Magnetic resonance elastography detects tumoral consistency in pituitary macroadenomas

Refining the predictive value of preoperative apparent diffusion coefficient (ADC) by whole-tumor analysis for facial nerve outcomes in vestibular schwannomas

BACKGROUND

Apparent diffusion coefficient (ADC) in MRI has been shown to correlate with postoperative House-Brackmann (HB) scores in patients with vestibular schwannoma despite limited methodology. To rectify limitations of single region of interest (ROI) sampling, we hypothesize that whole-tumor ADC histogram analysis will refine the predictive value of this preoperative biomarker related to postoperative facial nerve function.

METHODS

Of 155 patients who underwent resection of vestibular schwannoma (2014-2020), 125 patients were included with requisite clinical and radiographic data. After volumetric analysis and whole-tumor ADC histogram, regression tree analysis identified ADC cutoff for significant differences in HB grade. Outcomes were extent of resection, facial nerve function, hospital length of stay (LOS), and complications.

RESULTS

Regression tree analysis defined three quantitative ADC groups (× 10-6 mm2/s) as high (> 2248.77; HB 1.7), mid (1468.44-2248.77; HB 3.1), and low (< 1468.44; HB 2.3) range (p 0.04). The mid-range ADC group had significantly worse postoperative HB scores and longer hospital LOS. Large tumor volume was independently predictive of lower rates of gross total resection (p <0.0001), higher postoperative HB score (p 0.002), higher rate of complications (p 0.04), and longer LOS (p 0.003).

CONCLUSIONS

Whole-tumor histogram yielded a robust regression tree analysis that defined three ADC groups with significantly different facial nerve outcomes. This likely reflects tumor heterogeneity better than solid-tumor ROI sampling. Whole-tumor ADC warrants further study as a useful radiographic biomarker in patients with vestibular schwannoma who are considering surgical resection.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Repeatability of diffusion-based stiffness prediction - A healthy volunteer study

INTRODUCTION

The study investigated the repeatability of brain diffusion-based stiffness prediction (DWIstiff) in healthy volunteers.

METHODS

Thirty-one healthy volunteers were examined with DWIstiff using two different sets of b-values: b200-1500 s/mm2 (DWIstiff, 1500) and b200-1000 s/mm2 (DWIstiff, 1000). Each b-value set was scanned twice per imaging session without repositioning the participants. DWIstiff images were reconstructed from each set. Two observers delineated regions of interest (ROIs) on each DWIstiff image. The repeatability coefficient (RC), coefficient of variation (CV), inter- and intraobserver agreement were calculated.

RESULTS

After excluding three participants due to image artifacts, the study included twenty-eight volunteers (mean age (range)) 37 years (24-62), 10 males, 18 females). For DWIstiff, 1500, the lowest and the highest RCs were in the parietal lobe (0.52) and respectively the brain stem (1.17). The lowest RC for DWIstiff, 1000 was in the frontal lobe (0.42) and the highest in the brain stem (1.58). The CV for whole brain measurements was 3.83 % for DWIstiff, 1500 and 4.93 % for DWIstiff, 1000. The Bland‒Altman (BA) limits of agreement (LoA) for the intraobserver agreement of DWIstiff, 1500 were -0.90 to 1.06 and respectively -0.78 to 0.88 for DWIstiff, 1000. Regarding interobserver agreement, the LoA were -0.85 to 0.94 for DWIstiff, 1500 and -0.61 to 0.66 for DWIstiff, 1000.

CONCLUSION

DWIstiff is a precise technique with some observer dependence. Repeatability is higher for DWIstiff, 1000 s/mm2 than for DWIstiff 1500 s/mm2.

IMPLICATIONS FOR PRACTICE

Our findings suggest that DWIstiff can reliably detect stiffness changes larger than 4.93 % in healthy volunteers. Further studies should investigate whether the repeatability of DWIstiff may be affected by the presence of pathology such as a brain tumor.

Preoperative Magnetic Resonance Elastography (MRE) of Skull Base Tumours: A Review

Conventional magnetic resonance imaging (MRI) can detect tumors consistency, but it can't predict tumor stiffness or adherence of the tumor to nearby structures. Magnetic resonance elastography (MRE) is a known non-invasive MRI based imaging technique used to assess the viscoelasticity of the tissues particularly liver fibrosis. This study discussed the importance of preoperative MRE in skull base tumors and the future implications of this new imaging modality. We did review of the English literature (by searching PubMed) regarding the use of MRE in preoperative assessment of skull base tumours stiffness and adherence to surrounding tissues. Recent research demonstrated that MRE can detect the stiffness and adherence of skull base tumors to surrounding structures by recording the spread of mechanical waves in the different tissues. In addition to non-radiation exposure, this technique is fast and can be incorporated into the conventional (MRI) study. MRE can palpate skull base tumours by imaging, allowing the stiffness of the tumour to be assessed. Preoperative assessment of brain tumours consistency, stiffness, and adherence to surrounding tissues is critical to avoid injury of important nearby structures and better preoperative patient counselling regarding surgical approach (endoscopic or open), operative time, and suspected surgical complications. However, the accuracy of MRE is less in small and highly vascular tumors. Also, MRE can't accurately detect tumour-brain adherence, but the new modality (slip-interface imaging) can. Hence, adding MRE to the conventional MRI study may help in preoperative diagnosis and treatment of skull base tumours.

Supershear Rayleigh wave imaging for quantitative assessment of biomechanical properties of brain using air-coupled optical coherence elastography

Recently, supershear Rayleigh waves (SRWs) have been proposed to characterize the biomechanical properties of soft tissues. The SRWs propagate along the surface of the medium, unlike surface Rayleigh waves, SRWs propagate faster than bulk shear waves. However, their behavior and application in biological tissues is still elusive. In brain tissue elastography, shear waves combined with magnetic resonance elastography or ultrasound elastography are generally used to quantify the shear modulus, but high spatial resolution elasticity assessment in 10 μm scale is still improving. Here, we develop an air-coupled ultrasonic transducer for noncontact excitation of SRWs and Rayleigh waves in brain tissue, use optical coherent elastography (OCE) to detect, and reconstruct the SRW propagation process; in combing with a derived theoretical model of SRWs on a free boundary surface, we quantify the shear modulus of brain tissue with high spatial resolution. We first complete validation experiments using a homogeneous isotropic agar phantom, and the experimental results clearly show the SRW is 1.9649 times faster than the bulk shear waves. Furthermore, the propagation velocity of SRWs in both the frontal and parietal lobe regions of the brain is all 1.87 times faster than the bulk shear wave velocity. Finally, we evaluated the anisotropy in different brain regions, and the medulla oblongata region had the highest anisotropy index. Our study shows that the OCE system using the SRW model is a new potential approach for high-resolution assessment of the biomechanical properties of brain tissue.

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.

Pituitary adenoma consistency affects postoperative hormone function: a retrospective study

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

The Party Wall: Redefining the Indications of Transcranial Approaches for Giant Pituitary Adenomas in Endoscopic Era

The evolution of endoscopic trans-sphenoidal surgery raises the question of the role of transcranial surgery for pituitary tumors, particularly with the effectiveness of adjunct irradiation. This narrative review aims to redefine the current indications for the transcranial approaches for giant pituitary adenomas in the endoscopic era. A critical appraisal of the personal series of the senior author (O.A.-M.) was performed to characterize the patient factors and the tumor's pathological anatomy features that endorse a cranial approach. Traditional indications for transcranial approaches include the absent pneumatization of the sphenoid sinus; kissing/ectatic internal carotid arteries; reduced dimensions of the sella; lateral invasion of the cavernous sinus lateral to the carotid artery; dumbbell-shaped tumors caused by severe diaphragm constriction; fibrous/calcified tumor consistency; wide supra-, para-, and retrosellar extension; arterial encasement; brain invasion; coexisting cerebral aneurysms; and separate coexisting pathologies of the sphenoid sinus, especially infections. Residual/recurrent tumors and postoperative pituitary apoplexy after trans-sphenoidal surgery require individualized considerations. Transcranial approaches still have a critical role in giant and complex pituitary adenomas with wide intracranial extension, brain parenchymal involvement, and the encasement of neurovascular structures.

Neoplasms and tumor-like lesions of the sellar region: imaging findings with correlation to pathology and 2021 WHO classification

The sellar region represents a complex anatomical area, composed of multiple structures of different embryological derivation, including the skull base and the pituitary gland, along with vascular, nervous, and meningeal structures. Masses arising in this region include benign and malignant lesions arising from the pituitary gland itself, but also from vestigial embryological residues or surrounding tissues, that may require different therapeutic approaches. While assessing sellar region masses, the combination of clinical presentation and imaging features is fundamental to define hypotheses about their nature. MR represents the imaging modality of choice, providing information about the site of the lesion, its imaging features, and relation with adjacent structures, while CT is useful to confirm the presence of lesion calcifications or to reveal tumor invasion of bony structures. The aim of this pictorial review is to provide an overview of the common neoplasms and tumor-like conditions of the sellar region, according to the 2021 WHO Classification of Tumors of the Central Nervous System (fifth edition), with an emphasis on the radiologic-pathologic correlation. After a brief introduction on the anatomy of this region and the imaging and pathological techniques currently used, the most relevant MRI characteristics, clinical findings, and pathological data, including histologic and molecular features, will be shown and discussed, with the aim of facilitating an appropriate differential diagnosis among these entities.

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.

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

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

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.

Applications of elastography in operative neurosurgery: A systematic review

Elastography is an imaging technology capable of measuring tissue stiffness and consistency. The technology has achieved widespread use in the workup and management of diseases of the liver, breast, thyroid, and prostate. Although elastography is increasingly being applied in neurosurgery, it has not yet achieved widespread adoption and many clinicians remain unfamiliar with the technology. Therefore, we sought to summarize the range of applications and elastography modalities available for neurosurgery, report its effectiveness in comparison with conventional imaging methods, and offer recommendations. All full-text English-language manuscripts on the use of elastography for neurosurgical procedures were screened using the PubMed/MEDLINE, Embase, Cochrane Library, Scopus, and Web of Science databases. Thirty-two studies were included with 990 patients, including 21 studies on intracranial tumors, 5 on hydrocephalus, 4 on epilepsy, 1 on spinal cord compression, and 1 on adolescent scoliosis. Twenty studies used ultrasound elastography (USE) whereas 12 used magnetic resonance elastography (MRE). MRE studies were mostly used in the preoperative setting for assessment of lesion stiffness, tumor-brain adherence, diagnostic workup, and operative planning. USE studies were performed intraoperatively to guide resection of lesions, determine residual microscopic abnormalities, assess the tumor-brain interface, and study mechanical properties of tumors. Elastography can assist with resection of brain tissue, detection of microscopic lesions, and workup of hydrocephalus, among other applications under investigation. Its sensitivity often exceeds that of conventional MRI and ultrasound for identifying abnormal tissue and lesion margins.

Mechanical Properties of the Extracellular Environment of Human Brain Cells Drive the Effectiveness of Drugs in Fighting Central Nervous System Cancers

The evaluation of nanomechanical properties of tissues in health and disease is of increasing interest to scientists. It has been confirmed that these properties, determined in part by the composition of the extracellular matrix, significantly affect tissue physiology and the biological behavior of cells, mainly in terms of their adhesion, mobility, or ability to mutate. Importantly, pathophysiological changes that determine disease development within the tissue usually result in significant changes in tissue mechanics that might potentially affect the drug efficacy, which is important from the perspective of development of new therapeutics, since most of the currently used in vitro experimental models for drug testing do not account for these properties. Here, we provide a summary of the current understanding of how the mechanical properties of brain tissue change in pathological conditions, and how the activity of the therapeutic agents is linked to this mechanical state.

Advanced Neuroimaging Approaches to Pediatric Brain Tumors

Simple Summary

After leukemias, brain tumors are the most common cancers in children, and early, accurate diagnosis is critical to improve patient outcomes. Beyond the conventional imaging methods of computed tomography (CT) and magnetic resonance imaging (MRI), advanced neuroimaging techniques capable of both structural and functional imaging are moving to the forefront to improve the early detection and differential diagnosis of tumors of the central nervous system. Here, we review recent developments in neuroimaging techniques for pediatric brain tumors.

Abstract

Central nervous system tumors are the most common pediatric solid tumors; they are also the most lethal. Unlike adults, childhood brain tumors are mostly primary in origin and differ in type, location and molecular signature. Tumor characteristics (incidence, location, and type) vary with age. Children present with a variety of symptoms, making early accurate diagnosis challenging. Neuroimaging is key in the initial diagnosis and monitoring of pediatric brain tumors. Conventional anatomic imaging approaches (computed tomography (CT) and magnetic resonance imaging (MRI)) are useful for tumor detection but have limited utility differentiating tumor types and grades. Advanced MRI techniques (diffusion-weighed imaging, diffusion tensor imaging, functional MRI, arterial spin labeling perfusion imaging, MR spectroscopy, and MR elastography) provide additional and improved structural and functional information. Combined with positron emission tomography (PET) and single-photon emission CT (SPECT), advanced techniques provide functional information on tumor metabolism and physiology through the use of radiotracer probes. Radiomics and radiogenomics offer promising insight into the prediction of tumor subtype, post-treatment response to treatment, and prognostication. In this paper, a brief review of pediatric brain cancers, by type, is provided with a comprehensive description of advanced imaging techniques including clinical applications that are currently utilized for the assessment and evaluation of pediatric brain tumors.

Predicting pituitary adenoma consistency with preoperative magnetic resonance elastography

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Pituitary MRI Standard and Advanced Sequences: Role in the Diagnosis and Characterization of Pituitary Adenomas

Pituitary adenomas (PAs) represent the most frequently found lesions in the sellar region; however, several other lesions may be encountered in this region, such as meningiomas, craniopharyngiomas, and aneurysms. High-quality imaging is fundamental for diagnosis, characterization, and guidance of treatment planning of PAs. Sellar magnetic resonance imaging (MRI) is considered the imaging modality of choice for the evaluation of lesions in the sella turcica. The sellar MRI standard protocol includes coronal and sagittal T1-weighted spin-echo sequencing with and without gadolinium-based contrast agent and coronal T2-weighted (T2w) fast-spin echo sequencing. A systematic MRI approach to the pituitary region generally provides information that includes the size and shape of the PA, the presence of cysts or hemorrhage within the tumor, its relationship with the optic pathways and surrounding structures, potential cavernous sinus invasion, sphenoid sinus pneumatization type, and differential diagnosis with other sellar lesions. The standard protocol is sufficient for the evaluation of most cases; however, some advanced techniques (susceptibility imaging, diffusion-weighted imaging, 3D T2w high-resolution sequences, magnetic resonance elastography, perfusion-weighted imaging) may render additional information, which may be important for some cases. In this "approach to the patient" manuscript, we will discuss the use of standard and advanced MRI sequences in the diagnosis and characterization of PAs, including MRI features associated with treatment response that may aid in presurgical evaluation and planning, and red flags that may point to an alternative diagnosis.

Impact of material homogeneity assumption on cortical stiffness estimates by MR elastography

PURPOSE

Inversion algorithms used to convert acquired MR elastography wave data into material property estimates often assume that the underlying materials are locally homogeneous. Here we evaluate the impact of that assumption on stiffness estimates in gray-matter regions of interest in brain MR elastography.

METHODS

We describe an updated neural network inversion framework using finite-difference model-derived data to train convolutional neural network inversion algorithms. Neural network inversions trained on homogeneous simulations (homogeneous learned inversions [HLIs]) or inhomogeneous simulations (inhomogeneous learned inversions [ILIs]) are generated with a variety of kernel sizes. These inversions are evaluated in a brain MR elastography simulation experiment and in vivo in a test-retest repeatability experiment including 10 healthy volunteers.

RESULTS

In simulation and in vivo, HLI and ILI with small kernels produce similar results. As kernel size increases, the assumption of homogeneity has a larger effect, and HLI and ILI stiffness estimates show larger differences. At each inversion's optimal kernel size in simulation (7 × 7 × 7 for HLI, 11 × 11 × 11 for ILI), ILI is more sensitive to true changes in stiffness in gray-matter regions of interest in simulation. In vivo, there is no difference in the region-level repeatability of stiffness estimates between the inversions, although ILI appears to better maintain the stiffness map structure as kernel size increases, while decreasing the spatial variance in stiffness estimates.

CONCLUSIONS

This study suggests that inhomogeneous inversions provide small but significant benefits even when large stiffness gradients are absent.

Multi-Omics Investigations Revealed Underlying Molecular Mechanisms Associated With Tumor Stiffness and Identified Sunitinib as a Potential Therapy for Reducing Stiffness in Pituitary Adenomas

Purpose: Pituitary adenomas (PAs) are the second most common intracranial neoplasms. Total surgical resection was extremely important for curing PAs, whereas tumor stiffness has gradually become the most critical factor affecting the resection rate in PAs. We aimed to investigate the molecular mechanisms of tumor stiffening and explore novel medications to reduce stiffness for improving surgical remission rates in PA patients.

Methods: RNA sequencing, whole-genome bisulfite sequencing, and whole exome sequencing were applied to identify transcriptomic, epigenomic, and genomic underpinnings among 11 soft and 11 stiff PA samples surgically resected from patients at Peking Union Medical College Hospital (PUMCH). GH3 cell line and xenograft PA model was used to demonstrate therapeutic effect of sunitinib, and atomic force microscopy (AFM) was used to detect the stiffness of tumors.

Results: Tumor microenvironment analyses and immunofluorescence staining indicated endothelial cells (ECs) and cancer-associated fibroblasts (CAFs) were more abundant in stiff PAs. Weighted gene coexpression network analysis identified the most critical stiffness-related gene (SRG) module, which was highly correlated with stiff phenotype, ECs and CAFs. Functional annotations suggested SRGs might regulate PA stiffness by regulating the development, differentiation, and apoptosis of ECs and CAFs and related molecular pathways. Aberrant DNA methylation and m6A RNA modifications were investigated to play crucial roles in regulating PA stiffness. Somatic mutation analysis revealed increased intratumoral heterogeneity and decreased response to immunotherapy in stiff tumors. Connectivity Map analysis of SRGs and pRRophetic algorithm based on drug sensitivity data of cancer cell lines finally determine sunitinib as a promising agent targeting stiff tumors. Sunitinib inhibited PA growth in vitro and in vivo, and also reduced tumor stiffness in xenograft PA models detected by AFM.

Conclusion: This is the first study investigating the underlying mechanisms contributing to the stiffening of PAs, and providing novel insights into medication therapy for stiff PAs.

Magnetic Resonance Elastography in Intracranial Neoplasms: A Scoping Review

BACKGROUND

Magnetic resonance elastography (MRE) allows noninvasive assessment of intracranial tumor mechanics and may thus be predictive of intraoperative conditions. Variations in the use of technical terms complicate reading of current literature, and there is need of a review using consolidated nomenclature.

OBJECTIVES

We present an overview of current literature on MRE relating to human intracranial neoplasms using standardized nomenclature suggested by the MRE guidelines committee. We then discuss the implications of the findings, and suggest approaches for future research.

METHOD

We performed a systematic literature search in PubMed, Embase, and Web of Science; the articles were screened for relevance and then subjected to full text review. Technical terms were consolidated.

RESULTS

We identified 12 studies on MRE in patients with intracranial tumors, including meningiomas, glial tumors including glioblastomas, vestibular schwannomas, hemangiopericytoma, central nervous system lymphoma, pituitary macroadenomas, and brain metastases. The studies had varying objectives that included prediction of intraoperative consistency, histological separation, prediction of adhesiveness, and exploration of the mechanobiology of tumor invasiveness and malignancy. The technical terms were translated using standardized nomenclature. The literature was highly heterogeneous in terms of image acquisition techniques, post-processing, and study design and was generally limited by small and variable cohorts.

CONCLUSIONS

MRE shows potential in predicting tumor consistency, adhesion, and mechanical homogeneity. Furthermore, MRE provides insight into malignant tumor behavior and its relation to tissue mechanics. MRE is still at a preclinical stage, but technical advances, improved understanding of soft tissue rheological impact, and larger samples are likely to enable future clinical introduction.

Primary Tumors of the Pituitary Gland: Radiologic-Pathologic Correlation

Primary tumors of the pituitary gland are the second most common histologic category of primary central nervous system tumors across all age groups and are the most common in adolescents to young adults, despite originating from a diminutive endocrine gland that is often described as "about the size of a pea." The vast majority of these represent primary tumors of the adenohypophysis, specifically pituitary adenomas, which can be either functional or silent with regard to hormone hypersecretion. According to the fourth edition of the World Health Organization classification of endocrine tumors, published in 2017, cellular lineage and immunohistochemical stains for pituitary hormones and/or transcription factors help with making the correct pathologic diagnosis. From a radiologic standpoint, microadenomas pose challenges for accurate detection and avoiding false-negative or false-positive results, while macroadenomas pose challenges from local mass effect on surrounding structures. Pituitary carcinoma and pituitary blastoma also arise from the adenohypophysis and are characterized by metastatic disease and infantile presentation, respectively. While primary tumors of the adenohypophysis are common, a second category comprising primary tumors of the Rathke pouch (ie, craniopharyngioma) are uncommon, and a third category comprising primary tumors of the neurohypophysis (eg, pituicytoma) are rare. The authors review all three categories of pituitary tumors, with emphasis on radiologic-pathologic correlation, including the typical neuroimaging, histologic, and molecular features that may point toward a specific diagnosis. Work of the U.S. Government published under an exclusive license with the RSNA.

Effects of compressive lesions on intraoperative human spinal cord elasticity

OBJECTIVE

Although evaluating tissue elasticity has various clinical applications, spinal cord elasticity (SCE) in humans has never been well documented. In this study, the authors aimed to evaluate the impact of compression on human SCE in vivo.

METHODS

The authors prospectively assessed SCE using intraoperative shear wave elastography (SWE). All consecutive patients undergoing spinal cord (SC) decompression (laminectomy or corpectomy) between June 2018 and June 2019 were included. After intraoperative exposure of the patient's dura mater, at least three SWE measurements of the SC and its coverings were performed. Intraoperative neurological monitoring in the form of motor and somatosensory evoked potentials was utilized. Cases were divided into two groups based on the state of SC compression following bone removal (laminectomy or corpectomy): patients with adequate decompression (the decompressed SC group [DCG]) following bone removal and patients with remining compression, e.g., compressing tumor or instability (the compressed SC group [COG]).

RESULTS

A total of 25 patients were included (8 females and 17 males) with a mean age of 48.28 ± 21.47 years. Most cases were degenerative diseases (10 cases) followed by tumors (6 cases), and the compression was observed at cervical (n = 14), thoracic (n = 9), and conus medullaris (n = 2) levels. The COG (6 cases) expressed significantly higher elasticity values, i.e., greater stiffness (median 93.84, IQR 75.27-121.75 kPa) than the decompressed SC in DCG (median 9.35, IQR 6.95-11.22 kPa, p < 0.001). Similarly, the compressed dura mater in the COG was significantly stiffer (mean ± SD 121.83 ± 70.63 kPa) than that in the DCG (29.78 ± 18.31 kPa, p = 0.042). Following SC decompression in COG, SCE values were significantly reduced (p = 0.006; adjusted for multiple comparisons). Intraoperative monitoring demonstrated no worsening from the baseline.

CONCLUSIONS

The current study is to the authors' knowledge the first to quantitatively demonstrate increased stiffness (i.e., elasticity value) of the human SC and dura mater in response to external compression in vivo. It appears that SCE is a dynamic phenomenon and is reduced following decompression. Moreover, the evaluation of human SCE using the SWE technique is feasible and safe. Information from future studies aiming to further define SCE could be valuable in the early and accurate diagnosis of the compressed SC.

Virtual magnetic resonance elastography has the feasibility to evaluate preoperative pituitary adenoma consistency

PURPOSE

To evaluate the use of preoperative virtual Magnetic Resonance Elastography (vMRE) for patients undergoing transsphenoidal resection of pituitary adenomas (PA).

METHODS

Ten patients (60.2 ± 19.6 years; 8 males) were prospectively examined with the vMRE-method prior to transsphenoidal surgery. vMRE-images, reflecting tissue stiffness were reconstructed. From these images, histograms as well as the mean stiffness values over the tumor body were extracted. Finally, vMRE-data was compared with the PA consistency at surgery blinded to vMRE.

RESULTS

In all patients, successful vMRE-examination was performed enabling evaluation of even small PAs. For tumors with homogenous tissue, the mean stiffness value increased with surgical consistency grading. For heterogenous tumors, however, the mean stiffness value did not consistently reflect the grading at surgery. On the other hand, the vMRE-images and histograms were found to be able to characterize the tumor heterogeneity and display focal regions of high stiffness that were found to affect the surgery outcome in these PAs. The vMRE-images and histograms showed great promise in characterizing the consistency at surgery for these PAs.

CONCLUSION

Evaluation of PA consistency in preparation for surgery seems to be feasible using the vMRE-method. Our findings also address the need for high resolution diagnostic methods that can non-invasively display focal regions of increased stiffness, as such regions may increase the difficulty of transsphenoidal PA-resection.

Harnessing brain waves: a review of brain magnetic resonance elastography for clinicians and scientists entering the field

Brain magnetic resonance elastography (MRE) is an imaging technique capable of accurately and non-invasively measuring the mechanical properties of the living human brain. Recent studies have shown that MRE has potential to provide clinically useful information in patients with intracranial tumors, demyelinating disease, neurodegenerative disease, elevated intracranial pressure, and altered functional states. The objectives of this review are: (1) to give a general overview of the types of measurements that have been obtained with brain MRE in patient populations, (2) to survey the tools currently being used to make these measurements possible, and (3) to highlight brain MRE-based quantitative biomarkers that have the highest potential of being adopted into clinical use within the next 5 to 10 years. The specifics of MRE methodology strategies are described, from wave generation to material parameter estimations. The potential clinical role of MRE for characterizing and planning surgical resection of intracranial tumors and assessing diffuse changes in brain stiffness resulting from diffuse neurological diseases and altered intracranial pressure are described. In addition, the emerging technique of functional MRE, the role of artificial intelligence in MRE, and promising applications of MRE in general neuroscience research are presented.

Semi-supervised method for image texture classification of pituitary tumors via CycleGAN and optimized feature extraction

Background

Accurately determining the softness level of pituitary tumors preoperatively by using their image textures can provide a basis for surgical options and prognosis. Existing methods for this problem require manual intervention, which could hinder the efficiency and accuracy considerably.

Methods

We present an automatic method for diagnosing the texture of pituitary tumors using unbalanced sequence image data. Firstly, for the small sample problem in our pituitary tumor MRI image dataset where T1 and T2 sequence data are unbalanced (due to data missing) and under-sampled, our method uses a CycleGAN (Cycle-Consistent Adversarial Networks) model for domain conversion to obtain fully sampled MRI spatial sequence. Then, it uses a DenseNet (Densely Connected Convolutional Networks)-ResNet(Deep Residual Networks) based Autoencoder framework to optimize the feature extraction process for pituitary tumor image data. Finally, to take advantage of sequence data, it uses a CRNN (Convolutional Recurrent Neural Network) model to classify pituitary tumors based on their predicted softness levels.

Results

Experiments show that our method is the best in terms of efficiency and accuracy (91.78%) compared to other methods.

Conclusions

We propose a semi-supervised method for grading pituitary tumor texture. This method can accurately determine the softness level of pituitary tumors, which provides convenience for surgical selection and prognosis, and improves the diagnostic efficiency of pituitary tumors.

Advances in the Imaging of Pituitary Tumors

In most patients with pituitary adenomas magnetic resonance imaging (MRI) is essential to guide effective decision-making. T1- and T2-weighted sequences allow the majority of adenomas to be readily identified. Supplementary MR sequences (e.g. FLAIR; MR angiography) may also help inform surgery. However, in some patients MRI findings are 'negative' or equivocal (e.g. with failure to reliably identify a microadenoma or to distinguish postoperative change from residual/recurrent disease). Molecular imaging [e.g. ¹¹C-methionine PET/CT coregistered with volumetric MRI (Met-PET/MR^CR)] may allow accurate localisation of the site of de novo or persistent disease to guide definitive treatment (e.g. surgery or radiosurgery).

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.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

Background

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

Material/Methods

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

Results

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

Conclusions

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

REVIEW: MR elastography of brain tumors

•

MR elastography allows non-invasive quantification of the shear modulus of tissue.

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MRE correlates with intra-operative consistency of meningiomas, pituitary adenomas.

•

Reported shear modulus values are widely distributed and overlap.

•

Meningiomas were the stiffest tumor-type relative to normal appearing white matter.

•

Studies are needed to determine clinical applications of MRE in neuro-oncology.

MR elastography allows non-invasive quantification of the shear modulus of tissue, i.e. tissue stiffness and viscosity, information that offers the potential to guide presurgical planning for brain tumor resection. Here, we review brain tumor MRE studies with particular attention to clinical applications. Studies that investigated MRE in patients with intracranial tumors, both malignant and benign as well as primary and metastatic, were queried from the Pubmed/Medline database in August 2018. Reported tumor and normal appearing white matter stiffness values were extracted and compared as a function of tumor histopathological diagnosis and MRE vibration frequencies. Because different studies used different elastography hardware, pulse sequences, reconstruction inversion algorithms, and different symmetry assumptions about the mechanical properties of tissue, effort was directed to ensure that similar quantities were used when making inter-study comparisons. In addition, because different methodologies and processing pipelines will necessarily bias the results, when pooling data from different studies, whenever possible, tumor values were compared with the same subject's contralateral normal appearing white matter to minimize any study-dependent bias. The literature search yielded 10 studies with a total of 184 primary and metastatic brain tumor patients. The group mean tumor stiffness, as measured with MRE, correlated with intra-operatively assessed stiffness of meningiomas and pituitary adenomas. Pooled data analysis showed significant overlap between shear modulus values across brain tumor types. When adjusting for the same patient normal appearing white matter shear modulus values, meningiomas were the stiffest tumor-type. MRE is increasingly being examined for potential in brain tumor imaging and might have value for surgical planning. However, significant overlap of shear modulus values between a number of different tumor types limits applicability of MRE for diagnostic purposes. Thus, further rigorous studies are needed to determine specific clinical applications of MRE for surgical planning, disease monitoring and molecular stratification of brain tumors.

The Microenvironment of Pituitary Tumors-Biological and Therapeutic Implications

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

Modern imaging of pituitary adenomas

Decision-making in pituitary disease is critically dependent on high quality imaging of the sella and parasellar region. Magnetic resonance imaging (MRI) is the investigation of choice and, for the majority of patients, combined T1 and T2 weighted sequences provide the information required to allow surgery, radiotherapy (RT) and/or medical therapy to be planned and long-term outcomes to be monitored. However, in some cases standard clinical MR sequences are indeterminate and additional information is needed to help inform the choice of therapy for a pituitary adenoma (PA). This article reviews current recommendations for imaging of PA, examines the potential added value that alternative MR sequences and/or CT can offer, and considers how the use of functional/molecular imaging might allow definitive treatment to be recommended for a subset of patients who would otherwise be deemed unsuitable for (further) surgery and/or RT.

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

Background: Prediction of tumor consistency before surgery is of vital importance to determine individualized therapeutic schemes for patients with acromegaly. The present study was performed to noninvasively predict tumor consistency based on magnetic resonance imaging and radiomics analysis. Methods: In total, 158 patients with acromegaly were randomized into the primary cohort (n = 100) and validation cohort (n = 58). The consistency of the tumor was classified as soft or firm according to the neurosurgeon's evaluation. The critical radiomics features were determined using the elastic net feature selection algorithm, and the radiomics signature was constructed. The most valuable clinical characteristics were then selected based on the multivariable logistic regression analysis. Next, a radiomics model was developed using the radiomics signature and clinical characteristics, and 30 patients with acromegaly were recruited for multicenter validation of the radiomics model. The model's performance was evaluated based on the receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), accuracy, and other associated classification measures. Its calibration, discriminating capacity, and clinical usefulness were also evaluated. Results: The radiomics signature established according to four radiomics features screened in the primary cohort exhibited excellent discriminatory capacity in the validation cohort. The radiomics model, which incorporated both the radiomics signature and Knosp grade, displayed favorable discriminatory capacity and calibration, and the AUC was 0.83 (95% confidence interval, 0.81-0.85) and 0.81 (95% confidence interval, 0.78-0.83) in the primary and validation cohorts, respectively. Furthermore, compared with the clinical characteristics, the as-constructed radiomics model is more effective in prediction of the tumor consistency in patients with acromegaly. Moreover, the multicenter validation and decision curve analysis suggested that the radiomics model was clinically useful. Conclusions: This radiomics model can assist neurosurgeons in predicting tumor consistency in patients with acromegaly before surgery and facilitates the determination of individualized therapeutic schemes.

In vivo assessment of spinal cord elasticity using shear wave ultrasound in dogs

OBJECTIVE

Evaluation of living tissue elasticity has wide applications in disease characterization and prognosis prediction. Few previous ex vivo attempts have been made to characterize spinal cord elasticity (SCE). Recently, tissue elasticity assessment has been clinically feasible using ultrasound shear wave elastography (SWE). The current study aims to characterize SCE in healthy dogs, in vivo, utilizing SWE, and to address SCE changes during compression.

METHODS

Ten Greyhound dogs (mean age 14 months; mean weight 14.3 kg) were anesthetized and tracheally intubated, with hemodynamic and neurological monitoring. A 3-level, midcervical laminectomy was performed. SCE was assessed at baseline. Next, 8- and 13-mm balloon compressions were sequentially applied ventral to the spinal cord.

RESULTS

The mean SCE was 18.5 ± 7 kPa. Elasticity of the central canal, pia mater, and dura mater were 21.7 ± 9.6 kPa, 26.1 ± 14.8 kPa, and 63.2 ± 11.5 kPa, respectively. As expected, the spinal cord demonstrated less elasticity than the dura mater (p < 0.0001) and pia mater (trend toward significance p = 0.08). Notably, the 13-mm balloon compression resulted in a stiffer spinal cord than at baseline (233 ± 73 kPa versus 18.5 ± 7 kPa, p < 0.0001) and 8-mm balloon compression (233 ± 73 kPa versus 185 ± 68 kPa, p < 0.048).

CONCLUSIONS

In vivo SCE evaluation using SWE is feasible and comparable to earlier reports, as demonstrated by physical sectioning of the spinal cord. The compressed spinal cord is stiffer than a free spinal cord, with a linear increase in SCE with increasing mechanical compression. Knowledge of the biomechanical properties of the spinal cord including SCE has potential implications for disease management and prognosis.

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

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

Characterization of Small Renal Tumors With Magnetic Resonance Elastography: A Feasibility Study

OBJECTIVES

The aim of this study was to explore the feasibility of magnetic resonance elastography (MRE) for characterizing indeterminate small renal tumors (SRTs) as part of a multiparametric magnetic resonance (MR) imaging protocol.

MATERIALS AND METHODS

After institutional review board approval and informed consent were obtained, 21 prospective adults (15 men; median age, 55 years; age range, 25-72 years) with SRT were enrolled. Tumors (2-5 cm Ø) were imaged using 3-directional, gradient echo MRE. Viscoelastic parametric maps (shear wave velocity [c] and attenuation [α]) were analyzed by 2 independent radiologists. Interobserver agreement (Bland-Altman statistics and intraclass correlation coefficients) was assessed. Anatomical T2-weighted, dynamic contrast-enhanced (DCE) and diffusion sequences completed the acquisition protocol. Imaging parameters were compared between groups (Mann-Whitney U test).

RESULTS

Quality of MRE was good in 18 cases (mean nonlinearity <50%), including 1 papillary renal cell carcinoma and 1 metanephric adenoma. A cohort of 5 oncocytomas and 11 clear-cell renal cell carcinomas (ccRCCs) was analyzed for statistical differences. The MRE viscoelastic parameters were the strongest imaging discriminators: oncocytomas displayed significantly lower shear velocity c (median, 0.77 m/s; interquartile range [IQR], 0.76-0.79) (P = 0.007) and higher shear attenuation α (median, 0.087 mm; IQR, 0.082-0.087) (P = 0.008) than ccRCC (medians, 0.92 m/s and 0.066 mm; IQR, 0.84-0.97 and 0.054-0.074, respectively). T2 signal intensity ratio (tumor/renal cortex) was lower in oncocytomas (P = 0.02). The DCE and diffusion MR parameters overlapped substantially (P ≥ 0.1). Oncocytomas displayed a consistent MRE viscoelastic profile, corresponding to data point clustering in a bidimensional scatter plot. Values for MRE intraclass correlation coefficient were 0.982 for c and 0.984 for α, indicating excellent interobserver agreement.

CONCLUSIONS

Magnetic resonance elastography is feasible for SRT characterization; MRE viscoelastic parameters were stronger discriminators between oncocytoma and ccRCC than anatomical, DCE and diffusion MR imaging parameters.

Double dissociation of structure-function relationships in memory and fluid intelligence observed with magnetic resonance elastography

Brain tissue mechanical properties, measured in vivo with magnetic resonance elastography (MRE), have proven to be sensitive metrics of neural tissue integrity. Recently, our group has reported on the positive relationship between viscoelasticity of the hippocampus and performance on a relational memory task in healthy young adults, which highlighted the potential of sensitive MRE measures for studying brain health and its relation to cognitive function; however, structure-function relationships outside of the hippocampus have not yet been explored. In this study, we examined the relationships between viscoelasticity of both the hippocampus and the orbitofrontal cortex and performance on behavioral assessments of relational memory and fluid intelligence. In a sample of healthy, young adults (N = 53), there was a significant, positive relationship between orbitofrontal cortex viscoelasticity and fluid intelligence performance (r = 0.42; p = .002). This finding is consistent with the previously reported relationship between hippocampal viscoelasticity and relational memory performance (r = 0.41; p = .002). Further, a significant double dissociation between the orbitofrontal-fluid intelligence relationship and the hippocampal-relational memory relationship was observed. These data support the specificity of regional brain MRE measures in support of separable cognitive functions. This report of a structure-function relationship observed with MRE beyond the hippocampus suggests a future role for MRE as a sensitive neuroimaging technique for brain mapping.

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

OBJECTIVES

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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