Comparison of growth hormone-producing and non-growth hormone-producing pituitary adenomas: imaging characteristics and pathologic correlation

Predictors of biochemical response to somatostatin receptor ligands in acromegaly

Although predictors of response to first-generation somatostatin receptor ligands (fg-SRLs), and to a lesser extent to pasireotide, have been studied in acromegaly for many years, their use is still not recommended in clinical guidelines. Is there insufficient evidence to use them? Numerous biomarkers including various clinical, functional, radiological and molecular markers have been identified. The first ones are applicable pre-surgery, while the molecular predictors are utilized for patients not cured after surgery. In this regard, factors predicting a good response to fg-SRLs are specifically: low basal GH, a low GH nadir in the acute octreotide test, T2 MRI hypointensity, a densely granulated pattern, high immunohistochemistry staining for somatostatin receptor 2 (SSTR2), and E-cadherin. However, there is still a lack of consensus regarding which of these biomarkers is more useful or how to integrate them into clinical practice. With classical statistical methods, it is complex to define reliable and generalizable cut-off values for a single biomarker. The potential solution to the limitations of traditional methods involves combining systems biology with artificial intelligence, which is currently providing answers to such long-standing questions that may eventually be finally included into the clinical guidelines and make personalized medicine a reality. The aim of this review is to describe the current knowledge of the main fg-SRLs and pasireotide response predictors, discuss their current usefulness, and point to future directions in the research of this field.

Analysis of MRI features and associated factors of the pituitary neuroendocrine tumor streaky sign

OBJECTIVES

Observation of pituitary neuroendocrine tumors with streaky sign on MRI, analysis of their features on imaging and further investigation of the relationship between the direction of the streak sign and the direction of optimal tumor expansion.

METHODS

The MR images of 237 patients with pituitary neuroendocrine tumors were retrospectively analyzed. The streaky-like high signal with a substantial length of more than 10 mm and obvious enhancement on T1WI was defined as the streaky sign. Finally, 66 patients were included in the study, comprising 33 patients with streaky sign pituitary neuroendocrine tumors and 33 randomly selected patients with non-streaky sign pituitary neuroendocrine tumors. The general condition of these 66 patients, the imaging features of the tumor, and the measurement and analysis of the direction of the streaky sign in relation to the direction of optimal tumor extension were observed and analyzed.

RESULTS

On MRI, 85 streaky signs were observed. The average deviation between the direction angle of all the streaky signs and the optimal extension direction angle of the tumor was approximately 11°. The longest streaky sign angle was positively correlated with the optimal extension angle of the tumor, with a correlation coefficient of 0.967.

CONCLUSION

The presence of a streaky sign of pituitary neuroendocrine tumors may indicate a dilated sinus or a small blood vessel. Its direction is highly consistent with the optimal extension direction of the tumor, which has a certain supporting effect on the long-distance growth of the tumor.

Newer parameters of the octreotide test in patients with acromegaly

PURPOSE

Predicting the therapeutic effects of first-generation somatostatin receptor ligands (fg-SRLs) is important when assessing or planning effective treatment strategies in patients with acromegaly. The oft-used maximum growth hormone (GH) suppression rate parameter of the octreotide test has a suboptimal predictive value. Therefore, this study explored newer parameters of the octreotide test for predicting the therapeutic effect of long-acting fg-SRLs.

METHODS

In this single-center retrospective study, the octreotide test parameters and the therapeutic effects of fg-SRL at 3 months were investigated in 45 consecutive treatment-naïve patients with acromegaly between April 2008 and March 2023. Additionally, the relationship between the octreotide test parameters and the therapeutic effects of fg-SRLs was investigated. Tumor shrinkage was evaluated based on changes in the longitudinal diameter of the macroadenomas. The area GH suppression rate-time under the curve (AUC) and the time to nadir GH level were calculated and compared with the maximum GH suppression rate.

RESULTS

The AUC estimated reductions in serum insulin-like growth factor I, and tumor shrinkage. The time to nadir GH level predicted tumor shrinkage more robustly than the maximum GH suppression rate in patients with macroadenoma.

CONCLUSION

The AUC and time to nadir GH level may potentially be newer parameters of the octreotide test for estimating the therapeutic effect of fg-SRLs.

Analysis of Diffusion-Weighted and T2-Weighted Imaging in the Prediction of Distinct Granulation Patterns of Somatotroph Adenomas

OBJECTIVE

The heterogeneity of the somatotroph adenomas, especially for sparsely granulated (SG) and densely granulated (DG) subtypes, has attracted great attention in identifying their imaging biomarker. The purpose of the current study was to compare the diagnostic performance of diffusion-weighted and T2-weighted magnetic resonance imaging (MRI) sequences for preoperatively distinguishing the granulation patterns of somatotroph adenomas.

METHODS

Thirty-two patients with a clinical diagnosis of somatotroph adenomas from October 2018 to March 2023 were included in this study. Coronal diffusion-weighted imaging (DWI) and T2-weighted MRI sequence data were collected from 3.0T MRI and compared between SG and DG groups. The immunohistochemistry was used to confirm the electron microscopy pathologic subtypes and Ki67 expression levels of somatotroph adenomas postoperatively.

RESULTS

Patients in the SG group had significantly higher signal intensity (SI) ratio of DWI (rDWI) (P < 0.001), lower SI ratio of apparent diffusion coefficient (rADC) (P < 0.001), and higher SI ratio of T2-weighted imaging (P = 0.011). The combined diagnosis index of rDWI and rADC had the highest diagnostic efficiency in predicting SG adenomas (sensitivity, 93.3%; specificity, 88.2%; P < 0.001). The rDWI and rADC values had positive and negative correlations with the Ki67 index and tumor maximum diameter, respectively. Lower rADC×103 was an independent predictor for SG adenomas.

CONCLUSIONS

Our results indicated that compared with previously used T2-weighted imaging, the DWI sequence, especially the combined diagnosis index of rDWI and rADC, could more efficiently distinguish the granulation patterns of somatotroph adenomas preoperatively.

Predictors of Response to Treatment with First-Generation Somatostatin Receptor Ligands in Patients with Acromegaly

BACKGROUND AND AIMS

Predictors of first-generation somatostatin receptor ligands (fgSRLs) response in acromegaly have been studied for over 30 years, but they are still not recommended in clinical guidelines. Is there not enough evidence to support their use? This systematic review aims to describe the current knowledge of the main predictors of fgSRLs response and discuss their current usefulness, as well as future research directions.

METHODS

A systematic search was performed in the Scopus and PubMed databases for functional, imaging, and molecular predictive factors.

RESULTS

A total of 282 articles were detected, of which 64 were included. Most of them are retrospective studies performed between 1990 and 2023 focused on the predictive response to fgSRLs in acromegaly. The usefulness of the predictive factors is confirmed, with good response identified by the most replicated factors, specifically low GH nadir in the acute octreotide test, T2 MRI hypointensity, high Somatostatin receptor 2 (SSTR2) and E-cadherin expression, and a densely granulated pattern. Even if these biomarkers are interrelated, the association is quite heterogeneous. With classical statistical methods, it is complex to define reliable and generalizable cut-off values worth recommending in clinical guidelines. Machine-learning models involving omics are a promising approach to achieve the highest accuracy values to date.

CONCLUSIONS

This survey confirms a sufficiently robust level of evidence to apply knowledge of predictive factors for greater efficiency in the treatment decision process. The irruption of artificial intelligence in this field is providing definitive answers to such long-standing questions that may change clinical guidelines and make personalized medicine a reality.

Clinical Significance of T2-Weighted Sequence Intensity on Magnetic Resonance Imaging in Clinically Non-Functioning Pituitary Adenomas

BACKGROUND

Little is known about the relationship between signal intensity patterns on T2-weighted magnetic resonance imaging (MRI) in non-functioning pituitary adenomas (NFPAs).

OBJECTIVE

In this study, the clinical, hormonal, histological features, and therapeutic responses were evaluated according to the T2 signal intensity in NFPAs.

METHODS

This retrospective and multicenter study included a group of 166 NFPA patients (93 men, 56%, mean age 58.5 ±14.8 yr).

RESULTS

Approximately half of the tumors (n=84, 50.6%) were hyperintense, while 34.3% (n=57) and 15.1% (n=25) were iso- and hypointense, respectively. The median maximum tumor diameter of the isointense group [16 (13-25) mm] was significantly lower than that of the hyperintense [23 (16.6-29.7) mm] group (p=0.003). Similarly, the tumor volume of the isointense group [1,523 (618-5,226) mm3] was significantly lower than that of the hyperintense [4,012 (2,506-8,320) mm3] group (p=0.002). Chiasmatic compression occurred less frequently in tumors with isointense signal characteristics (38.6%) compared to tumors with hypointense (68%) and hyperintense (65.5%) signal characteristics (p=0.003). Invasive adenomas (p=0.001) and the degree of cavernous sinus invasion (p<0.001) were more frequent in the hyperintense adenoma group compared to the remaining groups. Plurihormonal tumors and silent lactotroph adenomas were more frequent in the isointense tumor group.

CONCLUSION

In conclusion, hyperintensity on T2-weighted MRI in NFPAs is associated with larger and more invasive tumors compared to isointense NFPAs.

Magnetic resonance imaging as a predictor of therapeutic response to pasireotide in acromegaly

OBJECTIVE

Hyperintensity signal in T2-weighted magnetic resonance imaging (MRI) has been related to better therapeutic response during pasireotide treatment in acromegaly. The aim of the study was to evaluate T2 MRI signal intensity and its relation with pasireotide therapeutic effectiveness in real-life clinical practice.

DESIGN, PATIENTS AND MEASUREMENTS

Retrospective multicentre study including acromegaly patients treated with pasireotide. Adenoma T2-weighted MRI signal at diagnosis was qualitatively classified as iso-hyperintense or hypointense. Insulin-like growth factor (IGF-I), growth hormone (GH) and tumour volume reduction were assessed after 6 and 12 months of treatment and its effectiveness evaluated according to baseline MRI signal. Hormonal response was considered 'complete' when normalization of IGF-I levels was achieved. Significant tumour shrinkage was defined as a volume reduction of ≥25% from baseline.

RESULTS

Eighty-one patients were included (48% women, 50 ± 1.5 years); 93% had previously received somatostatin receptor ligands (SRLs) treatment. MRI signal was hypointense in 25 (31%) and hyperintense in 56 (69%) cases. At 12 months of follow-up, 42/73 cases (58%) showed normalization of IGF-I and 37% both GH and IGF-I. MRI signal intensity was not associated with hormonal control. 19/51 cases (37%) presented a significant tumour volume shrinkage, 16 (41%) from the hyperintense group and 3 (25%) from the hypointense.

CONCLUSIONS

T2-signal hyperintensity was more frequently observed in pasireotide treated patients. Almost 60% of SRLs resistant patients showed a complete normalization of IGF-I after 1 year of pasireotide treatment, regardless of the MRI signal. There was also no difference in the percentage tumour shrinkage over basal residual volume between the two groups.

Prolactin and Growth Hormone Signaling and Interlink Focused on the Mammosomatotroph Paradigm: A Comprehensive Review of the Literature

Prolactin (PRL) and growth hormone (GH) are peptide hormones that bind to the class 1 cytokine receptor superfamily, a highly conserved cell surface class of receptors. Both hormones control their own secretion via a negative autocrine loop in their own mammosomatotroph, lactotroph or somatotroph. In this regard, GH and PRL are regulated by similar signaling pathways involving cell growth and hormone secretion. Thus, GH and PRL dysregulation and pituitary neuroendocrine tumor (PitNET) development may have common pathogenic pathways. Based on cell linage, lactotroph and somatotroph PitNETs come from pituitary-specific POU-class homeodomain transcription factor (Pit-1). Mammosomatotroph and plurihormonal PitNETs are a unique subtype of PitNETs that arise from a single-cell population of Pit-1 lineage. In contrast, mixed somatotroph-lactotroph PitNETs are composed of two distinct cell populations: somatotrophs and lactotrophs. Morphologic features that distinguish indolent PitNETs from locally aggressive ones are still unidentified, and no single prognostic parameter can predict tumor aggressiveness or treatment response. In this review, we aim to explore the latest research on lactotroph and somatotroph PitNETs, the molecular mechanisms involved in PRL and GH axis regulation and the signaling pathways involved in their aggressiveness, particularly focused on mammosomatotroph and mixed subtypes. Finally, we summarize epidemiological, clinical, and radiological features of these exceptional tumors. We aim to shed light, from basic to clinical settings, on new perspectives and scientific gaps in this field.

Analysis of risk factors of pituitary neoplasms invading the sphenoidal sinus

High-resolution computed tomography (HR-CT) can more effectively discern the relationship between pituitary neoplasms (PNs) and neighboring anatomical structures. Moreover, pathological features can facilitate a more accurate determination of the growth pattern of PNs. Consequently, integrating imaging and pathological data might enhance our predictive capability regarding the growth patterns of PNs and aid in the formulation of surgical plans. We compared HR-CT images of 54 patients and 52 volunteers. Using ITK-SNAP software, we segmented and reconstructed the anatomical features of the sphenoidal sinus (SS) and calculated its volume. A comparative analysis of the invasive attributes of the 54 PNs was carried out based on clinical features and pathological data. The average volume of the SS in the volunteer group was 11.05 (8.10) mL, significantly larger than that of the PNs group at 7.45 (4.88) mL (P = .005). The postsellar type was the most common pneumatization type, and a significantly higher proportion in the PNs group exhibited a depressed saddle base (83.3%). A notable male predominance was observed for SS invasion in the PNs group (72.7%), with the Ki-67 antigen and maximum diameter significantly higher (P < .05), showing a positive correlation. The optimal cutoff points for Ki-67 antigen and the maximum diameter of PNs were 3.25% (AUC = 0.754, Sensitivity 54.5%, Specificity 90.6%) and 24.5 mm (AUC = 0.854, Sensitivity 86.4%, Specificity 78.1%), respectively. The type of pneumatization and the morphology of the sellar-floor serve as anatomical foundations for SS invasion. Factors such as the Ki-67 antigen, the maximum diameter of PNs, and high-risk sub-types constitute risk factors for PNs invasion into the SS. These insights are of significant utility for clinicians in crafting treatment strategies for PNs.

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.

The Significance of the Intercarotid Distances for Transsphenoidal Pituitary Surgery: A Magnetic Resonance Imaging Study

OBJECTIVE

We performed magnetic resonance imaging (MRI) to analyze the distance between the left and right internal carotid arteries (ICD) around pituitary tumors for transsphenoidal surgery (TSS).

METHODS

Measurements were performed using thin slice T2-weighted MRI, and/or time-of-flight (TOI) MR angiography imaging for 64 nonfunctioning pituitary neuroendocrine tumors (NF-pitNETs), 22 growth hormone-producing pitNETs (GH producing pitNETs), and 46 normal controls. We measured the ICD at 3 anatomic levels: at the distal dural ring (ICD-A); at the most concave point of the C4-C5 bend (ICD-B); and at the most convex point of the C4 bend (ICD-C). Additionally, we measured the sagittal distance between the tuberculum selle and the junction of the sellar floor and clivus on the midsagittal MRI (TS-C).

RESULTS

We found that ICD-B was the longest and that ICD-A was the shortest among the 3 distance parameters in all groups (P < 0.001). The comparison of the groups revealed that the NF-pitNET group had longer distances than the normal control group at all ICDs (P < 0.001). The GH producing pitNET group had longer distance than the normal control group at ICD-B (P < 0.001). Tumor volume was correlated with ICD-A and ICD-B in the NF-pitNET, and was correlated with ICD-C in the GH producing pitNET group.

CONCLUSIONS

Among the distance parameters, ICD-B is the longest, and was approximately twice the width of the TS-C. The shape of the sella is an ellipse that is widest in the lateral dimension in TSS. A horizontal based dural incision may be more rational than a conventional X-shaped dural incision.

Survivin: A Potential Marker of Resistance to Somatostatin Receptor Ligands

CONTEXT

Invasive and somatostatin receptor ligand (SRL)-resistant pituitary tumors represent a challenge in the clinical practice of endocrinologists. Efforts have been made to elucidate reliable makers for both. Survivin and eukaryotic translation initiation factor-binding protein 1 (4EBP1) are upregulated in several cancers and involved in apoptosis and cell proliferation.

OBJECTIVE

We explored the role of these markers in somatotropinomas.

METHODS

Immunostains for survivin and 4EBP1, and also for somatostatin receptor type 2 (SSTR2), Ki-67, and cytokeratin 18, were analyzed in tissue microarrays containing 52 somatotropinoma samples. Tumor invasiveness was evaluated in all samples while drug resistance was evaluated in 34 patients who received SRL treatment. All these parameters were correlated with first-generation SRL (fg-SRL) responsiveness and tumor invasiveness.

RESULTS

Low survivin expression (P = 0.04), hyperintense signal on T2 weighted image (T2WI) (P = 0.01), younger age (P = 0.01), sparsely granular adenomas (SGA) (P = 0.04), high postoperative growth hormone (GH) and insulin-like growth factor-1 (IGF-1) levels (P = 0.049 and P < 0.001, respectively), and large postoperative tumor size (P = 0.02) were associated with resistance to fg-SRL. Low survivin and SSTR2 expression and high 4EBP1 expression were associated with SGA (P = 0.04, P = 0.01, and P = 0.001, respectively). Younger age (P = 0.03), large tumor pre- and postoperative (P = 0.04 and P = 0.006, respectively), low SSTR2 expression (P = 0.03), and high baseline GH and IGF-1 (P = 0.01 and P = 0.02, respectively) were associated with tumor invasiveness. However, survivin, 4EBP1, Ki-67, and granulation patterns were not associated with tumor invasion.

CONCLUSION

This study suggests that low survivin expression is predictive of resistance to fg-SRL in somatotropinomas, but not of tumor invasiveness.

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.

Multidisciplinary management of difficult/aggressive growth-hormone pituitary neuro-endocrine tumors

Growth Hormone-secreting adenomas exhibits variable biological behavior and heterogeneous natural history, ranging from small adenomas and mild disease, to invasive and aggressive neoplasms with more severe clinical picture. Patients not cured or controlled after neurosurgical and first-generation somatostatin receptor ligands (SRL) therapy could require multiple surgical, medical and/or radiation treatments to achieve disease control. To date, no clinical, laboratory, histopathological, or neuroradiological markers are able to define the aggressiveness or predict the disease prognosis in patients with acromegaly. Therefore, the management of these patients requires careful evaluation of laboratory assessments, diagnostic criteria, neuroradiology examinations, and neurosurgical approaches to choose an effective and patient-tailored medical therapy. A multidisciplinary approach is particularly useful in difficult/aggressive acromegaly to schedule multimodal treatment, which includes radiation therapy, chemotherapy with temozolomide and other, recent emerging treatments. Herein, we describe the role of the different members of the multidisciplinary team according to our personal experience; a flow-chart for the therapeutic approach of difficult/aggressive acromegaly patients is proposed.

Age, GH/IGF-1 levels, tumor volume, T2 hypointensity, and tumor subtype rather than proliferation and invasion are all reliable predictors of biochemical response to somatostatin analogue therapy in patients with acromegaly: A clinicopathological study

PURPOSE

To determine whether biochemical responses to long-acting forms of first-generation somatostatin analogue (SSA) therapy in patients with acromegaly could be predicted from baseline and postoperative hormone concentrations, and tumor radiological and histopathological characteristics.

METHODS

A total of 68 patients with acromegaly for whom postoperative SSA therapy was started were categorized according to their responses to treatment (SSA-responders vs. non-responders). The patients were compared based on their demographic characteristics, hormone levels, magnetic resonance imaging (MRI), and histopathological findings. Receiver-operating-characteristic (ROC) curves were constructed using the predictive factors that were significant in the univariate analysis to determinate the optimal cut-off values.

RESULTS

The SSA-responders were significantly older (p = 0.041). Lower GH at diagnosis (p = 0.036), the postoperative 1st-week GH level (p = 0.027), baseline GH, insulin-like growth factor-1 (IGF-1) and IGF-1% upper limit of normal (ULN) (p = 0.001, p = 0.006, p = 0.023, respectively) were associated with biochemical response. T2-hypointensity and lower tumor volume were more common in the SSA-responders (p = 0.018, p = 0.03, respectively). Compared to sparsely granulated somatotroph tumors, densely granulated somatotroph tumors and other PitNETs causing GH excess including mammosomatotroph and mixed somatotroph and lactotroph tumors were more likely to respond to SSA therapy (p = 0.026, p = 0.03, respectively). The cut-off values generated by ROC curve analysis were GH at diagnosis of ≤8.8 ng/mL, GH at baseline of ≤2.69 ng/mL, IGF-1 at baseline ≤461.5 ng/mL, IGF-1% ULN at baseline ≤180.4%, and tumor volume of ≤1.11 cm³ (all p < 0.05). There were no differences between the groups in terms of tumor invasiveness, proliferative activity (mitotic count per 2 mm² and Ki-67 labeling index) and quantitative analyses of T2-weighted MRI.

CONCLUSION

This study underscores that advanced age, low baseline GH and IGF-1 at diagnosis, low tumor volume, densely granulated tumor subtype, and T2 hypointensity may help predict biochemical response to SSA therapy in cases of acromegaly. These variables should be assessed with utmost attention for all patients prior to SSA treatment. In cases of possible resistance to SSA therapy, therapeutic activity should be monitored more closely and other therapies should be administered immediately in the event of poor response.

Predictive Factors of Somatostatin Receptor Ligand Response in Acromegaly-A Prospective Study

CONTEXT

Somatostatin receptor ligands (SRLs) are the cornerstone medical treatments for acromegaly; however, many patients remain unresponsive to SRLs. Well-established predictive markers of response are needed.

OBJECTIVE

We aimed to explore the relationship between responsiveness to SRLs relative to somatostatin (SST)2A and 5 receptor expression, adenoma granularity, and T2-weighted magnetic resonance imaging (MRI) signal intensity (T2WSI).

METHODS

We conducted a multicentric, prospective, observational cohort study, in France. Forty-nine naïve patients (ie, patients without preoperative SRL treatment) with active acromegaly following surgery were treated with octreotide (group 1; n = 47), or pasireotide if uncontrolled under first-generation SRLs (group 2; n = 9). Data were collected at baseline and months 3 and 6. Biochemical measurements, immunohistochemistry studies, and MRI readings were centralized.

RESULTS

In group 1, IGF-I decrease from baseline to month 6 positively correlated with SST2A immunoreactive score (IRS), P = 0.01. Densely granulated/intermediate adenomas had a greater IGF-I and GH decrease under octreotide compared with sparsely granulated adenomas (P = 0.02 and P = 0.006, respectively), and expressed greater levels of SST2A (P < 0.001), coupled with lower levels of SST5 (P = 0.004). T2WSI changed between preoperative MRI and month 6 MRI in one-half of the patients. Finally, SST5 IRS was higher in preoperative hyperintense compared with preoperative hypointense adenomas (P = 0.04), and most sparsely granulated and most hyperintense adenomas expressed high SST5 levels.

CONCLUSION

We prospectively confirm that SST2A and adenoma granularity are good predictors of response to octreotide. We propose the IRS for scoring system harmonization. MRI sequences must be optimized to be able to use the T2WSI as a predictor of treatment response.

Recommendations for the diagnosis and radiological follow-up of pituitary neuroendocrine tumours

Pituitary neuroendocrine tumours (PitNETs) constitute a heterogeneous group of tumours with a gradually increasing incidence, partly accounted for by more sensitive imaging techniques and more extensive experience in neuroradiology in this regard. Although most PitNETs are indolent, some exhibit aggressive behaviour, and recurrence may be seen after surgical removal. The changes introduced in the WHO classification in 2017 and terminological debates in relation to neuroendocrine tumours warrant an update of the guidelines for the diagnosis, preoperative and postoperative management, and follow-up of response to treatment of PitNETs. This multidisciplinary document, an initiative of the Neuroendocrinology area of the Sociedad Española de Endocrinología y Nutrición [Spanish Society of Endocrinology and Nutrition] (SEEN), focuses on neuroimaging studies for the diagnosis, prognosis and follow-up of PitNETs. The basic requirements and elements that should be covered by magnetic resonance imaging are described, and a minimum radiology report to aid clinicians in treatment decision-making is proposed. This work supplements the consensus between the Neuroendocrinology area of the SEEN and the Sociedad Española de Anatomía Patológica [Spanish Society of Pathology] (SEAP) for the pathological study of PitNETs.

A current perspective of pituitary adenoma MRI characteristics: a review

INTRODUCTION

MR imaging is an essential and fundamental tool in the diagnosis, management, and follow-up of patients with pituitary adenomas (PAs). Recent advances have continued to enhance the usefulness of this imaging modality.

AREAS COVERED

This article focuses on signal intensity patterns of PAs and associated clinical characteristics, vertical extension patterns, and cavernous sinus invasion with a special focus on the clinical implications that arise. A search using Medline and Google Scholar was conducted using different combinations of relevant keywords, giving preference to recent publications.

EXPERT OPINION

A higher proportion of GH-secreting PAs are hypointense on T2 weighted images compared to other tumor subtypes. Hypointense tumors are generally smaller compared to hyperintense ones, and among the GH-secreting subgroup, a better response to somatostatin analogue treatment was noted together with an association for a densely granulated pattern. Nonfunctional PAs show a predilection to extend upwards while GH-secreting PAs and prolactinomas show a predominantly inferior extension growth pattern. Further studies to better understand the mechanisms responsible for this behavior are anticipated. Further development, refining and validation of predictive scoring systems for tumor behavior might be useful adjuncts in the management of patients with PAs.

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.

Pituitary MRI Features in Acromegaly Resulting From Ectopic GHRH Secretion From a Neuroendocrine Tumor: Analysis of 30 Cases

CONTEXT

Ectopic acromegaly is a consequence of rare neuroendocrine tumors (NETs) that secrete GHRH. This abnormal GHRH secretion drives GH and IGF-1 excess, with a clinical presentation similar to classical pituitary acromegaly. Identifying the underlying cause for the GH hypersecretion in the setting of ectopic GHRH excess is, however, essential for proper management both of acromegaly and the NET. Owing to the rarity of NETs, the imaging characteristics of the pituitary in ectopic acromegaly have not been analyzed in depth in a large series.

OBJECTIVE

Characterize pituitary magnetic resonance imaging (MRI) features at baseline and after NET treatment in patients with ectopic acromegaly.

DESIGN

Multicenter, international, retrospective.

SETTING

Tertiary referral pituitary centers.

PATIENTS

Thirty ectopic acromegaly patients having GHRH hypersecretion.

INTERVENTION

None.

MAIN OUTCOME MEASURE

MRI characteristics of pituitary gland, particularly T2-weighted signal.

RESULTS

In 30 patients with ectopic GHRH-induced acromegaly, we found that most patients had hyperplastic pituitaries. Hyperplasia was usually moderate but was occasionally subtle, with only small volume increases compared with normal ranges for age and sex. T2-weighted signal was hypointense in most patients, especially in those with hyperplastic pituitaries. After treatment of the NET, pituitary size diminished and T2-weighted signal tended to normalize.

CONCLUSIONS

This comprehensive study of pituitary MRI characteristics in ectopic acromegaly underlines the utility of performing T2-weighted sequences in the MRI evaluation of patients with acromegaly as an additional tool that can help to establish the correct diagnosis.

Efficacy of lanreotide 120 mg primary therapy on tumour shrinkage and ophthalmologic symptoms in acromegaly after 1 month

INTRODUCTION

Few studies have attempted to evaluate the early efficacy of first-generation somatostatin analogues in somatotroph macroadenomas.

OBJECTIVE

To investigate the short-term efficacy of primary therapy with lanreotide 120 mg at 1 and 3 months on tumour shrinkage and ophthalmologic symptoms in newly diagnosed patients with acromegaly.

DESIGN AND PATIENTS

This single-centre retrospective study included 21 patients with de novo acromegaly resulting from pituitary macroadenoma, with optic chiasm compression (Grade ≤ 2) and/or cavernous sinus invasion, treated with a monthly injection of lanreotide 120 mg. Clinical, hormonal, ophthalmologic and magnetic resonance imaging scan evaluations were conducted after the first and the third months of treatment.

RESULTS

Tumour volume reduction was more pronounced at 1 month; mean volume change: -31.4 ± 19.5%, p < .0001 than between the first and third month of treatment; mean volume reduction: -20.6 ± 13.4%, p = .0009. The mean volume change between baseline and the third month was - 46.4 ± 21.6, (p < .0001). A significant volume reduction (≥25%) was observed in 61.9% of individuals (13/21) at the first month. Among 14 individuals with optic chiasm compression and visual field defects, visual field normalization or improvement were observed in seven cases (50%), stabilization in four cases (28.5%), and mild worsening in three cases (21.4%) at 1 month. The decrease in growth hormone and IGF-1 serum values was significant at 1 month.

CONCLUSIONS

Primary treatment with lanreotide 120 mg in patients with somatotroph macroadenomas provides early significant tumour shrinkage with rapid improvement of visual symptoms at the end of the first month in 50% of patients.

Growth hormone secreting pituitary adenomas show distinct extrasellar extension patterns compared to nonfunctional pituitary adenomas

PURPOSE

Patterns of extension of pituitary adenomas (PA) may vary according to PA subtype. Understanding extrasellar extension patterns in growth hormone PAs (GHPA) vis-a-vis nonfunctional PAs (NFPAs) may provide insights into the biology of GHPA and future treatment avenues.

METHODS

Preoperative MR imaging (MRI) in 179 consecutive patients treated surgically for NFPA (n = 139) and GHPA (n = 40) were analyzed to determine patterns of extrasellar growth. Extension was divided into two principal directions: cranio-caudal (measured by infrasellar/suprasellar extension), and lateral cavernous sinus invasion (CSI) determined by Knosp grading score of 3-4. Suprasellar extension was defined as tumor extension superior to the tuberculum sellae- dorsum sellae line, and inferior extension as invasion through the sellar floor into the sphenoid sinus or clivus. Categorical analysis was performed using Fisher's exact test.

RESULTS

GHPAs were overall more likely to remain purely intrasellar compared to NFPA (50% vs 26%, p < 0.001). GHPAs, however, were 7 times more likely to exhibit isolated infrasellar extension compared to NFPA (20% vs 2.8%, p = 0.001). Conversely, NFPAs were twice as likely to exhibit isolated suprasellar extension compared to GHPA (60% vs 28%, p < 0.001), as well as combined suprasellar/infrasellar extension (25% vs 3%, p = 0.011). There were no overall differences in CSI between the two subgroups.

DISCUSSION

GHPA and NFPA demonstrate distinct extrasellar extension patterns on MRI. GHPAs show proclivity for inferior extension with bony invasion, whereas NFPAs are more likely to exhibit suprasellar extension through the diaphragmatic aperture. These distinctions may have implications into the biology and future treatment of PAs.

Italian Association of Clinical Endocrinologists (AME) and International Chapter of Clinical Endocrinology (ICCE). Position statement for clinical practice: prolactin-secreting tumors

Prolactinomas are the most frequent pituitary adenomas. Prolactinoma may occur in different clinical settings and always require an individually tailored approach. This is the reason why a panel of Italian neuroendocrine experts was charged with the task to provide indications for the diagnostic and therapeutic approaches that can be easily applied in different contexts. The document provides 15 recommendations for diagnosis and 54 recommendations for treatment, issued according to the GRADE system. The level of agreement among panel members was formally evaluated by RAND-UCLA methodology. In the last century, prolactinomas represented the paradigm of pituitary tumors for which the development of highly effective drugs obtained the best results, allowing to avoid neurosurgery in most cases. The impressive improvement of neurosurgical endoscopic techniques allows a far better definition of the tumoral tissue during surgery and the remission of endocrine symptoms in many patients with pituitary tumors. Consequently, this refinement of neurosurgery is changing the therapeutic strategy in prolactinomas, allowing the definitive cure of some patients with permanent discontinuation of medical therapy.

Quantitative Magnetic Resonance-Derived Biomarkers as Predictors of Function and Histotype in Adenohypophyseal Tumours

INTRODUCTION

Magnetic resonance imaging (MRI) is the main modality to diagnose adenohypophyseal tumours, while biochemical assessment of pituitary hormones allows for their functional classification. In this retrospective exploratory cohort study, we investigated if quantitative differences in tumour MR signal intensity (SI) could be utilized to predict the function and histotype.

METHODS

Clinically acquired pretreatment MRI images were retrospectively analysed in 67 clinically non-functioning gonadotropinomas (NFG), 38 somatotropinomas, and 16 medically treated giant macroprolactinomas. Mean T1- and T2-weighted SI values were determined for each tumour and normalized against either centrum semiovale white matter or CSF to derive relative T1W and T2W SI values and the relative tumour T2/T1 SI ratio. Inter-group differences in quantitative MR parameters were compared, and the power of each parameter to discriminate tumour type and subtype was assessed using the area under the receiver operator characteristic curve (AUROC). In resected somatotropinomas, the relationship between tumour granulation status, relative MR SI values, and biochemical data was also compared.

RESULTS

Compared to somatotropinomas, NFG and macroprolactinomas displayed higher relative T2W SI (p < 0.001) and higher relative tumour T2/T1 SI ratio values (p < 0.001, ANOVA). Compared to intermediate/densely granulated tumours, sparsely granulated somatotropinomas were larger (p = 0.006, Mann-Whitney U test), had higher relative T2W SI (p ≤ 0.005), and higher relative tumour T2/T1 SI ratios (p ≤ 0.001, 2-tailed t test). Relative tumour T2W SI values and relative tumour T2/T1 ratio values demonstrated good discriminatory power in differentiating NFG from somatotropinoma (AUROC = 0.87-0.94) and predicting somatotropinoma subtypes (AUROC = 0.87-0.95).

CONCLUSION

Quantitative SI-based MR parameters derived using clinical acquisition MRI protocols may help non-invasively discriminate the functional status of adenohypophyseal tumours and the histological subtype of somatotropinomas.

Clinical, hormonal and pathomorphological markers of somatotroph pituitary neuroendocrine tumors predicting the treatment outcome in acromegaly

BACKGROUND

Transsphenoidal adenomectomy (TSS) of somatotroph pituitary neuroendocrine tumor (PitNET) is the first-line treatment of acromegaly. Pharmacological treatment is recommended if surgery is contraindicated or did not lead to disease remission. The choice of treatment best fitting each patient should be based on thorough investigation of patients' characteristics. The current analysis attempts to create a tool for personalized treatment planning.

AIM

This study aimed to assess whether clinical, biochemical, imaging and pathological characteristics can predict surgical remission and response to first-generation somatostatin receptor ligands (SRLs) and pasireotide-LAR in acromegaly.

PATIENTS AND METHODS

A retrospective study of 153 acromegaly patients, treated in the Department of Endocrinology in Bielanski Hospital in Warsaw, Poland was performed. Data on demographics, hormonal and imaging results, pathological evaluation, and treatment outcome was extracted from the Polish Acromegaly Registry collecting information from 11 endocrinology centers in Poland and analyzed.

RESULTS

Patients with surgical remission had lower GH and IGF-1 concentrations at diagnosis (median GH 5.5 µg/L [IQR: 3.1-16.0] vs. 19.9 µg/L [IQR: 9.8-42.4], p=<0.001 and mean IGF-1 3.1xULN ± SD=1.2 vs. 3.7xULN ± SD=1.2, p=0.007, respectively) and smaller tumors (median 12.5mm [IQR: 9-19] vs. 23mm [IQR: 18-30], p<0.001). These tumors were more often densely granulated (DG) (73.2% vs. 40.0%, p=0.001) with positive staining for alpha-subunit (α-SU) (58.3% vs. 35.5%, p=0.021) and lower Ki-67 index (p=0.002). Patients responding well to SRLs were more often male (55.6% vs 44.4%, p=0.026), presented lower GH concentration (median GH 17.2 µg/L [IQR: 6.2-29.0] vs. 23.8 µg/L [IQR: 11.2-49.5], p=0.048) and had more often DG tumors (63.0% vs. 14.3%, p<0.001). No significant differences between good and poor-response to pasireotide-LAR groups were found. In multivariate logistic regression analysis fasting GH concentration <8.63 µg/L, maximal tumor diameter <15.5mm, normoprolactinemia and DG tumor turned out to be independent predictors of surgical remission (OR=0.92, p=0.026; OR=0.87, p=0.069, OR=3.86, p=0.096 and OR=3.05, p=0.181, respectively). Fasting GH concentration <36.6 µg/L and DG tumor turned out to be independent predictors of good response to first-generation SRLs (OR=0.96, p=0.06 and OR=10.68, p=0.002, respectively).

CONCLUSIONS

Younger age at diagnosis, male sex, lower GH, IGF-1 and PRL concentrations, smaller tumor size at diagnosis as well as positive α-SU staining, lower Ki-67 index and DG tumors predicted better treatment outcome in acromegaly patients.

Predicting Subtype of Growth Hormone Pituitary Adenoma based on Magnetic Resonance Imaging Characteristics

Supplemental digital content is available in the text.

This study aimed to investigate the value of magnetic resonance (MR) characteristics in differentiating the subtypes of growth hormone pituitary adenomas.

Imaging of Sella and Parasellar Region

The sellar and parasellar region is complex, with a unique meningeal, neural, vascular, and bony anatomy. Understanding the imaging anatomy is critical for accurate imaging interpretation. resonance (MR) imaging is the primary modality for pituitary imaging, whereas computed tomography may be used when MR imaging is contraindicated, and provides complementary bony anatomic information. This article reviews embryology and anatomy of the sellar and parasellar region. Imaging appearances of pituitary adenomas, Rathke cleft cysts, meningiomas, craniopharyngiomas, arachnoid cysts, vascular disorders, infectious abnormalities, and pituitary apoplexy are discussed and illustrated.

Consistency of pituitary adenomas: Amounts of collagen types I and III and the predictive value of T2WI MRI

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.

Tumor volume improves preoperative differentiation of prolactinomas and nonfunctioning pituitary adenomas

PURPOSE

Both prolactinomas and nonfunctioning adenomas (NFAs) can present with hyperprolactinemia. Distinguishing them is critical because prolactinomas are effectively managed with dopamine agonists, whereas compressive NFAs are treated surgically. Current guidelines rely only on serum prolactin (PRL) levels, which are neither sensitive nor specific enough. Recent studies suggest that accounting for tumor volume may improve diagnosis. The objective of this study is to investigate the diagnostic utility of PRL, tumor volume, and imaging features in differentiating prolactinoma and NFA.

METHODS

Adult patients with pathologically confirmed prolactinoma (n = 21) or NFA with hyperprolactinemia (n = 58) between 2013 and 2020 were retrospectively identified. Diagnostic performance of clinical and imaging variables was analyzed using receiver-operating characteristic curves to calculate area under the curve (AUC).

RESULTS

Tumor volume and PRL positively correlated for prolactinoma (r = 0.4839, p = 0.0263) but not for NFA (r = 0.0421, p = 0.7536). PRL distinguished prolactinomas from NFAs with an AUC of 0.8892 (p < 0.0001) and optimal cut-off value of 62.45 ng/ml, yielding a sensitivity of 85.71% and specificity of 94.83%. The ratio of PRL to tumor volume had an AUC of 0.9647 (p < 0.0001) and optimal cut-off value of 21.62 (ng/ml)/cm³ with sensitivity of 100% and specificity of 82.76%. Binary logistic regression found that PRL was a significant positive predictor of prolactinoma diagnosis, whereas tumor volume, presence of cavernous sinus invasion, and T2 hyperintensity were significant negative predictors. The regression model had an AUC of 0.9915 (p < 0.0001).

CONCLUSIONS

Consideration of tumor volume improves differentiation between prolactinomas and NFAs, which in turn leads to effective management.

Patterns of extrasellar invasive growth of pituitary adenomas with normal sellar cavity size

BACKGROUND

Pituitary adenomas (PAs) are among the most common brain tumors which characteristically become symptomatic due to the mass effect on surrounding structures and/or hormonal imbalances. This study describes 28 cases of PAs with an extrasellar invasive growth (EIG) at the early stage of tumor growth with normal sellar cavity size.

METHODS

1200 cases of PAs either treated medically or via Endoscopic transsphenoidal surgery were reviewed during a 10-year period. Pre-operative imaging was analyzed to evaluate the tumor expansion pattern, tumor invasion sites and other relevant tumor properties. A comprehensive preoperative endocrinological along with postoperative histopathological studies were conducted to evaluate the subjects' homeostasis and further identify the lesions characteristics.

RESULTS

Of the 28 patients, patients 19, 2, 1 and 6 had a growth hormone (GH)-secreting PA, an adrenocorticotropic hormone (ACTH)-secreting PA, a nonfunctional PA (NFPA) and a mix-hormones secreting PA, respectively. There was a statistically significant difference between patients with and without EIG regarding types of PAs (P = 0.000). Post-hoc tests demonstrated that GH-secreting PAs (P = 0.0003) and mix-hormones secreting PAs (P = 0.0000) are significantly more invasive, while NFPAs (P = 0.0000) are less invasive. There was not a statistically significant difference between the invasion sites and different types of PAs (P = 0.122).

CONCLUSION

Among different histological subtypes of PAs, GH-secreting PAs revealed a remarkable tendency for EIG with normal sellar cavity size. The extra-sellar tumor extension with a normal sella did not correlate with atypical histology. Considering EIG patterns, surgeons should be vigilant to investigate and follow the tumor spreading to its enclosing boundary during surgery, the clival part of sphenoid bone should be more exposed, and both inferomedial and lateral borders of the sphenoid sinus should be carefully explored in order to remove the tumor.

MR-Based Radiomics for Differential Diagnosis between Cystic Pituitary Adenoma and Rathke Cleft Cyst

Background

It is often tricky to differentiate cystic pituitary adenoma from Rathke cleft cyst with visual inspection because of similar MRI presentations between them. We aimed to design an MR-based radiomics model for improving differential diagnosis between them.

Methods

Conventional diagnostic MRI data (T1-,T2-, and postcontrast T1-weighted MR images) were obtained from 215 pathologically confirmed patients (105 cases with cystic pituitary adenoma and the other 110 cases with Rathke cleft cyst) and were divided into training (n = 172) and test sets (n = 43). MRI radiomics features were extracted from the imaging data, and semantic imaging features (n = 15) were visually estimated by two radiologists. Four classifiers were used to construct radiomics models through 5-fold crossvalidation after feature selection with least absolute shrinkage and selection operator. An integrated model by combining radiomics and semantic features was further constructed. The diagnostic performance was validated in the test set. Receiver operating characteristic curve was used to evaluate and compare the performance of the models at the background of diagnostic performance by radiologist.

Results

In test set, the combined radiomics and semantic model using ANN classifier obtained the best classification performance with an AUC of 0.848 (95% CI: 0.750-0.946), accuracy of 76.7% (95% CI: 64.1-89.4%), sensitivity of 73.9% (95% CI: 56.0-91.9%), and specificity of 80.0% (95% CI: 62.5-97.5%) and performed better than multiparametric model (AUC = 0.792, 95% CI: 0.674-0.910) or semantic model (AUC = 0.823, 95% CI: 0.705-0.941). The two radiologists had an accuracy of 69.8% and 74.4%, respectively, sensitivity of 69.6% and 73.9%, and specificity of 70.0% and 75.0%.

Conclusions

The MR-based radiomics model had technical feasibility and good diagnostic performance in the differential diagnosis between cystic pituitary adenoma and Rathke cleft cyst.

Consistency of Pituitary Adenoma: Prediction by Pharmacokinetic Dynamic Contrast-Enhanced MRI and Comparison with Histologic Collagen Content

Simple Summary

Transsphenoidal resection of hard pituitary adenomas have a particularly high risk of residual tumor and complications. Therefore, prediction of tumor consistency is valuable for planning pituitary adenoma surgery. We prospectively examined whether quantitative pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is useful for predicting consistency of pituitary adenoma in 49 participants. We found that the measure of volume of extravascular extracellular space per unit volume of tissue derived from DCE-MRI could predict the consistency of pituitary adenomas. Furthermore, the volume of extravascular extracellular space per unit volume of tissue was significantly positively correlated with histopathologic collagen content of the adenoma. Our results suggest that volume of extravascular extracellular space per unit volume of tissue derived from quantitative pharmacokinetic analysis of DCE-MRI has a predictive value for consistency of pituitary adenomas.

Abstract

Prediction of tumor consistency is valuable for planning transsphenoidal surgery for pituitary adenoma. A prospective study was conducted involving 49 participants with pituitary adenoma to determine whether quantitative pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is useful for predicting consistency of adenomas. Pharmacokinetic parameters in the adenomas including volume of extravascular extracellular space (EES) per unit volume of tissue (v_e), blood plasma volume per unit volume of tissue (v_p), volume transfer constant between blood plasma and EES (K^trans), and rate constant between EES and blood plasma (k_ep) were obtained. The pharmacokinetic parameters and the histologic percentage of collagen content (PCC) were compared between soft and hard adenomas using Mann–Whitney U test. Pearson’s correlation coefficient was used to correlate pharmacokinetic parameters with PCC. Hard adenomas showed significantly higher PCC (44.08 ± 15.14% vs. 6.62 ± 3.47%, p < 0.01), v_e (0.332 ± 0.124% vs. 0.221 ± 0.104%, p < 0.01), and K^trans (0.775 ± 0.401/min vs. 0.601 ± 0.612/min, p = 0.02) than soft adenomas. Moreover, a significant positive correlation was found between v_e and PCC (r = 0.601, p < 0.01). The v_e derived using DCE-MRI may have predictive value for consistency of pituitary adenoma.

The utility of dynamic MRI in differentiating the hormone-producing ability of pituitary adenomas

PURPOSE

To investigate the relationship between dynamic magnetic resonance imaging (MRI) findings and hormonal activity in pituitary adenomas.

METHODS

We retrospectively evaluated the dynamic MRI findings in 244 patients with pathologically confirmed pituitary adenomas and a diagnosis of clinically active prolactin (PRL)-producing adenomas. Among the 244 pituitary adenomas, 55, 16, 6, and 4 produced growth hormone (GH), PRL, adrenocorticotropic hormone, and thyroid-stimulating hormone, respectively, while 163 were non-functioning (NF) adenomas. For each adenoma, we calculated the washout rate (WR) and early (EER) and delayed (DER) tumour-to-normal-tissue enhancement ratios.

RESULTS

The respective mean values of the WR, EER, and DER were 9.4%, 75.2%, and 64.5% for GH-producing adenomas; 6.2%, 117.1%, and 106.2% for PRL-producing adenomas; and 5.4%, 116.7%, and 108.7% for NF adenomas. GH-producing adenomas had significantly lower EER and DER values than PRL-producing (P < 0.001) and NF adenomas (P < 0.001). In ROC analysis of GH-producing and non-GH-producing adenomas, the areas under the curves of WR, EER, and DER were 0.593, 0.825, and 0.857, respectively.

CONCLUSION

There are differences in dynamic MRI features between GH-producing and non-GH-producing adenomas, which suggests that EER and DER may be useful for diagnosing GH-producing adenomas.

Radiomics With Ensemble Machine Learning Predicts Dopamine Agonist Response in Patients With Prolactinoma

CONTEXT

Early identification of the response of prolactinoma patients to dopamine agonists (DA) is crucial in treatment planning.

OBJECTIVE

To develop a radiomics model using an ensemble machine learning classifier with conventional magnetic resonance images (MRIs) to predict the DA response in prolactinoma patients.

DESIGN

Retrospective study.

SETTING

Severance Hospital, Seoul, Korea.

PATIENTS

A total of 177 prolactinoma patients who underwent baseline MRI (109 DA responders and 68 DA nonresponders) were allocated to the training (n = 141) and test (n = 36) sets. Radiomic features (n = 107) were extracted from coronal T2-weighed MRIs. After feature selection, single models (random forest, light gradient boosting machine, extra-trees, quadratic discrimination analysis, and linear discrimination analysis) with oversampling methods were trained to predict the DA response. A soft voting ensemble classifier was used to achieve the final performance. The performance of the classifier was validated in the test set.

RESULTS

The ensemble classifier showed an area under the curve (AUC) of 0.81 [95% confidence interval (CI), 0.74-0.87] in the training set. In the test set, the ensemble classifier showed an AUC, accuracy, sensitivity, and specificity of 0.81 (95% CI, 0.67-0.96), 77.8%, 78.6%, and 77.3%, respectively. The ensemble classifier achieved the highest performance among all the individual models in the test set.

CONCLUSIONS

Radiomic features may be useful biomarkers to predict the DA response in prolactinoma patients.

Usefulness of the Texture Signatures Based on Multiparametric MRI in Predicting Growth Hormone Pituitary Adenoma Subtypes

Objective

To explore the usefulness of texture signatures based on multiparametric magnetic resonance imaging (MRI) in predicting the subtypes of growth hormone (GH) pituitary adenoma (PA).

Methods

Forty-nine patients with GH-secreting PA confirmed by the pathological analysis were included in this retrospective study. Texture parameters based on T1-, T2-, and contrast-enhanced T1-weighted images (T1C) were extracted and compared for differences between densely granulated (DG) and sparsely granulated (SG) somatotroph adenoma by using two segmentation methods [region of interest 1 (ROI₁), excluding the cystic/necrotic portion, and ROI₂, containing the whole tumor]. Receiver operating characteristic (ROC) curve analysis was performed to determine the differentiating efficacy.

Results

Among 49 included patients, 24 were DG and 25 were SG adenomas. Nine optimal texture features with significant differences between two groups were obtained from ROI₁. Based on the ROC analyses, T1WI signatures from ROI₁ achieved the highest diagnostic efficacy with an AUC of 0.918, the accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 85.7, 72.0, 100.0, 100.0, and 77.4%, respectively, for differentiating DG from SG. Comparing with the T1WI signature, the T1C signature obtained relatively high efficacy with an AUC of 0.893. When combining the texture features of T1WI and T1C, the radiomics signature also had a good performance in differentiating the two groups with an AUC of 0.908. In addition, the performance got in all the signatures from ROI₂ was lower than those in the corresponding signature from ROI_1.

Conclusion

Texture signatures based on MR images may be useful biomarkers to differentiate subtypes of GH-secreting PA patients.

T2-weighted magnetic resonance imaging as a novel predictor of surgical remission in newly diagnosed pituitary macroadenomas presenting as acromegaly

BACKGROUND

Any preoperative diagnostic assessment that can predict the success of the operation in acromegaly will provide a positive impact on overall remission rates. The aim of this study is to reveal whether the signal intensity in T2-weighted Magnetic Resonance Imaging can predict postoperative results in acromegaly patients with macroadenoma.

METHODS

We analyzed our surgical results in regard to T2-weighted images in newly diagnosed consecutive 124 patients with acromegaly, operated between 2014 and 2019. The T2-intensity of the pure somatotroph macroadenomas was correlated with the clinical, radiological, surgical and histopathological characteristics of the acromegaly patients.

RESULTS

We found a predominance of T2-hyperintensity in our series (45%) and the T2-hypointense pure somatotroph adenomas were detected in only 34% of our patients. Total resection was performed in 72% of newly diagnosed acromegaly patients in this series. Accordingly, total resection was achieved in 69% of the T2-hyperintense group, 77% of the T2-hypointense group and 69% of the T2-isointense group. The surgical remission rates for the T2-hyper-, hypo- and isointense groups were 54.5%, 80.7%, and 68.7%, respectively. The surgical remission rate in the T2-hyperintense group was significantly lower than those of hypo- and isointense groups in newly diagnosed acromegaly patients.

CONCLUSIONS

This study demonstrates a close relationship between the T2 signal intensity and the surgical remission rates in acromegaly patients with macroadenoma. Preoperative T2-intensity images may predict the probability of post-surgical remission in patients with newly diagnosed acromegaly. Further support fort this idea comes from recent guidelines for acromegaly management in which the potential utility of using T2 intensity to optimize patient management has been emphasized.

An Update on Pituitary Neuroendocrine Tumors Leading to Acromegaly and Gigantism

An excess of growth hormone (GH) results in accelerated growth and in childhood, the clinical manifestation is gigantism. When GH excess has its onset after epiphyseal fusion at puberty, the overgrowth of soft tissue and bone results in acromegaly. Persistent GH excess in gigantism also causes acromegalic features that become evident in the adult years. The causes of GH excess are primarily lesions in the pituitary, which is the main source of GH. In this review, we provide an update on the clinical, radiological and pathologic features of the various types of pituitary neuroendocrine tumors (PitNETs) that produce GH. These tumors are all derived from PIT1-lineage cells. Those composed of somatotrophs may be densely granulated, resembling normal somatotrophs, or sparsely granulated with unusual fibrous bodies. Those composed of mammosomatotrophs also produce prolactin; rare plurihormonal tumors composed of cells that resemble mammosomatotrophs also produce TSH. Some PitNETs are composed of immature PIT1-lineage cells that do not resemble differentiated somatotrophs, mammosomatotrophs, lactotroph or thyrotrophs; these tumors may cause GH excess. An unusual oncocytic PIT1-lineage tumor known as the acidophil stem cell tumor is predominantly a lactotroph tumor but may express GH. Immature PIT1-lineage cells that express variable amounts of hormones alone or in combination can sometimes cause GH excess. Unusual tumors that do not follow normal lineage differentiation may also secrete GH. Exceptional examples of acromegaly/gigantism are caused by sellar tumors composed of hypothalamic GHRH-producing neurons, alone or associated with a sparsely granulated somatotroph tumor. Each of these various tumors has distinct clinical, biochemical and radiological features. Data from careful studies based on morphologic subtyping indicate that morphologic classification has both prognostic and predictive value.

Magnetic resonance fingerprinting for preoperative differentiation between gonadotroph and non-gonadotroph pituitary macroadenomas

OBJECTIVES

To use magnetic resonance fingerprinting (MRF)-derived T1 and T2 values to differentiate gonadotroph from non-gonadotroph pituitary macroadenomas based on the 2017 World Health Organization classification of pituitary adenomas.

METHODS

A total of 57 patients with suspected pituitary macroadenomas were enrolled for analyses in this study between May 2018 and January 2020. Conventional magnetic resonance imaging (MRI) and MRF were performed in all patients before surgery using a 3-T MRI scanner. MRF-derived T1 and T2 values were compared between the gonadotroph and non-gonadotroph pituitary macroadenomas using a Mann-Whitney U test. The Knosp classification was used to evaluate cavernous sinus invasion by the adenomas. Receiver operating characteristic analyses were used to determine the diagnostic performance of T1 and T2 values.

RESULTS

Quantitative T1 and T2 values yielded from MRF of gonadotroph pituitary macroadenomas were significantly higher than those of the non-gonadotroph pituitary macroadenomas (p < 0.001 and = 0.002, respectively). The AUC for the T2 value (0.888) was significantly greater than that for the T1 value (0.742) (p = 0.034). The AUC for combined T1 and T2 values was 0.885. Non-gonadotroph pituitary macroadenomas were more likely to invade the cavernous sinus than gonadotroph pituitary macroadenomas (55% vs 26%, p = 0.026).

CONCLUSIONS

MRF may help to preoperatively differentiate between gonadotroph and non-gonadotroph pituitary macroadenomas and may be useful in guiding the treatment of these adenomas.

KEY POINTS

• Somatostatin receptor type 3 is the most abundant receptor subtype in gonadotroph pituitary adenomas. • Magnetic resonance fingerprinting may help to preoperatively differentiate between gonadotroph and non-gonadotroph pituitary macroadenomas. • Magnetic resonance fingerprinting shows potential for guiding the treatment of pituitary macroadenomas.

Up-To-Date Magnetic Resonance Imaging Findings for the Diagnosis of Hypothalamic and Pituitary Tumors

Magnetic resonance imaging (MRI) is the preferred imaging technique for the sellar and parasellar regions. In this review article, we report our clinical experience with MRI for hypothalamic and pituitary lesions, such as pituitary adenomas, craniopharyngiomas, Rathke cleft cysts, germinoma, and hypophysitis with reference to the histopathological findings through a review of the literature. Our previous study indicated that three dimensional-spoiled gradient echo sequence is a more suitable sequence for evaluating sellar lesions on postcontrast T1 weighted image (WI). This image demonstrates the defined relationship between the tumor and its surroundings, such as the normal pituitary gland, cavernous sinus, and optic pathway. We demonstrated the characteristic MRI findings of functioning pituitary adenoma. In growth hormone-producing adenoma, signal intensity on T2WI is important to differentiate densely from sparsely granulated somatotroph adenomas. In prolactin-producing pituitary adenomas, distinct hypointense areas in early phase on T2WI, possibly owning to diffuse hemorrhage, indicate pronounced regressions of invasive macroprolactinomas during cabergoline therapy. The two histopathological subtypes, adamantinomatous and squamous papillary craniopharyngioma, differ in genesis. Calcified tumors are mostly adamantinomatous type. On MRI, these lesions have a heterogenous appearance with a solid portion and cystic components. The solid portions and cyst wall enhance heterogeneously. Although cyst fluid of Rathke cleft cysts show variable intensities on MRI, intracystic waxy nodule can be hypointense on T2WI. The enhancing cyst wall may contain the squamous metaplasia. Cystic lesions of the sellar and parasellar areas may be difficult to differentiate on a clinical, imaging, or even histopathological basis.

Clinical, biological, radiological, and pathological comparison of sparsely and densely granulated somatotroph adenomas: a single center experience from a cohort of 131 patients with acromegaly

PURPOSE

Growth hormone-producing pituitary adenomas are divided into two clinically relevant histologic subtypes, densely (DG-A) and sparsely (SG-A) granulated. Histologic subtype was evaluated in a large cohort of patients with acromegaly, separating DG-A and SG-A, and correlated with clinicopathological characteristics.

METHODS

Patients with acromegaly undergoing surgery as initial therapy between 1995 and 2015 were identified. Histologic subtype was determined by keratin expression pattern with CAM5.2 and correlated with clinical and imaging parameters, somatostatin receptor subtype 2 (SST2) expression, post-surgical remission rate, and application of a prognostic scoring system incorporating proliferation and invasiveness.

RESULTS

One hundred thirty-one patients were included. Tumors were classified as DG-A (75, 57.3%), SG-A (29, 22.1%), intermediate (I-A) (9, 6.9%), and unclassified (18, 13.7%) when CAM5.2 was negative. DG-A and I-A were combined for analysis (DG/I-A) and compared to SG-A. Age, gender, proliferation, and post-surgical remission did not differ. SG-A were larger [2 vs. 1.5 cm (median), p = 0.03], more frequently invasive [65.5% vs. 32.9%, p = 0.004], associated with higher MRI T2-weighted signal ratio [1.01 vs. 0.82 (median), p = 0.01], showed lower SST2 expression (p < 0.0001), and scored higher in the prognostic classification (p = 0.004). Surgical remission occurred in 41.7% DG/I-A and 41.4% SG-A (p = 1.0). On multivariate analysis, absence of invasion (p = 0.009) and lower pre-operative IGF-1 index (p = 0.0002) were associated with post-surgical remission.

CONCLUSION

CAM5.2 allowed distinction between DG/I-A and SG-A in most but not all cases. Histologic subtype did not predict surgical outcome. Absence of invasion and lower pre-operative IGF-1 index were the only significant predictors of post-surgical remission in this cohort.

Clinical and Radiological Predictors of Biochemical Response to First-Line Treatment With Somatostatin Receptor Ligands in Acromegaly: A Real-Life Perspective

BACKGROUND

First-generation somatostatin receptor ligands (fg-SRLs) represent the first-line medical treatment for acromegaly, recommended in patients with persistent disease after neurosurgery, or when surgical approach is not feasible. Despite the lack of strong recommendations from guidelines and consensus statements, data from national Registries report an increasing use of medical therapy as first-line treatment in acromegaly.

OBJECTIVE

We retrospectively evaluated the potential role of a large number of clinical and radiological parameters in predicting the biochemical response to 6-month treatment with fg-SRLs, in a cohort of naïve acromegaly patients referred to a single tertiary center for pituitary diseases.

METHODS

Univariable and multivariable logistic regression and linear regression analyses were performed. Biochemical response was defined based on IGF-1 levels, represented as both categorical (tight control, control, >50% reduction) and continuous (linear % reduction) variables.

RESULTS

Fifty-one patients (33 females, median age 57 years) were included in the study. At univariable logistic regression analysis, we found that younger age (≤ 40 years; OR 0.04, p=0.045) and higher BMI (OR 0.866, p=0.034) were associated with a lower chance of achieving >50% IGF-1 reduction. On the contrary, higher IGF-1 xULN values at diagnosis (OR 2.304, p=0.007) and a T2-hypointense tumor (OR 18, p=0.017) were associated with a significantly higher likelihood of achieving >50% IGF-1 reduction after SRL therapy. Of note, dichotomized age, IGF1 xULN at diagnosis, and T2-hypointense signal of the tumor were retained as significant predictors by our multivariable logistic regression model. Furthermore, investigating the presence of predictors to the linear % IGF-1 reduction, we found a negative association with younger age (≤ 40 years; β -0.533, p<0.0001), while a positive association was observed with both IGF-1 xULN levels at diagnosis (β 0.330, p=0.018) and the presence of a T2-hypointense pituitary tumor (β 0.466, p=0.019). All these variables were still significant predictors at multivariable analysis.

CONCLUSIONS

Dichotomized age, IGF-1 levels at diagnosis, and tumor T2-weighted signal are reliable predictors of both >50% IGF-1 reduction and linear % IGF-1 reduction after 6 month fg-SRL treatment in naïve acromegaly patients. These parameters should be considered in the light of an individualized treatment for acromegaly patients.

Radiomics model predicts granulation pattern in growth hormone-secreting pituitary adenomas

PURPOSE

To investigate whether radiomic features from magnetic resonance image (MRI) can predict the granulation pattern of growth hormone (GH)-secreting pituitary adenoma patients.

METHODS

Sixty-nine pathologically proven acromegaly patients (densely granulated [DG] = 50, sparsely granulated [SG] = 19) were included. Radiomic features (n = 214) were extracted from contrast-enhancing and total tumor portions from T2-weighted (T2) MRIs. Imaging features were selected using a least absolute shrinkage and selection operator (LASSO) logistic regression model with fivefold cross-validation. Diagnostic performance for predicting granulation pattern was compared with that for qualitative T2 signal intensity assessment and T2 relative signal intensity (rSI) using the area under the receiver operating characteristics curve (AUC).

RESULTS

Four significant radiomic features from the contrast-enhancing tumor (1 from shape, 1 from first order feature, and 2 from second order features) were selected by LASSO for model construction. The radiomics model showed an AUC, accuracy, sensitivity, and specificity of 0.834 (95% confidence interval [CI] 0.738-0.930), 73.7%, 74.0%, and 73.9%, respectively. The radiomics model showed significantly better performance than the model using qualitative T2 signal intensity assessment (AUC 0.597 [95% CI 0.447-0.747], P = 0.009) and T2 rSI (AUC 0.647 [95% CI 0.523-0.759], P = 0.037).

CONCLUSION

Radiomic features may be useful biomarkers to differentiate granulation pattern of GH-secreting pituitary adenoma patients, and showed better performance than qualitative assessment or rSI evaluation.

Cystic appearance on magnetic resonance imaging in bihormonal growth hormone and prolactin tumors in acromegaly

PURPOSE

To investigate demographic, imaging and laboratory characteristics, and treatment outcomes of acromegaly patients who have bihormonal (BA) growth hormone (GH) and prolactin (PRL) immunoreactive adenomas compared to patients who have densely granulated GH adenomas (DGA) and sparsely granulated GH adenomas (SGA).

METHODS

Retrospective review of single-center surgically treated acromegaly patients; pathology was analyzed by a single neuropathologist using 2017 WHO criteria. Preoperative magnetic resonance imaging was assessed to evaluate tumor size, cystic component, invasion and T2 signal intensity.

RESULTS

Seventy-seven patients; 19 BA (9 mammosomatotroph and 10 mixed GH and PRL adenomas) were compared with 30 DGA, and 28 SGA. Patients with BA were older than SGA (49.6 vs 38.5 years, p = 0.035), had a higher IGF-1 index (3.3 vs 2.3, p = 0.040) and tumors were less frequently invasive (15.8% vs 57.1%, p = 0.005). BA more frequently had a cystic component on MRI than both SGA and DGA (52.6% vs 14.3%, and 22%, p = 0.005 and 0.033, respectively). When all histological types were combined, biochemical remission postoperatively was more common in non-cystic than cystic tumors (50% vs 22.5%, p = 0.042). Somatostatin receptor ligand response rate was 66.7%, 90.9% and 37.5% in BA, DGA and SGA patients, respectively (p = 0.053).

CONCLUSION

Imaging characteristics are an increasingly important adenoma behavior determinant. An adenoma cystic component may suggest that a GH adenoma is a BA. Cystic tumors exhibited lower rates of surgical remission in this series; therefore, optimized individual patient treatment is needed, as patients could be candidates for primary medical treatment.

Artificial intelligence and pituitary adenomas: A review

The aim of this review was to provide an overview of the main concepts in machine learning (ML) and to analyze the ML applications in the imaging of pituitary adenomas. After describing the clinical, pathological and imaging features of pituitary tumors, we defined the difference between ML and classical rule-based algorithms, we illustrated the fundamental ML techniques: supervised, unsupervised and reinforcement learning and explained the characteristic of deep learning, a ML approach employing networks inspired by brain’s structure. Pre-treatment assessment and neurosurgical outcome prediction were the potential ML applications using magnetic resonance imaging. Regarding pre-treatment assessment, ML methods were used to have information about tumor consistency, predict cavernous sinus invasion and high proliferative index, discriminate null cell adenomas, which respond to neo-adjuvant radiotherapy from other subtypes, predict somatostatin analogues response and visual pathway injury. Regarding neurosurgical outcome prediction, the following applications were discussed: Gross total resection prediction, evaluation of Cushing disease recurrence after transsphenoidal surgery and prediction of cerebrospinal fluid fistula’s formation after surgery. Although clinical applicability requires more replicability, generalizability and validation, results are promising, and ML software can be a potential power to facilitate better clinical decision making in pituitary tumor patients.

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.

MRI texture analysis in acromegaly and its role in predicting response to somatostatin receptor ligands

PURPOSE

Given the paucity of reliable predictors of tumor recurrence, progression, or response to somatostatin receptor ligand (SRL) therapy in acromegaly, we attempted to determine whether preoperative MR image texture was predictive of these clinical outcomes. We also determined whether image texture could differentiate somatotroph adenomas from non-functioning pituitary adenomas (NFPAs).

METHODS

We performed a retrospective study of patients with acromegaly due to a macroadenoma who underwent transsphenoidal surgery at our institution between 2007 and 2015. Clinical data were extracted from electronic medical records. MRI texture analysis was performed on preoperative non-enhanced T1-weighted images using ImageJ (NIH). Logistic and Cox models were used to determine if image texture parameters predicted outcomes.

RESULTS

Eighty-nine patients had texture parameters measured, which were compared to that of NFPAs, while 64 of these patients had follow-up and were included in the remainder of analyses. Minimum pixel intensity, skewness, and kurtosis were significantly different in somatotroph adenomas versus NFPAs (area under the receiver operating characteristic curve, 0.7771, for kurtosis). Furthermore, those with a maximum pixel intensity above the median had an increased odds of IGF-I normalization on SRL therapy (OR 5.96, 95% CI 1.33-26.66), which persisted after adjusting for several potential predictors of response. Image texture did not predict tumor recurrence or progression.

CONCLUSION

Our data suggest that MRI texture analysis can distinguish NFPAs from somatotroph macroadenomas with good diagnostic accuracy and can predict normalization of IGF-I with SRL therapy.

Diagnosis and Management of pituitary disease with focus on the role of Magnetic Resonance Imaging

Magnetic resonance (MR) imaging is an essential tool in the diagnosis and management of pituitary diseases, indispensable for making correct treatment decisions. Successful management and follow-up of pituitary pathology requires an understanding of the MR appearance of normal and abnormal structures in the sellar region. This review will describe the MR appearance of the normal and abnormal pituitary gland and proposes an algorithm for the management strategy of some of the most common abnormalities in or around the sella.

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.