PET/MR Imaging of Somatostatin Receptor Expression and Tumor Vascularity in Meningioma: Implications for Pathophysiology and Tumor Outcomes.

BACKGROUND AND PURPOSE: Meningiomas, the most common primary intracranial tumor, are vascular neoplasms that express somatostatin receptor-2 (SSTR2). The purpose of this investigation was to evaluate if a relationship exists between tumor vascularity and SSTR2 expression, which may play a role in meningioma prognostication and clinical management. MATERIALS AND METHODS: Gallium-68-DOTATATE PET/MRI with dynamic contrast-enhanced (DCE) perfusion was prospectively performed. Clinical and demographic patient characteristics were recorded. Tumor volumes were segmented and superimposed onto parametric DCE maps including flux rate constant (Kep), transfer constant (Ktrans), extravascular volume fraction (Ve), and plasma volume fraction (Vp). Meningioma PET standardized uptake value (SUV) and SUV ratio to superior sagittal sinus (SUVRSSS) were recorded. Pearson correlation analyses were performed. In a random subset, analysis was repeated by a second investigator, and intraclass correlation coefficients (ICCs) were determined. RESULTS: Thirty-six patients with 60 meningiomas (20 WHO-1, 27 WHO-2, and 13 WHO-3) were included. Mean Kep demonstrated a strong significant positive correlation with SUV (r = 0.84, p < 0.0001) and SUVRSSS (r = 0.81, p < 0.0001). When stratifying by WHO grade, this correlation persisted in WHO-2 (r = 0.91, p < 0.0001) and WHO-3 (r = 0.92, p = 0.0029) but not WHO-1 (r = 0.26, p = 0.4, SUVRSSS). ICC was excellent (0.97-0.99). CONCLUSION: DOTATATE PET/MRI demonstrated a strong significant correlation between tumor vascularity and SSTR2 expression in WHO-2 and WHO-3, but not WHO-1 meningiomas, suggesting biological differences in the relationship between tumor vascularity and SSTR2 expression in higher-grade meningiomas, the predictive value of which will be tested in future work.

The Emergency Radiology Dashboard: Facilitating Workflow With Realtime Data.

Emergency radiology imaging volume varies widely due to predictable (eg, day of the week) and unpredictable factors. This can lead to inefficient or insufficient staffing of radiologists, suboptimal workflow and poor trainee education. In collaboration with the radiology IT division we created and implemented a 2-tiered real-time dashboard to facilitate operational workflow. This allowed us to track overall emergency department patient census, ordered but not yet performed imaging studies, and performed but unread imaging studies. The capability of clicking to obtain information on specific studies was also incorporated. We describe our experience of how this information has improved our workflow, staffing, and trainee education.

Imaging-guided precision medicine in glioblastoma patients treated with immune checkpoint modulators: research trend and future directions in the field of imaging biomarkers and artificial intelligence.

Immunotherapies that employ immune checkpoint modulators (ICMs) have emerged as an effective treatment for a variety of solid cancers, as well as a paradigm shift in the treatment of cancers. Despite this breakthrough, the median survival time of glioblastoma patients has remained at about 2 years. Therefore, the safety and anti-cancer efficacy of combination therapies that include ICMs are being actively investigated. Because of the distinct mechanisms of ICMs, which restore the immune system's anti-tumor capacity, unconventional immune-related phenomena are increasingly being reported in terms of tumor response and progression, as well as adverse events. Indeed, immunotherapy response assessments for neuro-oncology (iRANO) play a central role in guiding cancer patient management and define a "wait and see strategy" for patients treated with ICMs in monotherapy with progressive disease on MRI. This article deciphers emerging research trends to ameliorate four challenges unaddressed by the iRANO criteria: (1) patient selection, (2) identification of immune-related phenomena other than pseudoprogression (i.e., hyperprogression, the abscopal effect, immune-related adverse events), (3) response assessment in combination therapies including ICM, and (4) alternatives to MRI. To this end, our article provides a structured approach for standardized selection and reporting of imaging modalities to enable the use of precision medicine by deciphering the characteristics of the tumor and its immune environment. Emerging preclinical or clinical innovations are also discussed as future directions such as immune-specific targeting and implementation of artificial intelligence algorithms.

Impact of a Structured Reporting Template on Adherence to Prostate Imaging Reporting and Data System Version 2 and on the Diagnostic Performance of Prostate MRI for Clinically Significant Prostate Cancer.

PURPOSE: The aim of this study was to assess the impact of a structured reporting template on adherence to the Prostate Imaging Reporting and Data System (PI-RADS) version 2 lexicon and on the diagnostic performance of prostate MRI to detect clinically significant prostate cancer (CS-PCa). METHODS: An imaging database was searched for consecutive patients who underwent prostate MRI followed by MRI-ultrasound fusion biopsy from October 2015 through October 2017. The initial MRI reporting template used included only subheadings. In July 2016, the template was changed to a standardized PI-RADS-compliant structured template incorporating dropdown menus. Lesion, patient characteristics, pathology, and adherence to the PI-RADS lexicon were extracted from MRI reports and patient charts. Diagnostic performance of prostate MRI to detect CS-PCa using combined ultrasound-MRI fusion and systematic biopsy as a reference standard was assessed. RESULTS: Three hundred twenty-four lesions in 202 patients (average age, 67 years; average prostate-specific antigen level, 5.9 ng/mL) were analyzed, including 217 MRI peripheral zone (PZ) lesions, 84 MRI non-PZ lesions, and 23 additional PZ lesions found on systematic biopsy but missed on MRI. Thirty-three percent (106 of 324) were CS-PCa. Adherence to the PI-RADS lexicon improved from 32.9% (50 of 152) to 88.4% (152 of 172) (P < .0001) after introduction of the structured template. The sensitivity of prostate MRI for CS-PCa in the PZ increased from 53% to 70% (P = .011). There was no significant change in specificity (60% versus 55%, P = .458). CONCLUSIONS: A structured template with dropdown menus incorporating the PI-RADS lexicon and classification rules improves adherence to PI-RADS and may increase the diagnostic performance of prostate MRI for CS-PCa.