Quantitative 3D Assessment of 68Ga-DOTATOC PET/MRI with Diffusion-Weighted Imaging to Assess Imaging Markers for Gastroenteropancreatic Neuroendocrine Tumors: Preliminary Results

An Illustrated Review of the Recent 2019 World Health Organization Classification of Neuroendocrine Neoplasms: A Radiologic and Pathologic Correlation

ABSTRACT

Recent advances in molecular pathology and an improved understanding of the etiology of neuroendocrine neoplasms (NENs) have given rise to an updated World Health Organization classification. Since gastroenteropancreatic NENs (GEP-NENs) are the most common forms of NENs and their incidence has been increasing constantly, they will be the focus of our attention. Here, we review the findings at the foundation of the new classification system, discuss how it impacts imaging research and radiological practice, and illustrate typical and atypical imaging and pathological findings. Gastroenteropancreatic NENs have a highly variable clinical course, which existing classification schemes based on proliferation rate were unable to fully capture. While well- and poorly differentiated NENs both express neuroendocrine markers, they are fundamentally different diseases, which may show similar proliferation rates. Genetic alterations specific to well-differentiated neuroendocrine tumors graded 1 to 3 and poorly differentiated neuroendocrine cancers of small cell and large-cell subtype have been identified. The new tumor classification places new demands and creates opportunities for radiologists to continue providing the clinically most relevant report and on researchers to design projects, which continue to be clinically applicable.

Advancements in Neuroendocrine Neoplasms: Imaging and Future Frontiers

Neuroendocrine neoplasms (NENs) are a diverse group of tumors with varying clinical behaviors. Their incidence has risen due to increased awareness, improved diagnostics, and aging populations. The 2019 World Health Organization classification emphasizes integrating radiology and histopathology to characterize NENs and create personalized treatment plans. Imaging methods like CT, MRI, and PET/CT are crucial for detection, staging, treatment planning, and monitoring, but each of them poses different interpretative challenges and none are immune to pitfalls. Treatment options include surgery, targeted therapies, and chemotherapy, based on the tumor type, stage, and patient-specific factors. This review aims to provide insights into the latest developments and challenges in NEN imaging, diagnosis, and management.

Neuroendocrine liver metastases treated using transarterial radioembolization: Identification of prognostic parameters at 68Ga-DOTATATE PET/CT

PURPOSE

To identify prognostic clinical and imaging parameters for patients with neuroendocrine liver metastases (NELMs) undergoing transarterial radioembolization (TARE).

MATERIALS AND METHODS

Forty-seven patients (27 men; mean age, 64 years) with NELMs who received TARE, along with pre-procedure liver MRI and 68Ga-DOTATATE positron emission tomography/computed tomography were included. Apparent diffusion coefficient and standardized uptake value (SUV) of three liver metastases, normal spleen and liver were measured. SUVmax or SUVmean were used for the calculation of tumor-to-organ ratios (tumor-to-spleen and tumor-to-liver ratios) using all possible combinations (including SUVmax/SUVmax, SUVmax/SUVmean, and SUVmean/SUVmean). Clinical parameters (hepatic tumor-burden, presence of extra-hepatic metastases, chromograninA, Ki-67 and bilirubin levels) were assessed. Overall survival, progression-free survival (PFS) and hepatic progression-free survival (HPFS) were calculated using Kaplan-Meier curves.

RESULTS

Median overall survival, PFS and HPFS were 49.6, 13.1 and 28.3 months, respectively. In multivariable Cox regression analysis, low Ki-67 (≤ 5%), low hepatic tumor-burden (< 10%), absence of extrahepatic metastases, and increased Tmean/Lmax ratio were significant prognostic factors of longer overall survival and HPFS. High baseline chromograninA (> 1330 ng/mL) was associated with shorter HPFS. Tmean/Lmax > 1.9 yielded a median overall survival of 69 vs. 33 months (P < 0.04), and a median HPFS of 30 vs. 19 months (P = 0.09). For PFS, high baseline SUVmax of NELMs was the single significant parameter in the multivariable model. SUVmax > 28 resulted in a median PFS of 16.9 vs. 6.5 months, respectively (P = 0.001).

CONCLUSION

High preinterventional Tmean/Lmax ratios, and high SUVmax on 68Ga-DOTATATE positron emission tomography/computed tomography seem to have prognostic value in patients with NELMs undergoing TARE, potentially aiding patient selection and management alongside conventional variables.

PET/MRI imaging in neuroendocrine neoplasm

Molecular imaging plays a vital role in the management of neuroendocrine neoplasms (NENs). Somatostatin receptor (SSTR) PET is critical for evaluating NENs, ascertaining peptide receptor radionuclide therapy (PRRT) eligibility, and treatment response. SSTR-PET/MRI can provide a one-stop-shop multiparametric evaluation of NENs. The acquisition of complementary imaging information in PET/MRI has distinct advantages over PET/CT and MR imaging acquisitions. The purpose of this manuscript is to provide a comprehensive overview of PET/MRI and a current review of recent PET/MRI advances in the diagnosis, staging, treatment, and surveillance of NENs.

Correlation of the apparent diffusion coefficient with the standardized uptake value in meningioma of the skull plane using [68]Ga-DOTATOC PET/MRI

PURPOSE

To evaluate a correlation between an MRI-specific marker for cellular density [apparent diffusion coefficient (ADC)] and the expression of Somatostatin Receptors (SSTR) in patients with meningioma of the skull plane and orbital space.

METHODS

68 Ga-DOTATOC PET/MR imaging was performed in 60 Patients with suspected or diagnosed meningiomas of the skull base and eye socket. Analysis of ADC values succeeded in 32 patients. ADC values (ADC mean and ADC min ) were analyzed using a polygonal region of interest. Tracer-uptake of target lesions was assessed according to corresponding maximal (SUV max ) and mean (SUV mean ) values. Correlations between assessed parameters were evaluated using the Pearson correlation coefficient.

RESULTS

One out of 32 patients (3%) was diagnosed with lymphoma by histopathological examination and therefore excluded from further analysis. Median ADC mean amounted to 822 × 10 -5  mm²/s -1 (95% CI: 570-1497) and median ADC min was 493 × 10 -5 mm 2 /s -1 (95% CI: 162-783). There were no significant correlations between SUV max and ADC min (r = 0.60; P  = 0.76) or ADC mean (r = -0.52; P  = 0.79), respectively. However, Pearson's test showed a weak, inverse but insignificant correlation between ADC mean and SUV mean (r = -0.33; P  = 0.07).

CONCLUSION

The presented data displays no relevant correlations between increased SSTR expression and cellularity in patients with meningioma of the skull base. SSTR-PET and DWI thus may offer complementary information on tumor characteristics of meningioma.

Introducing HDAC-Targeting Radiopharmaceuticals for Glioblastoma Imaging and Therapy

Despite recent advances in multimodality therapy for glioblastoma (GB) incorporating surgery, radiotherapy, chemotherapy and targeted therapy, the overall prognosis remains poor. One of the interesting targets for GB therapy is the histone deacetylase family (HDAC). Due to their pleiotropic effects on, e.g., DNA repair, cell proliferation, differentiation, apoptosis and cell cycle, HDAC inhibitors have gained a lot of attention in the last decade as anti-cancer agents. Despite their known underlying mechanism, their therapeutic activity is not well-defined. In this review, an extensive overview is given of the current status of HDAC inhibitors for GB therapy, followed by an overview of current HDAC-targeting radiopharmaceuticals. Imaging HDAC expression or activity could provide key insights regarding the role of HDAC enzymes in gliomagenesis, thus identifying patients likely to benefit from HDACi-targeted therapy.

A novel figure of merit to investigate 68Ga PET/CT image quality based on patient weight and lesion size using Q.Clear reconstruction algorithm: A phantom study

INTRODUCTION

Q.Clear is a Bayesian penalised-likelihood algorithm that uses a β-value for positron emission tomography(PET)/computed tomography(CT) image reconstruction(IR). Our study proposes a novel figure of merit, named CRBV, to compare the Q.Clear performances using 68Ga PET/CT image with the ordered-subset-expectation-maximization(OSEM) algorithm and to identify the optimal β-values for these images using two phantoms mimicking normal and overweight patients.

METHODS

NEMA IQ phantom with or without a ring of water-filled plastic bags (NEMAstd and NEMAow, respectively) was acquired and reconstructed with OSEM and Q.Clear at various β-values and minutes/bed position(min/bp). Contrast recovery(CR), background variability(BV) and CRBV were calculated. Highest CRBV values were used to identify optimal β-value ranges.

RESULTS

Q.Clear with 250 ≤ β ≤ 800 improved CRBV compared to OSEM for all the investigated spheres and acquisition setups. Outside of this range, Q.Clear still outperformed OSEM with few exceptions depending on spheres diameters and phantoms(e.g.,β-value = 1600 for diameters ≤ 17 mm using the NEMAow phantom). Regarding the CRBV performance for IR optimization, for the 4 min/bp NEMAstd IR, β-values = 300 ÷ 350 allowed to simultaneously optimize all diameters(except for the 10 mm); for the NEMAow IR, β-values = 350 ÷ 500 were needed for diameters > 20 mm, while β-values = 200 ÷ 250 were selected for the remaining diameters. For the 2 min/bp, β-value = 500 was suitable for diameters > 17 mm in both NEMAstd and NEMAow IR, while for smaller diameters β-value = 200 and β-values = 250 ÷ 350 were obtained for NEMAstd and NEMAow, respectively.

CONCLUSION

Almost all tested β-values of Q.Clear improved the CRBV compared to OSEM. In both phantoms, simulating normal and over-weight patients, optimal β-values were found according to lesion sizes and investigated acquisition times.

PET/CT and PET/MRI in neuroendocrine neoplasms

Advanced molecular imaging has come to play an integral role in the management of gastro-entero-pancreatic neuroendocrine neoplasms (GEP-NENs). Somatostatin receptor (SSTR) PET has now emerged as the reference standard for the evaluation of NENs and is particularly critical in the context of peptide receptor radionuclide therapy (PRRT) eligibility. SSTR PET/MRI with liver-specific contrast agent has a strong potential for one-stop-shop multiparametric evaluation of GEP-NENs. 18F-FDG is a complementary radiotracer to SSTR, especially in the context of high-grade neuroendocrine neoplasms. Knowledge gaps in quantitative evaluation of molecular imaging studies and their role in assessment of response to PRRT and combination therapies are active research areas. Novel radiotracers have the potential to overcome existing limitations in the molecular imaging of GEP-NENs. The purpose of this article is to provide an overview of the current trends, pitfalls, and recent advancements of molecular imaging for GEP-NENs.

The Diagnostic and Grading Accuracy of 68Ga-DOTATATE and 18F-FDG PET/MR for Pancreatic Neuroendocrine Neoplasms

Accurate diagnosis and grading are critical for pancreatic neuroendocrine neoplasm (pNEN) management. This study compares the diagnostic and grading value of ⁶⁸Ga-DOTATATE PET/MR and ¹⁸F-FDG PET/MR for pNENs separately as well as in combination. A total of 36 patients with histologically confirmed pNENs, who underwent both ⁶⁸Ga-DOTATATE PET/MR and ¹⁸F-FDG PET/MR within 2 weeks from 2020 to 2021, were retrospectively collected and analyzed. The maximum standardized uptake values of ⁶⁸Ga-DOTATATE (G-SUVmax) and ¹⁸F-FDG (F-SUVmax) on PET and the minimum values of apparent diffusion coefficient (ADCmin) on MR were measured on the lesions with known histological grading (25 by surgery, 11 by biopsy). Receiver-operating characteristic analysis was applied to determine the cutoffs of these parameters or their combinations for differentiation between G1 and G2, as well as between low-grade and high-grade pNENs. The Spearman rank correlation coefficient was used to assess the correlation between the imaging parameters and the maximum tumor diameters. The detection rate of ⁶⁸Ga-DOTATATE PET imaging alone was 95%, 87.5%, and 37.5% for G1, G2, and G3, respectively. Adding ¹⁸F-FDG PET or MR sequences of PET/MR increased the detection rate to 100% in all grades. Among the three parameters, G-SUVmax had the highest diagnostic rate in predicting tumor grade. It presented a sensitivity of 87.5% and a specificity of 80.0% with a cutoff value of 42.75 for differentiating G2 from G1 pNETs and a sensitivity and specificity of 100% and 71.4% with a cutoff value of 32.75 in predicting high-grade pNENs. The ratio of G-SUVmax to F-SUVmax (G-SUVmax/F-SUVmax) showed slight improvement in the diagnostic rate, while the product of G-SUVmax and ADCmin (G-SUVmax*ADCmin) did not improve the diagnostic rate. ⁶⁸Ga-DOTATATE PET/MR alone is sufficient for the diagnosis of pNENs and the prediction of various grades.

Added Value of Tomoelastography for Characterization of Pancreatic Neuroendocrine Tumor Aggressiveness Based on Stiffness

Simple Summary

The prediction of pancreatic neuroendocrine tumor (PNET) aggressiveness is important for treatment planning. The aim of this study was to evaluate the diagnostic performance of magnetic resonance elastography (MRE) with tomoelastography postprocessing (tomoelastography) in differentiating PNET from healthy pancreatic tissue and to correlate PNET stiffness with aggressiveness using asphericity derived from positron emission tomography (PET) as reference. In this prospective study we showed in a group of 13 patients with PNET that tomoelastography detected PNET by increased stiffness (p < 0.01) with a high diagnostic performance (AUC = 0.96). PNET was positively correlated with PET derived asphericity (r = 0.81). Tomoelastography provides quantitative imaging markers for the detection of PNET and the prediction of greater tumor aggressiveness by increased stiffness.

Abstract

Purpose: To evaluate the diagnostic performance of tomoelastography in differentiating pancreatic neuroendocrine tumors (PNETs) from healthy pancreatic tissue and to assess the prediction of tumor aggressiveness by correlating PNET stiffness with PET derived asphericity. Methods: 13 patients with PNET were prospectively compared to 13 age-/sex-matched heathy volunteers (CTR). Multifrequency MR elastography was combined with tomoelastography-postprocessing to provide high-resolution maps of shear wave speed (SWS in m/s). SWS of pancreatic neuroendocrine tumor (PNET-T) were compared with nontumorous pancreatic tissue in patients with PNET (PNET-NT) and heathy pancreatic tissue (CTR). The diagnostic performance of tomoelastography was evaluated by ROC-AUC analysis. PNET-SWS correlations were calculated with Pearson’s r. Results: SWS was higher in PNET-T (2.02 ± 0.61 m/s) compared to PNET-NT (1.31 ± 0.18 m/s, p < 0.01) and CTR (1.26 ± 0.09 m/s, p < 0.01). An SWS-cutoff of 1.46 m/s distinguished PNET-T from PNET-NT (AUC = 0.89; sensitivity = 0.85; specificity = 0.92) and a cutoff of 1.49 m/s differentiated pancreatic tissue of CTR from PNET-T (AUC = 0.96; sensitivity = 0.92; specificity = 1.00). The SWS of PNET-T was positively correlated with PET derived asphericity (r = 0.81; p = 0.01). Conclusions: Tomoelastography provides quantitative imaging markers for the detection of PNET and the prediction of greater tumor aggressiveness by increased stiffness.

Multimodality Imaging Review of Multiple Endocrine Neoplasia

OBJECTIVE. The purpose of this article is to review the clinical manifestations, endocrine tumors types, and multimodality diagnostic tools available to physicians involved in the management of patients with multiple endocrine neoplasia (MEN) syndrome, in addition to discussing relevant imaging findings and appropriate imaging follow-up. CONCLUSION. Thorough knowledge of the spectrum of tumors associated with MEN gene mutations aids in the screening, diagnostic workup, and posttreatment monitoring of patients with MEN-related gene mutations.

Somatostatin Receptor PET/CT Imaging for the Detection and Staging of Pancreatic NET: A Systematic Review and Meta-Analysis

We investigated the diagnostic performance of Somatostatin Receptor Positron Emission Tomography/Computed Tomography (SSR-PET/CT) for the detection of primary lesion and initial staging of pancreatic neuroendocrine tumors (pNETs). A comprehensive literature search up to January 2020 was performed selecting studies in presence of: sample size ≥10 patients; index test (i.e., 68Ga-DOTATOC or 68Ga-DOTANOC or 68Ga-DOTATATE PET/CT); and outcomes (i.e., detection rate (DR), true positive, true negative, false positive, and false-negative). The methodological quality was evaluated with QUADAS-2. Pooled DR and pooled sensitivity and specificity for the identification of the primary tumor were assessed by a patient-based and a lesion-based analysis. Thirty-eight studies were selected for the qualitative analysis, while 18 papers were included in the meta-analysis. The number of pNET patients ranged from 10 to 142, for a total of 1143 subjects. At patient-based analysis, the pooled sensitivity and specificity for the assessment of primary pNET were 79.6% (95% confidence interval (95%CI): 71–87%) and 95% (95%CI: 75–100%) with a heterogeneity of 59.6% and 51.5%, respectively. Pooled DR for the primary lesion was 81% (95%CI: 65–90%) and 92% (95%CI: 80–97%), respectively, at patient-based and lesion-based analysis. In conclusion, SSR-PET/CT has high DR and diagnostic performances for primary lesion and initial staging of pNETs.