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The nature of somatotroph adenomas has not been clearly revealed in studies. We consider that there are macroscopic differences in intraoperative tumor consistency in acromegaly patients. We aimed to determine whether there is a relationship between intraoperative tumor consistency and histopathological subtypes by planning a prospective study to determine whether these differences are significant. Between August 1997 and December 2021, 1118 patients with GH-secreting tumors underwent endoscopic endonasal surgery at our Pituitary Research Center. Between January 2022 and May 2023, pure GH-secreting adenomas operated via the endoscopic endonasal approach were sequentially categorized into three types(Type-1:Soft, Type-2:Mucinous/Adhesive, Type-3:Mix/Intermediate) according to the intraoperative tumor consistency. The final patient cohort consisted 218 cases. The ratio of densely granulated adenomas(DG-A) to sparsely granulated adenomas(SG-A) was as follows: Type-1, 89/11; Type-2, 5/95; Type-3, 13/5. Logistic regression revealed that Type-1 tumors were associated with a high remission rate( p  = 0.011), and Type-2 were associated with SG-A( p  < 0.001). Furthermore, no or weak staining for E-cadherin was associated with Type-2 tumors( p  < 0.001). Surgeon could predict the prognosis and histopathological subtype of the pure somatotroph adenoma by observing the intraoperative tumor consistency. This could facilitate better intraoperative planning of patient-specific surgical strategies to increase the remission rates.

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.

Background Tumor consistency is considered to be a critical factor for the surgical removal of meningiomas and its preoperative assessment is intensively studied. A significant drawback in the research of predictive methods is the lack of a clear shared definition of tumor consistency, with most authors resorting to subjective binary classification labeling the samples as “soft” and “hard.” This classification is highly observer-dependent and its discrete nature fails to capture the fine nuances in tumor consistency. To compensate for these shortcomings, we examined the utility of texture analysis to provide an objective observer-independent continuous measure of meningioma consistency. Methods A total of 169 texturometric measurements were conducted using the Brookfield CT3 Texture Analyzer on meningioma samples from five patients immediately after the removal and on the first, second, and seventh postoperative day. The relationship between measured stiffness and time from sample extraction, subjectively assessed consistency grade and histopathological features (amount of collagen and reticulin fibers, presence of psammoma bodies, predominant microscopic morphology) was analyzed. Results The stiffness measurements exhibited significantly lower variance within a sample than among samples ( p  = 0.0225) and significant increase with a higher objectively assessed consistency grade ( p  = 0.0161, p  = 0.0055). A significant negative correlation was found between the measured stiffness and the time from sample extraction ( p  < 0.01). A significant monotonic relationship was revealed between stiffness values and amount of collagen I and reticulin fibers; there were no statistically significant differences between histological phenotypes in regard to presence of psammoma bodies and predominant microscopic morphology. Conclusions We conclude that the values yielded by texture analysis are highly representative of an intrinsic consistency-related quality of the sample despite the influence of intra-sample heterogeneity and that our proposed method can be used to conduct quantitative studies on the role of meningioma consistency.

Background/objectives The consistency of pituitary adenoma (PA) significantly impacts surgical difficulty and the extent of resection. Machine learning (ML) and radiomics have emerged as quantitative tools to predict tumor firmness from MRI-derived features. This systematic review and meta-analysis aimed to synthesize the diagnostic performance of ML-based models for preoperative prediction of PA consistency. Methods PubMed, Embase, Scopus, and Web of Science were searched through September 2025. Studies developing or validating ML or deep learning (DL) models for predicting PA consistency were included. Pooled estimates of area under the curve (AUC), accuracy (ACC), sensitivity (SEN), specificity (SPE), and diagnostic odds ratio (DOR) were calculated with 95% confidence intervals (CIs). Results Nine studies with 1,621 patients were analyzed. Algorithms included Extra Trees (ET), Random Forest (RF), Support Vector Machine (SVM), k-Nearest Neighbors (kNN), Logistic Regression (LR), Artificial Neural Network (ANN), and hybrid DL architectures. The pooled AUC was 0.92 (95% CI: 0.86–0.98), ACC 0.86 (95% CI: 0.79–0.92), SEN 0.80 (95% CI: 0.71–0.87), SPE 0.85 (95% CI: 0.80–0.89), and DOR 19.27 (95% CI: 10.27–36.17). Leave-one-out analyses confirmed robustness, and Egger’s tests indicated no significant publication bias. Conclusion ML-based models demonstrate excellent pooled diagnostic accuracy in predicting PA consistency preoperatively, underscoring their value for individualized surgical planning. Future multicenter studies with standardized imaging and external validation are needed to optimize clinical translation.

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.

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 mm 3 [95% CI 620–8828], were included. Greater tumor volume (χ 2  = 14.621, p  = 0.006) and male sex (χ 2  = 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% (χ 2  = 8.154, p  = 0.04), greater risk of developing postoperative hormone deficiencies (χ 2  = 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.

Pituitary adenomas, the most common type of lesion in the sellar region, rank third among all brain tumors, with an incidence of 73-94 cases per 100,000 individuals. Due to its high resolution, MRI is highly efficient in brain imaging and has emerged as the most appropriate method for tumor consistency evaluation. The present study aimed to assess the levels of collagen types I and III in pituitary adenomas with different consistencies and to determine the value of T2-weighted imaging (T2WI) MRI for predicting tumor consistency. A total of 55 patients with pituitary adenomas were divided into the soft and firm tumor groups according to intraoperative tumor consistency. The ratio of the tumor to Pons' signal intensities on T2WI scans was determined. A receiver operating characteristic curve was plotted to assess the specificity and sensitivity of T2WI in predicting tumor consistency. Average optical density (AOD) values for collagen types I (0.046±0.008 vs. 0.052±0.012, P=0.033) and III (0.044±0.008 vs. 0.050±0.010, P=0.016) were significantly lower in the soft tumor group compared with those in the firm tumor group. There was no significant difference in the ratio of the tumor to Pons' signal intensities on T2WI scans. The area under the ROC curve was 0.595±0.078 (P=0.250). The maximum tumor diameter significantly differed between the soft and firm tumor groups (P=0.001). AOD values for collagen types I and III were significantly correlated with the maximum tumor diameter (P<0.001). The amounts of collagen types I and III were elevated in firm pituitary tumors compared with the soft ones. The ratio of tumor to Pons' signal intensities on T2WI scans was not able to accurately predict tumor consistency. The size of pituitary adenomas may be associated with the expression levels of collagen types I and III.

Backgrounds Firm tumor consistency is one of the most important factors that impede sufficient removal of pituitary macroademoas via a transsphenoidal approach. The utility of diffusion-weighted (DW) magnetic resonance imaging (MRI) in predicting the tumor consistency and successfulness of transsphenoidal resection was evaluated in this study. Methods Thirty consecutive primary cases of nonfunctional pituitary macroadenomas were prospectively enrolled. Conventional and DW MRI were done for all the patients and the apparent diffusion coefficient (ADC) values and the signal intensity of the solid tumor were determined. Intraoperative report of tumor consistency, the degree of fibrosis and percentage of collagen content were documented. The 8 weeks postoperative MRI was used for calculation of the tumor resection rate. Results The tumor consistency was soft in 10 patients (33.3 %), intermediate in 14 patients (46.7 %) and hard in 6 patients (20 %). The mean collagen content percentage was 10, 23.5 and 66 % ( p  = 0.009) and the average resection rate was 75, 43 39 % in the three groups respectively ( p  = 0.001). The mean ADC value was not significantly correlated with the tumor consistency and resection rate. Tumors with isointense to hyperintense signal on DW MRI were more commonly removable by suction and had higher resection rates than those with hypointense signals ( p  = 0.019). For ADC values within the range of 600–740 × 10 -3  mm 2 /s, a residual volume larger than 20 % of the tumor was more likely. Conclusions DW MRI was useful to predict the tumor consistency, collagen content and the chance of removal of pituitary macroadenomas through endoscopic transsphenoidal surgery, and is recommended in the preoperative patient evaluation.

Background The consistency of meningiomas is critical to determine surgical planning and has a significant impact on surgical outcomes. Our aim was to compare mono-exponential, bi-exponential and stretched exponential MR diffusion-weighted imaging in predicting the consistency of meningiomas before surgery. Methods Forty-seven consecutive patients with pathologically confirmed meningiomas were prospectively enrolled in this study. Two senior neurosurgeons independently evaluated tumour consistency and classified them into soft and hard groups. A volume of interest was placed on the preoperative MR diffusion images to outline the whole tumour area. Histogram parameters (mean, median, 10th percentile, 90th percentile, kurtosis, skewness) were extracted from 6 different diffusion maps including ADC (DWI), D*, D, f (IVIM), alpha and DDC (SEM). Comparisons between two groups were made using Student’s t-Test or Mann-Whitney U test. Parameters with significant differences between the two groups were included for Receiver operating characteristic analysis. The DeLong test was used to compare AUCs. Results DDC, D* and ADC 10th percentile were significantly lower in hard tumours than in soft tumours (P ≤ 0.05). The alpha 90th percentile was significantly higher in hard tumours than in soft tumours (P < 0.02). For all histogram parameters, the alpha 90th percentile yielded the highest AUC of 0.88, with an accuracy of 85.10%. The D* 10th percentile had a relatively higher AUC value, followed by the DDC and ADC 10th percentile. The alpha 90th percentile had a significantly greater AUC value than the ADC 10th percentile (P ≤ 0.05). The D* 10th percentile had a significantly greater AUC value than the ADC 10th percentile and DDC 10th percentile (P ≤ 0.03). Conclusion Histogram parameters of Alpha and D* may serve as better imaging biomarkers to aid in predicting the consistency of meningioma.

Background Meningioma is a common neoplasm primarily arising in the central nervous system. Its consistency is considered to be one of the critical prognostic factors for determining surgical resectability. The present study endeavored to investigate predictive factors associated with the tumor consistency. Methods Two hundred and forty-three consecutive participants who underwent resective surgery of meningioma were examined. The authors designed an objective grading system for meningioma consistency and utilized it for assessing consistency among all cases. We focused on the relationship between preoperative tumor characteristics on neuroimaging studies and the consistency. Results The tumor attributes on T2-weighted image (T2WI) and fluid attenuated inversion recovery (FLAIR) image were significantly correlated with the tumor consistency ( p  = 0.004 and 0.045, respectively). The hypointense tumors on both MRI sequences tended to be hard, whereas the tumors showing hypersignal intensity were associated with soft consistency. There was no correlation between the consistency and age, gender, duration of neurologic symptoms, tumor location, size, calcification, cystic portion, en plague appearance, tumor-brain contact interface expressed by cerebrospinal fluid (CSF) cleft, perilesional vasogenic edema, bony status, features on T1-weighted image (T1WI) and pattern of contrast enhancement. In multiple logistic regression analysis, the tumor characteristics on T2WI and FLAIR image were independent factors significantly correlated with the tumor consistency ( p  = 0.005 and 0.041, respectively). The tumor consistency was also correlated with operative radicalness as evaluated by the Simpson criteria. Conclusions Signal intensity on T2WI and FLAIR image can be used for insinuating meningioma consistency. Presurgical prediction of the consistency is highly valuable in operative planning, particularly in arduous cases.