Residual Tumor Confers a 10-Fold Increased Risk of Regrowth in Clinically Nonfunctioning Pituitary Tumors

Development and prospective validation of an artificial intelligence-based smartphone app for rapid intraoperative pituitary adenoma identification

BACKGROUND

Intraoperative pathology consultation plays a crucial role in tumor surgery. The ability to accurately and rapidly distinguish tumor from normal tissue can greatly impact intraoperative surgical oncology management. However, this is dependent on the availability of a specialized pathologist for a reliable diagnosis. We developed and prospectively validated an artificial intelligence-based smartphone app capable of differentiating between pituitary adenoma and normal pituitary gland using stimulated Raman histology, almost instantly.

METHODS

The study consisted of three parts. After data collection (part 1) and development of a deep learning-based smartphone app (part 2), we conducted a prospective study that included 40 consecutive patients with 194 samples to evaluate the app in real-time in a surgical setting (part 3). The smartphone app's sensitivity, specificity, positive predictive value, and negative predictive value were evaluated by comparing the diagnosis rendered by the app to the ground-truth diagnosis set by a neuropathologist.

RESULTS

The app exhibits a sensitivity of 96.1% (95% CI: 89.9-99.0%), specificity of 92.7% (95% CI: 74-99.3%), positive predictive value of 98% (95% CI: 92.2-99.8%), and negative predictive value of 86.4% (95% CI: 66.2-96.8%). An external validation of the smartphone app on 40 different adenoma tumors and a total of 191 scanned SRH specimens from a public database shows a sensitivity of 93.7% (95% CI: 89.3-96.7%).

CONCLUSIONS

The app can be readily expanded and repurposed to work on different types of tumors and optical images. Rapid recognition of normal versus tumor tissue during surgery may contribute to improved intraoperative surgical management and oncologic outcomes. In addition to the accelerated pathological assessments during surgery, this platform can be of great benefit in community hospitals and developing countries, where immediate access to a specialized pathologist during surgery is limited.

A proposed clinical classification for pituitary neoplasms to guide therapy and prognosis

No comprehensive classification system that guides prognosis and therapy of pituitary adenomas exists. The 2022 WHO histopathology-based classification system can only be applied to lesions that are resected, which represent few clinically significant pituitary adenomas. Many factors independent of histopathology provide mechanistic insight into causation and influence prognosis and treatment of pituitary adenomas. We propose a new approach to guide prognosis and therapy of pituitary adenomas by integrating clinical, genetic, biochemical, radiological, pathological, and molecular information for all adenomas arising from anterior pituitary cell lineages. The system uses an evidence-based scoring of risk factors to yield a cumulative score that reflects disease severity and can be used at the bedside to guide pituitary adenoma management. Once validated in prospective studies, this simple manageable classification system could provide a standardised platform for assessing disease severity, prognosis, and effects of therapy on pituitary adenomas.

A Multicenter, Propensity Score-Matched Assessment of Endoscopic Versus Microscopic Approaches in the Management of Pituitary Adenomas

BACKGROUND AND OBJECTIVES

There is considerable controversy as to which of the 2 operating modalities (microsurgical or endoscopic transnasal surgery) currently used to resect pituitary adenomas (PAs) is the safest and most effective intervention. We compared rates of clinical outcomes of patients with PAs who underwent resection by either microsurgical or endoscopic transnasal surgery.

METHODS

To independently assess the outcomes of each modality type, we sought to isolate endoscopic and microscopic PA surgeries with a 1:1 tight-caliper (0.01) propensity score-matched analysis using a multicenter, neurosurgery-specific database. Surgeries were performed between 2017 and 2020, with data collected retrospectively from 12 international institutions on 4 continents. Matching was based on age, previous neurological deficit, American Society of Anesthesiologists (ASA) score, tumor functionality, tumor size, and Knosp score. Univariate and multivariate analyses were performed.

RESULTS

Among a pool of 2826 patients, propensity score matching resulted in 600 patients from 9 surgery centers being analyzed. Multivariate analysis showed that microscopic surgery had a 1.91 odds ratio (OR) ( P = .03) of gross total resection (GTR) and shorter operative duration ( P < .01). However, microscopic surgery also had a 7.82 OR ( P < .01) for intensive care unit stay, 2.08 OR ( P < .01) for intraoperative cerebrospinal fluid (CSF) leak, 2.47 OR ( P = .02) for postoperative syndrome of inappropriate antidiuretic hormone secretion (SIADH), and was an independent predictor for longer postoperative stay (β = 2.01, P < .01). Overall, no differences in postoperative complications or 3- to 6-month outcomes were seen by surgical approach.

CONCLUSION

Our international, multicenter matched analysis suggests microscopic approaches for pituitary tumor resection may offer better GTR rates, albeit with increased intensive care unit stay, CSF leak, SIADH, and hospital utilization. Better prospective studies can further validate these findings as matching patients for outcome analysis remains challenging. These results may provide insight into surgical benchmarks at different centers, offer room for further registry studies, and identify best practices.

Identification of biomarkers associated with the invasion of nonfunctional pituitary neuroendocrine tumors based on the immune microenvironment

Introduction

The invasive behavior of nonfunctioning pituitary neuroendocrine tumors (NF-PitNEts) affects complete resection and indicates a poor prognosis. Cancer immunotherapy has been experimentally used for the treatment of many tumors, including pituitary tumors. The current study aimed to screen the key immune-related genes in NF-PitNEts with invasion.

Methods

We used two cohorts to explore novel biomarkers in NF-PitNEts. The immune infiltration-associated differentially expressed genes (DEGs) were obtained based on high/low immune scores, which were calculated through the ESTIMATE algorithm. The abundance of immune cells was predicted using the ImmuCellAI database. WGCNA was used to construct a coexpression network of immune cell-related genes. Random forest analysis was used to select the candidate genes associated with invasion. The expression of key genes was verified in external validation set using quantitative real-time polymerase chain reaction (qRT‒PCR).

Results

The immune and invasion related DEGs was obtained based on the first dataset of NF-PitNEts (n=112). The immune cell-associated modules in NF-PitNEts were calculate by WGCNA. Random forest analysis was performed on 81 common genes intersected by immune-related genes, invasion-related genes, and module genes. Then, 20 of these genes with the highest RF score were selected to construct the invasion and immune-associated classification model. We found that this model had high prediction accuracy for tumor invasion, which had the largest area under the receiver operating characteristic curve (AUC) value in the training dataset from the first dataset (n=78), the self-test dataset from the first dataset (n=34), and the independent test dataset (n=73) (AUC=0.732/0.653/0.619). Functional enrichment analysis revealed that 8 out of the 20 genes were enriched in multiple signaling pathways. Subsequently, the 8-gene (BMP6, CIB2, FABP5, HOMER2, MAML3, NIN, PRKG2 and SIDT2) classification model was constructed and showed good efficiency in the first dataset (AUC=0.671). In addition, the expression levels of these 8 genes were verified by qRT‒PCR.

Conclusion

We identified eight key genes associated with invasion and immunity in NF-PitNEts that may play a fundamental role in invasive progression and may provide novel potential immunotherapy targets for NF-PitNEts.

Post-operative surveillance for somatotroph, lactotroph and non-functional pituitary adenomas after curative resection: a systematic review

CONTEXT

Pituitary tumors are the third most common brain tumor and yet there is no standardization of the surveillance schedule and assessment modalities after transsphenoidal surgery.

EVIDENCE ACQUISITION

OVID, EMBASE and the Cochrane Library databases were systematically screened from database inception to March 5, 2020. Inclusion and exclusion criteria were designed to capture studies examining detection of pituitary adenoma recurrence in patients 18 years of age and older following surgical resection with curative intent.

EVIDENCE SYNTHESIS

A total of 7936 abstracts were screened, with 812 articles reviewed in full text and 77 meeting inclusion criteria for data extraction. A pooled analysis demonstrated recurrence rates at 1 year, 5 years and 10 years for non-functioning pituitary adenomas (NFPA; N = 3533 participants) were 1%, 17%, and 33%, for prolactin-secreting adenomas (PSPA; N = 1295) were 6%, 21%, and 28%, and for growth-hormone pituitary adenomas (GHPA; N = 1257) were 3%, 8% and 13%, respectively. Rates of recurrence prior to 1 year were 0% for NFPA, 1-2% for PSPA and 0% for GHPA. The mean time to disease recurrence for NFPA, PSPA and GHPA were 4.25, 2.52 and 4.18 years, respectively.

CONCLUSIONS

This comprehensive review of the literature quantified the recurrence rates for commonly observed pituitary adenomas after transsphenoidal surgical resection with curative intent. Our findings suggest that surveillance within 1 year may be of low yield. Further clinical trials and cohort studies investigating cost-effectiveness of surveillance schedules and impact on quality of life of patients under surveillance will provide further insight to optimize follow-up.

Recurrence Rate and Exploration of Clinical Factors after Pituitary Adenoma Surgery: A Systematic Review and Meta-Analysis based on Computer Artificial Intelligence System

Background

The first-line treatment for patients with any type of pituitary adenoma is trans-sphenoidal surgery. Considering the prevalence of the condition globally, the treatment is quite common. The recurrence of pituitary adenoma is a recognized occurrence in the medical field; however, there is limited comprehensive research and analysis of the predictive factors of recurrence rates and the clinical factors impacting relapse rates. Identifying the recurrence rates of pituitary adenomas and the clinical factors associated with them could help increase the remission rate by increasing focus on the specific aspects for early diagnosis and improved treatment.

Objective

The objective of the current systematic review and meta-analysis is to assess the recurrent rates based on previous studies and to explore the clinical factors after pituitary surgery.

Methods

A search was performed on PubMed, APA PsycINFO, Scopus, CENTRAL, and Google Scholar databases for English articles published from 1^st January 2010 to 1^st August 2022. Systematic reviews, meta-analysis, evidence syntheses, editorials, commentaries, preclinical studies, abstracts, theses, and preprints were excluded. Meta XL statistical software was used to conduct a prevalence meta-analysis.

Results

PubMed, PsycINFO, and Medline databases were searched. All of the articles were written between 2012 and 2022. In the beginning, 612 items were recognized. After removing duplicates and analyzing the remaining articles in terms of inclusion and exclusion criteria, 31 articles remained.

Conclusion

There is a relationship between recurrence rates and the follow-up period. There were conflicting results about the clinical factors after pituitary adenoma surgery, specifically age and tumor size. Some included studies that there was an association between macroadenomas and high recurrence rates. No study reported that gender was a clinical factor affecting pituitary adenoma surgery outcomes or the recurrence rate. Studies also reported that there was a correlation between the remnant tumor factor and the recurrence rates; adenoma remnants after surgery increased the risk of recurrence rates for patients.

A systematic review of molecular alterations in invasive non-functioning pituitary adenoma

PURPOSE

Invasive non-functional pituitary adenomas (NFPAs) constitute 35% of NFPAs. Despite a relatively large body of molecular investigations on the invasiveness of NFPA, the underlying molecular mechanisms of invasiveness are yet to be determined. Herein, we aimed to provide an overview of gene/microRNA(miRNAs) expression alterations in invasive NFPA.

METHODS

This article describes a systematic literature review of articles published up to March 23, 2021, on the transcriptional alterations of invasive NFPA. Five digital libraries were searched, and 42 articles in total fulfilled the eligibility criteria. Pathway enrichment was conducted, and protein interactions among the identified deregulated genes were inferred.

RESULTS

In total 133 gene/protein transcriptional alterations, comprising 87 increased and 46 decreased expressions, were detected in a collective number of 1001 invasive compared with 1007 non-invasive patients with NFPA. Deregulation of CDH1, PTTG1, CCNB1, SNAI1, SLUG, EZR, and PRKACB, which are associated with epidermal-mesenchymal transition (EMT), was identified. Moreover, six members of the angiogenesis pathway, i.e., VEGFA, FLT1, CCND1, CTNNB1, MYC(c-MYC), and PTTG1, were detected. SLC2A1, FLT1, and VEGFA were also recognized in the hypoxia pathway. Physical interactions of CTNNB1 with FLT1, CCND1, and EZR as well as its indirect interactions with VEGFA, MYC, CCNB1, and PCNA indicate the tight interplay between EMT, angiogenesis, and hypoxia pathways in invasive NFPAs. In addition, Hippo, JAK-STAT, MAPK, Wnt, PI3K-Akt, Ras, TGF-b, VEGF, and ErbB were identified as interwoven signaling pathways.

CONCLUSION

In conclusion, invasive NFPA shares very common deregulated signaling pathways with invasive cancers. A large amount of heterogeneity in the reported deregulations in different studies necessitates the validation of the expressional changes of the suggested biomarkers in a large number of patients with invasive NFPA.

Quality of Life After Endoscopic Surgical Management of Pituitary Adenomas

BACKGROUND

Patient-reported quality of life (QOL) is a vital metric for surgical success.

OBJECTIVE

To assess the effect of surgery on QOL in the largest prospectively collected, longitudinal cohort of surgically managed pituitary adenomas.

METHODS

A consecutive surgical adenoma cohort (n = 304) between late 2016 and mid-2020 underwent a scheduled overall (Anterior Skull Base Questionnaire-35) and sinonasal-specific (Sinonasal Outcome Test-22) QOL assessment. Scores were stratified by adenoma subtype and analyzed for clinical predictors of QOL changes.

RESULTS

The average age was 53.8 ± 16 yr, and 53% of participants were female. 60.9% of adenomas were nonfunctioning while adrenocorticotropic hormone adenomas (16.4%), growth hormone adenomas (14.1%), and prolactinomas (5.9%) were the most prevalent secreting adenomas. Baseline overall QOL differed between tumor types (P = .006), with adrenocorticotropic hormone adenomas worse than growth hormone adenomas (P = .03) and nonfunctioning pituitary adenomas (NFPA) (P < .001). Sinonasal QOL worsened in the 3 wk after surgery but returned to baseline by 6 wk and beyond. Overall QOL worsened at 3 wk after surgery (P < .001) but significantly improved from baseline by 3 mo (P = .009) and beyond (P < .001). Emotional functioning improved soon after surgery, followed by performance and pain, and then, by 6 mo, physical function and vitality. Predictors of improved QOL were sellar/suprasellar lesions (P = .01), prolactinomas (P = .003), and NFPA (P = .04). Conversely, new postoperative hypopituitarism (P = .04) and larger adenoma volume (P = .04) predicted QOL worsening.

CONCLUSION

QOL is worsened after surgery at early time points. Prolactinomas and NFPA enjoy significant QOL improvements from surgery as early as 3 mo postoperatively. Other functional tumors may experience early benefits in younger patients without hypopituitarism and when isolated to the sellar/suprasellar region. These findings provide valuable information for counseling patients and setting expectations for surgery.

Clinically non-functioning pituitary adenomas

Clinically non functioning pituitary adenomas (NFPAs) include all pituitary adenomas that are not hormonally active. They are not associated with clinical syndromes such as amenorrhea-galactorrhea (prolactinomas), acromegaly, Cushing's disease or hyperthyroidism (TSH-secreting adenomas) and are therefore usually diagnosed by signs and symptoms related to a mass effect (headache, visual impairment, sometimes pituitary apoplexy), but also incidentally. Biochemical work up often documents several pituitary insufficiencies. In histopathology, the majority of NFPAs are gonadotroph. In the absence of an established medical therapy, surgery is the mainstay of treatment, unless contraindicated or in particular situations (e.g. small incidentalomas, distance from optic pathways). Resection, generally via a trans-sphenoidal approach (with the help of an endoscope), should be performed by a neurosurgeon with extensive experience in pituitary surgery, in order to maximize the chances of complete resection and to minimize complications. If a tumor remnant persists, watchful waiting is preferred to routine radiotherapy, as long as the tumor residue does not grow and is distant from the optic pathways. NFPA can sometimes recur even after complete resection, but predicting the individual risk of tumor remnant progression is difficult. Postoperative irradiation is only considered in case of residual tumor growth or relapse, due to its potential side effects.

Solid tumor size for prediction of recurrence in large and giant non-functioning pituitary adenomas

A subset of large non-functioning pituitary adenomas (lNFPA) and giant non-functioning pituitary adenomas (gNFPA) undergoes early progression/recurrence (P/R) after surgery. This study revealed the clinical and image predictors of P/R in lNFPA and gNFPA, with emphasis on solid tumor size. This retrospective study investigated the preoperative MR imaging features for the prediction of P/R in lNFPA (> 3 cm) and gNFPA (> 4 cm). Only the patients with a complete preoperative brain MRI and undergone postoperative MRI follow-ups for more than 1 year were included. From November 2010 to December 2020, a total of 34 patients diagnosed with lNFPA and gNFPA were included (median follow-up time 47.6 months) in this study. A total of twenty-three (23/34, 67.6%) patients had P/R, and the median time to P/R is 25.2 months. Solid tumor diameter (STD), solid tumor volume (STV), and extent of resection are associated with P/R (p < 0.05). Multivariate analysis showed large STV is a risk factor for P/R (p < 0.05) with a hazard ratio of 30.79. The cutoff points of STD and STV for prediction of P/R are 26 mm and 7.6 cm³, with AUCs of 0.78 and 0.79 respectively. Kaplan-Meier analysis of tumor P/R trends showed that patients with larger STD and STV exhibited shorter progression-free survival (p < 0.05). For lNFPA and gNFPA, preoperative STD and STV are significant predictors of P/R. The results offer objective and valuable information for treatment planning in this subgroup.

Thin-Slice Pituitary MRI with Deep Learning-based Reconstruction: Diagnostic Performance in a Postoperative Setting

Background Achieving high-spatial-resolution pituitary MRI is challenging because of the trade-off between image noise and spatial resolution. Deep learning-based MRI reconstruction enables image denoising with sharp edges and reduced artifacts, which improves the image quality of thin-slice MRI. Purpose To assess the diagnostic performance of 1-mm slice thickness MRI with deep learning-based reconstruction (DLR) (hereafter, 1-mm MRI+DLR) compared with 3-mm slice thickness MRI (hereafter, 3-mm MRI) for identifying residual tumor and cavernous sinus invasion in the evaluation of postoperative pituitary adenoma. Materials and Methods This single-institution retrospective study included 65 patients (mean age ± standard deviation, 54 years ± 10; 26 women) who underwent a combined imaging protocol including 3-mm MRI and 1-mm MRI+DLR for postoperative evaluation of pituitary adenoma between August and October 2019. Reference standards for correct diagnosis were established by using all available imaging resources, clinical histories, laboratory findings, surgical records, and pathology reports. The diagnostic performances of 3-mm MRI, 1-mm slice thickness MRI without DLR (hereafter, 1-mm MRI), and 1-mm MRI+DLR for identifying residual tumor and cavernous sinus invasion were evaluated by two readers and compared between the protocols. Results The performance of 1-mm MRI+DLR in the identification of residual tumor was comparable to that of 3-mm MRI (area under the receiver operating characteristic curve [AUC], 0.89-0.92 vs 0.85-0.89, respectively; P ≥ .09). In the identification of cavernous sinus invasion, the diagnostic performance of 1-mm MRI+DLR was higher than that of 3-mm MRI (AUC, 0.95-0.98 vs 0.83-0.87, respectively; P ≤ .02). Conventional 1-mm MRI (AUC, 0.82-0.83) showed comparable diagnostic performance to 3-mm MRI (AUC, 0.83-0.87) (P ≥ .38). With 1-mm MRI+DLR, residual tumor was diagnosed in 20 patients and cavernous sinus invasion was diagnosed in 14 patients, in whom these diagnoses were not made with 3-mm MRI. Conclusion In the postoperative evaluation of pituitary adenoma, 1-mm slice thickness MRI with deep learning-based reconstruction showed higher diagnostic performance than 3-mm slice thickness MRI in the identification of cavernous sinus invasion and comparable diagnostic performance to 3-mm slice thickness MRI in the identification of residual tumor. © RSNA, 2020 Online supplemental material is available for this article.