratio or collagen percentage, calculate ratio of cut-off points for clinical use, and assess for correlation between intensity ratios and collagen percentage. Results  Tumors with ratios < 1.6 on the T2-weighted coronal image and collagen content > 5.3% were likely to have required a more aggressive resection technique. Statistically significant lower rates of GTR and higher rates of perioperative complications were seen with such tumors. Conclusion  Preoperative MRI analyses can be helpful but not definitive in predicting adenoma consistency. Fibrous adenomas, associated with higher collagen content, are more difficult to resect and have higher rates of subtotal resection.

Evaluation of Surgical Resection Goal and Its Relationship to Extent of Resection and Patient Outcomes in a Multicenter Prospective Study of Patients With Surgically Treated, Nonfunctioning Pituitary Adenomas: A Case Series

BACKGROUND

The influence of the surgeon's preoperative goal regarding the extent of tumor resection on patient outcomes has not been carefully studied among patients with nonfunctioning pituitary adenomas.

OBJECTIVE

To analyze the relationship between surgical tumor removal goal and patient outcomes in a prospective multicenter study.

METHODS

Centrally adjudicated extent of tumor resection (gross total resection [GTR] and subtotal resection [STR]) data were analyzed using standard univariate and multivariable analyses.

RESULTS

GTR was accomplished in 148 of 171 (86.5%) patients with planned GTR and 32 of 50 (64.0%) patients with planned STR (P = .001). Sensitivity, specificity, positive predictive value, and negative predictive value of GTR goal were 82.2, 43.9, 86.5, and 36.0%, respectively. Knosp grade 0-2, first surgery, and being an experienced surgeon were associated with surgeons choosing GTR as the goal (P &lt; .01). There was no association between surgical goal and presence of pituitary deficiency at 6 mo (P = .31). Tumor Knosp grade (P = .004) and size (P = .001) were stronger predictors of GTR than was surgical goal (P = .014). The most common site of residual tumor was the cavernous sinus (29 of 41 patients; 70.1%).

CONCLUSION

This is the first pituitary surgery study to examine surgical goal regarding extent of tumor resection and associated patient outcomes. Surgical goal is a poor predictor of actual tumor resection. A more aggressive surgical goal does not correlate with pituitary gland dysfunction. A better understanding of the ability of surgeons to meet their expectations and of the factors associated with surgical result should improve prognostication and preoperative counseling.

Preoperative evaluation of tumour consistency in pituitary macroadenomas: a machine learning-based histogram analysis on conventional T2-weighted MRI

PURPOSE

To evaluate the potential value of machine learning (ML)-based histogram analysis (or first-order texture analysis) on T2-weighted magnetic resonance imaging (MRI) for predicting consistency of pituitary macroadenomas (PMA) and to compare it with that of signal intensity ratio (SIR) evaluation.

METHODS

Fifty-five patients with 13 hard and 42 soft PMAs were included in this retrospective study. Histogram features were extracted from coronal T2-weighted original, filtered and transformed MRI images by manual segmentation. To achieve balanced classes (38 hard vs 42 soft), multiple samples were obtained from different slices of the PMAs with hard consistency. Dimension reduction was done with reproducibility analysis, collinearity analysis and feature selection. ML classifier was artificial neural network (ANN). Reference standard for the classifications was based on surgical and histopathological findings. Predictive performance of histogram analysis was compared with that of SIR evaluation. The main metric for comparisons was the area under the receiver operating characteristic curve (AUC).

RESULTS

Only 137 of 162 features had excellent reproducibility. Collinearity analysis yielded 20 features. Feature selection algorithm provided six texture features. For histogram analysis, the ANN correctly classified 72.5% of the PMAs regarding consistency with an AUC value of 0.710. For SIR evaluation, accuracy and AUC values were 74.5% and 0.551, respectively. Considering AUC values, ML-based histogram analysis performed better than SIR evaluation (z = 2.312, p = 0.021).

CONCLUSION

ML-based T2-weighted MRI histogram analysis might be a useful technique in predicting the consistency of PMAs, with a better predictive performance than that of SIR evaluation.

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

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.

Clinical usefulness of 99mTc-HYNIC-TOC, 99mTc(V)-DMSA, and 99mTc-MIBI SPECT in the evaluation of pituitary adenomas

Background

The aim of this study was to evaluate the behavioral uptake and ability to diagnose pituitary adenoma (PA) using tumor-seeking radiopharmaceuticals, and to provide a semiquantitative analysis of tracer uptake in the pituitary region.

Patients and methods

The study included 33 (13 hormonally active and 20 nonfunctioning) patients with PA and 45 control participants without pituitary involvement. All patients (n=78) underwent single photon emission computed tomography (SPECT) imaging with technetium-99m-labeled hydrazinonicotinyl-tyr³-octreotide (^99mTc-HYNIC-TOC), dimercaptosuccinic acid (^99mTc(V)-DMSA) and hexakis-2-methoxyisobutylisonitrile (^99mTc-MIBI). A semiquantitative analysis of abnormal uptake was carried out by drawing identical regions of interest over the pituitary area and the normal brain on one transverse section that shows the lesion most clearly. The pituitary uptake to normal brain uptake (P/B) ratio was calculated in all cases.

Results

The result of this study confirms that the SPECT semiquantitative method, with all three tracers, showed statistically significant differences between the PA group and the controls. However, ^99mTc-HYNIC-TOC scintigraphy could have the highest diagnostic yield because of the smallest overlap between the P/B ratios between adenoma versus nonadenoma participants (the receiver operating characteristic curve P/B ratio cut-off value was 13.08). In addition, only ^99mTc-MIBI SPECT have the diagnostic potential to detect secreting PAs, with statistically significant differences between groups (P<0.001), with an receiver operating characteristic curve P/B ratio cut-off value of 16.72.

Conclusion

A semiquantitative analysis of increased focal tracer uptake in the sellar area showed that ^99mTc-HYNIC-TOC is a highly sensitive and reliable tumor-seeking agent for detecting PA, whereas ^99mTc-MIBI SPECT is a highly sensitive and specific method in differentiating hormone-secreting pituitary tumor.

Tumor to Cerebellar Peduncle T2-Weighted Imaging Intensity Ratio Fails to Predict Pituitary Adenoma Consistency

Object  The consistency of pituitary macroadenomas affects the complexity of surgical resection. On T2-weighted (T2W) imaging, the intensity ratio of the tumor to the cerebellar peduncle (tumor to cerebellar peduncle T2-weighted imaging intensity [TCTI] ratio) correlates with meningioma consistency. We aimed to determine the correlation of this radiographic finding with pituitary macroadenoma consistency and to determine whether it can be used for preoperative planning. Methods  We performed a retrospective evaluation of 196 patients with macroadenomas who underwent endoscopic transsphenoidal resection from January 2012 to June 2017. Macroadenoma consistency was determined by one senior neurosurgeon at the time of surgery. Axial and coronal T2W magnetic resonance imaging images were evaluated retrospectively, and adenoma size, Knosp grade, suprasellar extension and TCTI were calculated. Results  The mean TCTI ratio was 1.70 (95% confidence interval [CI]: 1.65-1.75). Intraoperatively, 140 (71.4%) adenomas were classified as soft and 48 (24.5%) as fibrous. Gross total resection was achieved in 66.7% of fibrous adenomas and in 86.4% of soft adenomas ( p  = 0.007). The mean ratio was 1.68 (95% CI: 1.62-1.74) for soft tumors and 1.76 (95%CI: 1.67-1.84) for fibrous tumors. There was no difference in the mean TCTI ratio between groups. Lactotroph and somatotroph adenomas had a lower mean TCTI ratio compared with other functioning and nonfunctioning adenomas with a mean TCTI of 1.52 compared with 1.77. Conclusions  In this retrospective cohort study, we found that the TCTI ratio does not correlate with tumor consistency. We also noted that the TCTI ratio is increased in prolactin and growth hormone-secreting adenomas.

Role of TGF-β1/Smad3-mediated fibrosis in drug resistance mechanism of prolactinoma

Prolactinomas are the most common functional pituitary adenomas. While dopamine agonists are a primary method of therapeutic treatment, the rate of resistance to these drugs continues to increase each year. During previous long-term clinical investigations, we found that partial resistant prolactinomas exhibited significantly more fibrosis than did sensitive adenomas, suggesting a role of fibrosis in their drug resistance. Furthermore, resistant adenomas with extensive fibrosis mainly express type I and type III collagens. Since TGF-β1 is the key factor in the initiation and development of tissue fibrosis, including in the pituitary, in this study, we aimed to determine whether TGF-β1 mediated fibrosis in prolactinomas and whether fibrosis was related to prolactinoma drug resistance. Using immunochemistry and western blotting, we found that the TGF-β1/Smad3 signaling pathway-related proteins were elevated in resistant prolactinoma specimens with high degrees of fibrosis compared to levels in sensitive samples, suggesting that this pathway may play a role in prolactinoma fibrosis. In vitro, TGF-β1 stimulation promoted collagen expression in normal HS27 fibroblasts. Furthermore, the sensitivity of rat prolactinoma MMQ cells to bromocriptine decreased when they were co-cultured with HS27 cells treated with TGF-β1. The TGF-β1/Smad3 signaling-specific inhibitor SB431542 counteracted these effects, indicating that TGF-β1/Smad3-mediated fibrosis was involved in the drug-resistant mechanisms of prolactinomas. These results indicate that SB431542 may serve as a promising novel treatment for preventing fibrosis and further improving the drug resistance of prolactinomas.

Is it really possible to predict the consistency of a pituitary adenoma preoperatively?

OBJECTIVES

To determine if the consistency of pituitary adenomas can be predicted based on a preoperative MRI study and to assess the surgical outcome of firm pituitary adenomas.

MATERIALS AND METHODS

One hundred consecutive patients with pituitary adenomas and suprasellar extension were operated by a transsphenoidal approach from July 2003 to December 2006. In addition to the neurological examination, the patients were evaluated by ophthalmological, endocrinological and radiological workups. The signal intensity of the lesion on T2WI and other dimensions of the tumors were included in the MRI study.

RESULTS

There were 52 male and 48 female patients with a mean age of 42.47 years. The mean diameter of the tumor was 32.97mm and the mean SSE was 14.95mm. Six out of 100 patients had firm adenomas peroperatively. Only one of the six patients had isointense SI on T2 WI. Of these 6 patients, total excision was performed in 1 patient, subtotal in 3 patients and partial excision in 2 patients. Among the six patients with firm adenomas, 4 had preoperative hypopituitarism (P<0.001). There was a statistically significant correlation between consistency and the postoperative permanent hypopituitarism (P<0.001). The average follow up was 43.5 months. The literature is reviewed and various aspects of pituitary adenoma consistency are discussed.

CONCLUSIONS

With the present study, the consistency of pituitary adenomas cannot be reliably predicted based on a preoperative MRI study. Patients with firm adenomas likely to have more incidence of preoperative hypopituitarism and postoperative permanent hypopituitarism.