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Purpose: Structural and functional alterations in tumor vasculature are thought to contribute to tumor hypoxia which is a primary driver of malignancy through its negative impact on the efficacy of radiation, immune surveillance, apoptosis, genomic stability, and accelerated angiogenesis. We performed a prospective, multicenter study to test the hypothesis that abnormal tumor vasculature and hypoxia, as measured with MRI and PET, will negatively impact survival in patients with newly diagnosed glioblastoma.Experimental Design: Prior to the start of chemoradiation, patients with glioblastoma underwent MRI scans that included dynamic contrast enhanced and dynamic susceptibility contrast perfusion sequences to quantitate tumor cerebral blood volume/flow (CBV/CBF) and vascular permeability (ktrans) as well as 18F-Fluoromisonidazole (18F-FMISO) PET to quantitate tumor hypoxia. ROC analysis and Cox regression models were used to determine the association of imaging variables with progression-free and overall survival.Results: Fifty patients were enrolled of which 42 had evaluable imaging data. Higher pretreatment 18F-FMISO SUVpeak (P = 0.048), mean ktrans (P = 0.024), and median ktrans (P = 0.045) were significantly associated with shorter overall survival. Higher pretreatment median ktrans (P = 0.021), normalized RCBV (P = 0.0096), and nCBF (P = 0.038) were significantly associated with shorter progression-free survival. SUVpeak [AUC = 0.75; 95% confidence interval (CI), 0.59–0.91], nRCBV (AUC = 0.72; 95% CI, 0.56–0.89), and nCBF (AUC = 0.72; 95% CI, 0.56–0.89) were predictive of survival at 1 year.Conclusions: Increased tumor perfusion, vascular volume, vascular permeability, and hypoxia are negative prognostic markers in newly diagnosed patients with gioblastoma, and these important physiologic markers can be measured safely and reliably using MRI and 18F-FMISO PET. Clin Cancer Res; 22(20); 5079–86. ©2016 AACR.

Supplemental Table 1: Participating centers that enrolled patients; Supplemental Table 2: Serial FMISO PET Imaging.

Background In Radiation Therapy Oncology Group (RTOG) 0825, a phase III trial of standard therapy with bevacizumab or without (placebo) in newly diagnosed glioblastoma, 44 patients underwent dynamic contrast enhanced (DCE) and/or dynamic susceptibility contrast (DSC) MRI in the American College of Radiology Imaging Network (ACRIN) trial 6686. The association between early changes in relative cerebral blood volume (rCBV) and volume transfer constant (Ktrans) with overall survival (OS) was evaluated. Methods MRI was performed at postop baseline (S0), immediately before (S1), 1 day after (S2), and 7 weeks after (S3) bevacizumab or placebo initiation. Mean normalized and standardized rCBV (nRCBV, sRCBV) and Ktrans were measured within contrast-enhancing lesion. Wilcoxon rank sum tests compared parameter changes from S1–S2 and S1–S3. Association with OS and progression-free survival (PFS) were determined using Kaplan–Meier and log-rank tests. Treatment response for groups stratified by pretreatment nRCBV (S0, S1) was explored. The intraclass correlation coefficient and repeatability coefficient for the placebo arm (S1–S2) were used to assess repeatability. Results Evaluable were 27–36 datasets per time point. Significant differences between treatment arms were found for changes in nRCBV and sRCBV from S1–S2 and S1–S3, and in Ktrans for S1–S3. Improved PFS (P = 0.05) but not OS (P = 0.46) was observed. High pretreatment rCBV predicted improved OS for bevacizumab-treated patients. Based on the intraclass correlation coefficient, sRCBV (0.92) was more repeatable than nRCBV (0.71) and Ktrans (0.75), consistent with repeatability coefficient values. Conclusions Bevacizumab significantly changes rCBV but not Ktrans as early as 1 day posttreatment in newly diagnosed glioblastoma unrelated to outcomes. Improvements in clinical trial design to maximize rCBV benefit are indicated.

Despite the widespread clinical use of dynamic susceptibility contrast (DSC) MRI, DSC-MRI methodology has not been standardized, hindering its utilization for response assessment in multicenter trials. Recently, the DSC-MRI Standardization Subcommittee of the Jumpstarting Brain Tumor Drug Development Coalition issued an updated consensus DSC-MRI protocol compatible with the standardized brain tumor imaging protocol (BTIP) for high-grade gliomas that is increasingly used in the clinical setting and is the default MRI protocol for the National Clinical Trials Network. After reviewing the basis for controversy over DSC-MRI protocols, this paper provides evidence-based best practices for clinical DSC-MRI as determined by the Committee, including pulse sequence (gradient echo vs spin echo), BTIP-compliant contrast agent dosing (preload and bolus), flip angle (FA), echo time (TE), and post-processing leakage correction. In summary, full-dose preload, full-dose bolus dosing using intermediate (60°) FA and field strength-dependent TE (40–50 ms at 1.5 T, 20–35 ms at 3 T) provides overall best accuracy and precision for cerebral blood volume estimates. When single-dose contrast agent usage is desired, no-preload, full-dose bolus dosing using low FA (30°) and field strength-dependent TE provides excellent performance, with reduced contrast agent usage and elimination of potential systematic errors introduced by variations in preload dose and incubation time.

A recent meeting was held on March 22, 2019, among the FDA, clinical scientists, pharmaceutical and biotech companies, clinical trials cooperative groups, and patient advocacy groups to discuss challenges and potential solutions for increasing development of therapeutics for central nervous system metastases. A key issue identified at this meeting was the need for consistent tumor measurement for reliable tumor response assessment, including the first step of standardized image acquisition with an MRI protocol that could be implemented in multicenter studies aimed at testing new therapeutics. This document builds upon previous consensus recommendations for a standardized brain tumor imaging protocol (BTIP) in high-grade gliomas and defines a protocol for brain metastases (BTIP-BM) that addresses unique challenges associated with assessment of CNS metastases. The “minimum standard” recommended pulse sequences include: (i) parameter matched pre- and post-contrast inversion recovery (IR)–prepared, isotropic 3D T1-weighted gradient echo (IR-GRE); (ii) axial 2D T2-weighted turbo spin echo acquired after injection of gadolinium-based contrast agent and before post-contrast 3D T1-weighted images; (iii) axial 2D or 3D T2-weighted fluid attenuated inversion recovery; (iv) axial 2D, 3-directional diffusion-weighted images; and (v) post-contrast 2D T1-weighted spin echo images for increased lesion conspicuity. Recommended sequence parameters are provided for both 1.5T and 3T MR systems. An “ideal” protocol is also provided, which replaces IR-GRE with 3D TSE T1-weighted imaging pre- and post-gadolinium, and is best performed at 3T, for which dynamic susceptibility contrast perfusion is included. Recommended perfusion parameters are given.

BACKGROUND: ACRIN 6686/RTOG 0825 was a phase III trial of conventional chemoradiation plus adjuvant temozolomide with bevacizumab or without (placebo) in newly diagnosed glioblastoma. This study investigated whether changes in contrast-enhancing and fluid attenuated inversion recovery (FLAIR)–hyperintense tumor assessed by central reading prognosticate overall survival (OS). METHODS: Two hundred eighty-four patients (171 men; median age 57 y, range 19–79; 159 on bevacizumab) had MRI at post-op (baseline) and pre-cycle 4 of adjuvant temozolomide (22 wk post chemoradiation initiation). Four central readers measured bidimensional lesion enhancement (2D-T1) and FLAIR hyperintensity at both time points. Changes from baseline to pre-cycle 4 for both markers were dichotomized (increasing vs non-increasing). Cox proportional hazards model and Kaplan–Meier survival estimates were used for inference. RESULTS: Adjusting for treatment, increasing 2D-T1 (n = 262, hazard ratio [HR] = 2.07, 95% CI: 1.48–2.91, P < 0.0001) and FLAIR (n = 273, HR = 1.75, 95% CI: 1.26–2.41, P = 0.0008) significantly predicted worse OS. Median OS (days) was significantly shorter for patients with increasing versus non-increasing 2D-T1 for both bevacizumab (443 vs 535, P = 0.004) and placebo (526 vs 887, P = 0.001). Median OS was significantly shorter for patients with increasing versus non-increasing FLAIR for placebo (595 vs 872, P = 0.001), and trended similarly for bevacizumab (499 vs 535, P = 0.0935). Adjusting for 2D-T1 and treatment, increasing FLAIR represented significantly higher risk for death (HR = 1.59 [1.11–2.26], P = 0.01). CONCLUSION: Increased 2D-T1 significantly predicts worse OS in both treatment groups, implying absence of a substantial proportion of pseudoprogression 22 weeks after initiation of standard therapy. FLAIR adds value beyond 2D-T1 in predicting OS, potentially addressing the pseudoresponse effect by substratifying bevacizumab-treated patients with non-increasing 2D-T1.

BACKGROUND Approximately 50% of patients with newly diagnosed high-grade glioma (HGG) develop progressive enhancement between their post-operative MRI scan and 12 weeks after radiation and temozolomide. Inter-reader variability on the assessment of progressive enhancement in this patient group is a significant barrier in designing multi-center biomarker trials to distinguish true progression from pseudoprogression. Although enhancement segmentation algorithms have become more widely available, more automated and reproducible techniques to identify patients who develop progressive enhancement are needed to facilitate acquisition of non-standard of care biomarkers when this occurs. We explored the feasibility of using a feature-based algorithm in tandem with freely available / open source automated segmentation algorithms to identify this subset of patients. METHODS An automated algorithm using subtraction of registered segmentations to detect new areas of localized thickness of enhancement was developed. Criteria for feasibility (50% within 95% CI of percent patients identified, and sensitivity of >85% of patients assessed as progressed [P+] identified) were determined prospectively. The algorithm was implemented across five different automated enhancement segmentation techniques, then evaluated using a retrospective dataset of 73 patients with newly diagnosed HGG (age 50.8±13.2 years, 37 men, 36 women, 50 GBM, 23 Grade III). Standardized post-baseline brain tumor imaging protocol MR acquisitions were obtained on 1.5T and 3T scanners (GE and Siemens). On chart review, 53% of patients were assessed by neuroradiologists and/or neuro-oncologists as P+ (progression vs. pseudoprogression). RESULTS 50% was within the 95% CI of percent of patients identified for all five segmentation algorithms. Sensitivity was over 85% for three segmentation algorithms, with the MIC-DKFZ algorithm having highest sensitivity of 92%. For this algorithm, specificity was 77%, PPV was 81% and NPV was 90%. CONCLUSION A feature-based algorithm in tandem with open source segmentation algorithms showed preliminary feasibility for automated identification of patients with progressive enhancement.

Validated biomarkers that more accurately predict prognosis and/or measure disease burden in patients with high-grade gliomas would help triage which treatment strategies are most promising for evaluation in Phase III multicenter trials. Multicenter trials to evaluate imaging biomarkers in this group face particular challenges; these trials have historically been slow to accrue and have not recently succeeded in validating new imaging biomarkers useful in treatment development. Due to variability in image acquisition protocols, scanner hardware, image analysis, and interpretive schemes, promising results obtained in single centers are poor predictors of success in the multicenter setting. Multicenter preliminary data to support further evaluation of imaging biomarkers is rarely available. The need for more efficient trial designs that bring multicenter data earlier into the process of biomarker development has become increasingly clear. In this presentation, the planning process within ECOG-ACRIN’s Brain Tumor Working Group for a platform multicenter trial called GABLE (Glioblastoma Accelerated Biomarker Learning Environment trial) designed to evaluate biomarkers for distinguishing pseudoprogression from true progression in patients with newly diagnosed GBM is described. In our planning process, it was determined that efficiencies can be gained from evaluating multiple biomarker types in parallel rather than serially; in the context of the proposed trial, not only conventional imaging biomarkers but plasma biomarkers and radiomic biomarkers can be evaluated simultaneously. Patient tolerance limits the feasibility of evaluating multiple non-standard-of-care imaging biomarkers in parallel. For this group of biomarkers, a “fast-switching” serial evaluation strategy using multiple interim analyses was developed to triage out biomarkers unlikely to succeed in identifying patient groups with clinically significant differences in median survival. For biomarker triage, an endpoint of event-free survival (events of either death or NANO progression) was proposed. Simulations were used to evaluate alpha and beta error using this evaluation strategy.

BACKGROUND AND PURPOSE: Brain tumor clinical trials requiring solid tumor assessment typically rely on the 2D manual delineation of enhancing tumors by ≥2 expert readers, a time-consuming step with poor interreader agreement. As a solution, we developed quantitative dT1 maps for the delineation of enhancing lesions. This retrospective analysis compares dT1 with 2D manual delineation of enhancing tumors acquired at 2 time points during the post therapeutic surveillance period of the American College of Radiology Imaging Network 6677/Radiation Therapy Oncology Group 0625 (ACRIN 6677/RTOG 0625) clinical trial. MATERIALS AND METHODS: Patients enrolled in ACRIN 6677/RTOG 0625, a multicenter, randomized Phase II trial of bevacizumab in recurrent glioblastoma, underwent standard MR imaging before and after treatment initiation. For 123 patients from 23 institutions, both 2D manual delineation of enhancing tumors and dT1 datasets were evaluable at weeks 8 (n = 74) and 16 (n = 57). Using dT1, we assessed the radiologic response and progression at each time point. Percentage agreement with adjudicated 2D manual delineation of enhancing tumor reads and association between progression status and overall survival were determined. RESULTS: For identification of progression, dT1 and adjudicated 2D manual delineation of enhancing tumor reads were in perfect agreement at week 8, with 73.7% agreement at week 16. Both methods showed significant differences in overall survival at each time point. When nonprogressors were further divided into responders versus nonresponders/nonprogressors, the agreement decreased to 70.3% and 52.6%, yet dT1 showed a significant difference in overall survival at week 8 (P = .01), suggesting that dT1 may provide greater sensitivity for stratifying subpopulations. CONCLUSIONS: This study shows that dT1 can predict early progression comparable with the standard method but offers the potential for substantial time and cost savings for clinical trials.

Background: Pediatric prolactinomas (PP) are rare but represent 50% of all pediatric pituitary adenomas. Girls are affected more frequently than boys, although PP tend to be larger and more aggressive (earlier age, larger mass, and higher prolactin levels) in boys. Thus, microadenomas (tumors < 10 mm in diameter) are typical in females and macroadenomas (10–40 mm in diameter) are typical in males. Giant prolactinomas (> 40 mm in maximum diameter), an unusual subset of macroprolactinomas, are also commonly found in boys. In a large case series, the largest tumor volume reported was 93.5 cm3. Here we report a giant prolactinoma in a female requiring V/P shunt for decompression. Clinical Case: A 16-year old female presented with 2 weeks of intractable headache, nausea and vomiting, vision impairment, and changes in balance described as running into stationary household objects. Historical review revealed primary amenorrhea and short stature. On initial exam, the patient had a right eye afferent pupillary defect, concern for loss of color vision, and bilateral optic nerve edema with blurred disc margins. Brain MRI showed a large lobulated mass centered in the suprasellar cistern, measuring approximately 6.4 x 5.8 x 5.7 cm with a tumor volume of 105 cm3. There was extension superiorly, anteriorly, and laterally, with homogeneously enhancing and cystic components, and mass effect resulting in obstructive hydrocephalus. Differential diagnoses included craniopharyngioma, germinoma, and adenoma. Initial tests demonstrated prolactin of >2,000 ng/mL, with diluted result of 17,811.16 ng/mL. Morning fasting labs confirmed multiple anterior pituitary hormone deficiencies including central hypothyroidism, ACTH deficiency, GH deficiency, and hypogonadotropic hypogonadism. The patient was started on hydrocortisone and levothyroxine. Due to obstructive hydrocephalus and vision impairment, she underwent VP shunt placement for decompression. She was started on cabergoline for medical treatment of the tumor and did not require surgical resection. Repeat prolactin measurements have shown striking improvement (to 2,350 ng/ml, 824 ng/ml, and 152 ng/ml at 1 week, 1-month, and 2-month-follow-up, respectively) with central vision improved in both eyes, papilledema resolved, and resolution of headaches. Conclusion: Giant prolactinomas presenting with hydrocephalus and intracranial hypertension are very rare in pediatrics, especially in girls, and can vary greatly in mass characteristics and resulting hormone deficiencies. Our patient is unique with her large tumor volume and the extent of pituitary hormone deficiencies. Prolactin levels should be measured with all sellar masses, as this may prevent unnecessary invasive intervention and possibly provide prompt response to medical management.

TPS2577 Background: Patients diagnosed with malignant high-grade gliomas (WHO grade III-IV) experience significant morbidity and mortality associated with these cancers. While the mainstay of therapy for patients with newly diagnosed high-grade glioma is surgery followed by concurrent chemotherapy and radiation therapy (RT), the outcomes remain very poor. BMX-001 (MnTnBuOE-2-PyP5+) is a metalloporphyrin with differential action in response to radiation therapy and chemotherapy-induced oxidative stress. Early preclinical studies demonstrated BMX-001’s ability to act as a radioprotectant to healthy tissue such as a central nervous white matter and as a radiosensitizer to cancer cells, in particular, human glioblastoma xenografts. We evaluated the safety of BMX-001 in combination with concurrent RT and temozolomide (TMZ) in a phase I study of newly diagnosed high-grade glioma patients, and we found that BMX-001 is safe and well-tolerated in this population. The maximum tolerated dose of BMX-001 during concurrent RT and TMZ was determined to be 28 mg delivered subcutaneously (SC) followed by 16 biweekly SC doses at 14 mg (Peters et al., Neuro-Oncology 2018). Methods: For this multi-site, open-label, phase II study (NCT02655601), we will randomize approximately 160 patients 1:1 to concurrent RT and TMZ with BMX-001 versus concurrent RT and TMZ alone. Key eligibility criteria include newly diagnosed histologically confirmed high-grade glioma (WHO III-IV), 18 ≥ years, and Karnofsky performance status ≥ 70%. The primary endpoint is overall survival. Secondary endpoints include cognitive performance as assessed by standardized cognitive testing, bone marrow protection, safety and tolerability, progression-free survival, overall tumor response rate, and plasma pharmacokinetics. Exploratory endpoints are health-related quality of life (as assessed by Functional Assessment of Cancer Therapy–Brain, Functional Assessment of Cancer Therapy-Cognition, and Functional Assessment of Chronic Illness Therapy-Fatigue), qualitative hair loss, and white matter integrity (as measured by MRI diffusion tensor/susceptibility imaging). Since November 2018, this phase II study has enrolled 64 of 160 high-grade glioma patients at six sites with future sites planned to be implemented. Clinical trial information: NCT02655601 .

PURPOSE: To evaluate factors contributing to interreader variation (IRV) in parameters measured at dynamic contrast material–enhanced (DCE) MRI in patients with glioblastoma who were participating in a multicenter trial. MATERIALS AND METHODS: A total of 18 patients (mean age, 57 years ± 13 [standard deviation]; 10 men) who volunteered for the advanced imaging arm of ACRIN 6677, a substudy of the RTOG 0625 clinical trial for recurrent glioblastoma treatment, underwent analyzable DCE MRI at one of four centers. The 78 imaging studies were analyzed centrally to derive the volume transfer constant (K(trans)) for gadolinium between blood plasma and tissue extravascular extracellular space, fractional volume of the extracellular extravascular space (v(e)), and initial area under the gadolinium concentration curve (IAUGC). Two independently trained teams consisting of a neuroradiologist and a technologist segmented the enhancing tumor on three-dimensional spoiled gradient-recalled acquisition in the steady-state images. Mean and median parameter values in the enhancing tumor were extracted after registering segmentations to parameter maps. The effect of imaging time relative to treatment, map quality, imager magnet and sequence, average tumor volume, and reader variability in tumor volume on IRV was studied by using intraclass correlation coefficients (ICCs) and linear mixed models. RESULTS: Mean interreader variations (± standard deviation) (difference as a percentage of the mean) for mean and median IAUGC, mean and median K(trans), and median v(e) were 18% ± 24, 17% ± 23, 27% ± 34, 16% ± 27, and 27% ± 34, respectively. ICCs for these metrics ranged from 0.90 to 1.0 for baseline and from 0.48 to 0.76 for posttreatment examinations. Variability in reader-derived tumor volume was significantly related to IRV for all parameters. CONCLUSION: Differences in reader tumor segmentations are a significant source of interreader variation for all dynamic contrast-enhanced MRI parameters. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by Wolf in this issue.

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Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has been correlated with prognosis in head and neck squamous cell carcinoma as well as with changes in normal tissues. These studies implement different software, either commercial or in-house, and different scan protocols. Thus, the generalizability of the results is not confirmed. To assist in the standardization of quantitative metrics to confirm the generalizability of these previous studies, this data descriptor delineates in detail the DCE-MRI digital imaging and communications in medicine (DICOM) files with DICOM radiation therapy (RT) structure sets and digital reference objects (DROs), as well as, relevant clinical data that encompass a data set that can be used by all software for comparing quantitative metrics. Variable flip angle (VFA) with six flip angles and DCE-MRI scans with a temporal resolution of 5.5 s were acquired in the axial direction on a 3T MR scanner with a field of view of 25.6 cm, slice thickness of 4 mm, and 256×256 matrix size.

Although investigators in the imaging community have been active in developing and evaluating quantitative imaging biomarkers (QIBs), the development and implementation of QIBs have been hampered by the inconsistent or incorrect use of terminology or methods for technical performance and statistical concepts. Technical performance is an assessment of how a test performs in reference objects or subjects under controlled conditions. In this article, some of the relevant statistical concepts are reviewed, methods that can be used for evaluating and comparing QIBs are described, and some of the technical performance issues related to imaging biomarkers are discussed. More consistent and correct use of terminology and study design principles will improve clinical research, advance regulatory science, and foster better care for patients who undergo imaging studies.

The study goal was to determine whether changes in relative cerebral blood volume (rCBV) derived from dynamic susceptibility contrast (DSC) MRI are predictive of overall survival (OS) in patients with recurrent glioblastoma multiforme (GBM) when measured 2, 8, and 16 weeks after treatment initiation.Patients with recurrent GBM (37/123) enrolled in ACRIN 6677/RTOG 0625, a multicenter, randomized, phase II trial of bevacizumab with irinotecan or temozolomide, consented to DSC-MRI plus conventional MRI, 21 with DSC-MRI at baseline and at least 1 postbaseline scan. Contrast-enhancing regions of interest were determined semi-automatically using pre- and postcontrast T1-weighted images. Mean tumor rCBV normalized to white matter (nRCBV) and standardized rCBV (sRCBV) were determined for these regions of interest. The OS rates for patients with positive versus negative changes from baseline in nRCBV and sRCBV were compared using Wilcoxon rank-sum and Kaplan-Meier survival estimates with log-rank tests.Patients surviving at least 1 year (OS-1) had significantly larger decreases in nRCBV at week 2 (P = .0451) and sRCBV at week 16 (P = .014). Receiver operating characteristic analysis found the percent changes of nRCBV and sRCBV at week 2 and sRCBV at week 16, but not rCBV data at week 8, to be good prognostic markers for OS-1. Patients with positive change from baseline rCBV had significantly shorter OS than those with negative change at both week 2 and week 16 (P = .0015 and P = .0067 for nRCBV and P = .0251 and P = .0004 for sRCBV, respectively).Early decreases in rCBV are predictive of improved survival in patients with recurrent GBM treated with bevacizumab.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provides quantitative metrics (e.g. Ktrans, ve) via pharmacokinetic models. We tested inter-algorithm variability in these quantitative metrics with 11 published DCE-MRI algorithms, all implementing Tofts-Kermode or extended Tofts pharmacokinetic models. Digital reference objects (DROs) with known Ktrans and ve values were used to assess performance at varying noise levels. Additionally, DCE-MRI data from 15 head and neck squamous cell carcinoma patients over 3 time-points during chemoradiotherapy were used to ascertain Ktrans and ve kinetic trends across algorithms. Algorithms performed well (less than 3% average error) when no noise was present in the DRO. With noise, 87% of Ktrans and 84% of ve algorithm-DRO combinations were generally in the correct order. Low Krippendorff’s alpha values showed that algorithms could not consistently classify patients as above or below the median for a given algorithm at each time point or for differences in values between time points. A majority of the algorithms produced a significant Spearman correlation in ve of the primary gross tumor volume with time. Algorithmic differences in Ktrans and ve values over time indicate limitations in combining/comparing data from distinct DCE-MRI model implementations. Careful cross-algorithm quality-assurance must be utilized as DCE-MRI results may not be interpretable using differing software.

Quantitative biomarkers from medical images are becoming important tools for clinical diagnosis, staging, monitoring, treatment planning, and development of new therapies. While there is a rich history of the development of quantitative imaging biomarker (QIB) techniques, little attention has been paid to the validation and comparison of the computer algorithms that implement the QIB measurements. In this paper we provide a framework for QIB algorithm comparisons. We first review and compare various study designs, including designs with the true value (e.g. phantoms, digital reference images, and zero-change studies), designs with a reference standard (e.g. studies testing equivalence with a reference standard), and designs without a reference standard (e.g. agreement studies and studies of algorithm precision). The statistical methods for comparing QIB algorithms are then presented for various study types using both aggregate and disaggregate approaches. We propose a series of steps for establishing the performance of a QIB algorithm, identify limitations in the current statistical literature, and suggest future directions for research.

RTOG 0625/ACRIN 6677 is a multicenter, randomized, phase II trial of bevacizumab with irinotecan or temozolomide in recurrent glioblastoma (GBM). This study investigated whether early posttreatment progression on FLAIR or postcontrast MRI assessed by central reading predicts overall survival (OS).Of 123 enrolled patients, 107 had baseline and at least 1 posttreatment MRI. Two central neuroradiologists serially measured bidimensional (2D) and volumetric (3D) enhancement on postcontrast T1-weighted images and volume of FLAIR hyperintensity. Progression status on all posttreatment MRIs was determined using Macdonald and RANO imaging threshold criteria, with a third neuroradiologist adjudicating discrepancies of both progression occurrence and timing. For each MRI pulse sequence, Kaplan-Meier survival estimates and log-rank test were used to compare OS between cases with or without radiologic progression.Radiologic progression occurred after 2 chemotherapy cycles (8 weeks) in 9 of 97 (9%), 9 of 73 (12%), and 11 of 98 (11%) 2D-T1, 3D-T1, and FLAIR cases, respectively, and 34 of 80 (43%), 21 of 58 (36%), and 37 of 79 (47%) corresponding cases after 4 cycles (16 weeks). Median OS among patients progressing at 8 or 16 weeks was significantly less than that among nonprogressors, as determined on 2D-T1 (114 vs 278 days and 214 vs 426 days, respectively; P.0001 for both) and 3D-T1 (117 vs 306 days [P.0001] and 223 vs 448 days [P = .0003], respectively) but not on FLAIR (201 vs 276 days [P = .38] and 303 vs 321 days [P = .13], respectively).Early progression on 2D-T1 and 3D-T1, but not FLAIR MRI, after 8 and 16 weeks of anti-vascular endothelial growth factor therapy has highly significant prognostic value for OS in recurrent GBM.

The prognosis for patients with recurrent glioblastoma remains poor. The purpose of this study was to assess the potential role of MR spectroscopy as an early indicator of response to anti-angiogenic therapy.Thirteen patients with recurrent glioblastoma were enrolled in RTOG 0625/ACRIN 6677, a prospective multicenter trial in which bevacizumab was used in combination with either temozolomide or irinotecan. Patients were scanned prior to treatment and at specific timepoints during the treatment regimen. Postcontrast T1-weighted MRI was used to assess 6-month progression-free survival. Spectra from the enhancing tumor and peritumoral regions were defined on the postcontrast T1-weighted images. Changes in the concentration ratios of n-acetylaspartate/creatine (NAA/Cr), choline-containing compounds (Cho)/Cr, and NAA/Cho were quantified in comparison with pretreatment values.NAA/Cho levels increased and Cho/Cr levels decreased within enhancing tumor at 2 weeks relative to pretreatment levels (P = .048 and P = .016, respectively), suggesting a possible antitumor effect of bevacizumab with cytotoxic chemotherapy. Nine of the 13 patients were alive and progression free at 6 months. Analysis of receiver operating characteristic curves for NAA/Cho changes in tumor at 8 weeks revealed higher levels in patients progression free at 6 months (area under the curve = 0.85), suggesting that NAA/Cho is associated with treatment response. Similar results were observed for receiver operating characteristic curve analyses against 1-year survival. In addition, decreased Cho/Cr and increased NAA/Cr and NAA/Cho in tumor periphery at 16 weeks posttreatment were associated with both 6-month progression-free survival and 1-year survival.Changes in NAA and Cho by MR spectroscopy may potentially be useful as imaging biomarkers in assessing response to anti-angiogenic treatment.

A major initiative of the Quantitative Imaging Biomarker Alliance (QIBA) is to develop standards-based documents called “Profiles”, which describe one or more technical performance claims for a given imaging modality. The term “actor” denotes any entity (device, software, person) whose performance must meet certain specifications in order for the claim to be met. The objective of this paper is to present the statistical issues in testing actors’ conformance with the specifications. In particular, we present the general rationale and interpretation of the claims, the minimum requirements for testing whether an actor achieves the performance requirements, the study designs used for testing conformity, and the statistical analysis plan. We use three examples to illustrate the process: apparent diffusion coefficient (ADC) in solid tumors measured by MRI, change in Perc 15 as a biomarker for the progression of emphysema, and percent change in solid tumor volume by CT as a biomarker for lung cancer progression.

The aim of this study was to determine the prognostic significance of changes in parameters derived from diffusion tensor imaging (DTI) that occur in response to treatment with bevacizumab and irinotecan in patients with recurrent glioblastoma multiforme.15 patients with recurrent glioblastoma multiforme underwent serial 1.5 T MRI. Axial single-shot echo planar DTI was obtained on scans performed 3 days and 1 day prior to and 6 weeks after initiation of therapy with bevacizumab and irinotecan. Apparent diffusion coefficient (ADC) and fractional anisotropy (FA) maps were registered to whole brain contrast-enhanced three-dimensional (3D) spoiled gradient recalled and 3D fluid attenuation inversion recovery (FLAIR) image volumes. Anatomic image volumes were segmented to isolate regions of interest defined by tumour-related enhancement (TRE) and FLAIR signal abnormality (FSA). Mean ADC and mean FA were calculated for each region. A Bland-Altman repeatability coefficient was also calculated for each parameter based on the two pre-treatment studies. A patient was considered to have a change in FA or ADC after therapy if the difference between the pre- and post-treatment values was greater than the repeatability coefficient for that parameter. Survival was compared using a Cox proportional hazard model.DTI detected a change in ADC within FSA after therapy in nine patients (five in whom ADC was increased; four in whom it was decreased). Patients with a change in ADC within FSA had significantly shorter overall survival (p=0.032) and progression free survival (p=0.046) than those with no change.In patients with recurrent glioblastoma multiforme treated with bevacizumab and irinotecan, a change in ADC after therapy in FSA is associated with decreased survival.

Purpose Dynamic contrast–enhanced (DCE) MRI-extracted parameters measure tumor microvascular physiology and are usually calculated from an intratumor region of interest (ROI). Optimal ROI delineation is not established. The valid clinical use of DCE-MRI requires that the variation for any given parameter measured within a tumor be less than that observed between tumors in different patients. This work evaluates the impact of tumor ROI selection on the assessment of intra- and interpatient variability. Method and Materials Head and neck cancer patients received initial targeted therapy (TT) treatment with erlotinib and/or bevacizumab, followed by radiotherapy and concurrent cisplatin with synchronous TT. DCE-MRI data from Baseline and the end of the TT regimen (Lead-In) were analyzed to generate the vascular transfer function (K trans ), the extracellular volume fraction (v e ), and the initial area under the concentration time curve (iAUC 1 min ). Four ROI sampling strategies were used: whole tumor or lymph node (Whole), the slice containing the most enhancing voxels (SliceMax), three slices centered in SliceMax (Partial), and the 5% most enhancing contiguous voxels within SliceMax (95Max). The average coefficient of variation (aCV) was calculated to establish intrapatient variability among ROI sets and interpatient variability for each ROI type. The average ratio between each intrapatient CV and the interpatient CV was calculated (aRCV). Results Baseline primary/nodes aRCVs for different ROIs not including 95Max were, for all three MR parameters, in the range of 0.14–0.24, with Lead-In values between 0.09 and 0.2, meaning a low intrapatient vs. interpatient variation. For 95Max, intrapatient CVs approximated interpatient CVs, meaning similar data dispersion and higher aRCVs (0.6–1.27 for baseline) and 0.54–0.95 for Lead-In. Conclusion Distinction between different patient’s primary tumors and/or nodes cannot be made using 95Max ROIs. The other three strategies are viable and equivalent for using DCE-MRI to measure head and neck cancer physiology.

Convection-enhanced delivery (CED) permits site-specific therapeutic drug delivery within interstitial spaces at increased dosages through circumvention of the blood-brain barrier. CED is currently limited by suboptimal methodologies for monitoring the delivery of therapeutic agents that would permit technical optimization and enhanced therapeutic efficacy.To determine whether a readily available small-molecule MRI contrast agent, gadolinium-diethylene triamine pentaacetic acid (Gd-DTPA), could effectively track the distribution of larger therapeutic agents.Gd-DTPA was coinfused with the larger molecular tracer, I-labeled human serum albumin (I-HSA), during CED of an EGFRvIII-specific immunotoxin as part of treatment for a patient with glioblastoma.Infusion of both tracers was safe in this patient. Analysis of both Gd-DTPA and I-HSA during and after infusion revealed a high degree of anatomical and volumetric overlap.Gd-DTPA may be able to accurately demonstrate the anatomic and volumetric distribution of large molecules used for antitumor therapy with high resolution and in combination with fluid-attenuated inversion recovery (FLAIR) imaging, and provide additional information about leaks into cerebrospinal fluid spaces and resection cavities. Similar studies should be performed in additional patients to validate our findings and help refine the methodologies we used.

Purpose: Calculation of the precontrast longitudinal relaxation times T10 is an integral part of the Tofts-based pharmacokinetic PK analysis of dynamic contrast enhanced–magnetic resonance images. The purpose of this study was to investigate the interpatient and over time variability of T10 in head and neck primary tumors and involved nodes and to determine the median T10 for primary and nodes T 10 p,n . The authors also looked at the implication of using voxel-based T10 values versus region of interest ROI-based T10 on the calculated values for vascular permeability K trans and extracellular volume fraction ve. Methods: Twenty head and neck cancer patients receiving concurrent chemoradiation and molecularly targeted agents on a prospective trial comprised the study population. Voxel-based T10’s were generated using a gradient echo sequence on a 1.5 T MR scanner using the variable flip angle method with two flip angles J. A. Brookes et al., “Measurement of spin-lattice relaxation times with FLASH for dynamic MRI of the breast,” Br. J. Radiol. 69, 206–214 1996. The voxel-based T10, K trans , and ve were calculated using iCAD’s ® Nashua, NH software. The mean T10’s in muscle and fat ROIs were calculated T10 m,f . To assess reliability of ROI drawing, T10 p,n values from ROIs delineated by 2 users A and B were calculated as the average of the T10’s for 14 patients. For a subset of three patients, the T10 variability from baseline to end of treatment was also investigated. The K trans and ve from primary and node ROIs were calculated using voxel-based T10 values and T 10 p,n and differences reported. Results: The calculated T 10 values for fat and muscle are within the range of values reported in literature for 1.5 T, i.e., T 10 m = 0.958 s and T 10 f = 0.303 s. The average over 14 patients of the T10’s based on drawings by users A and B were T 10 pA = 0.804 s, T 10 nA = 0.760 s, T 10 pB = 0.849 s, and T10 nB = 0.810 s. The absolute percentage difference between K trans and ve calculated with voxelbased T10 versus T 10 p,n ranged from 6% to 81% and from 2% to 24%, respectively. Conclusions: There is a certain amount of variability in the median T10 values between patients, but the differences are not significant. There were also no statistically significant differences between the T10 values for primary and nodes at baseline and the subsequent time points p = 0.94 Friedman test. Voxel-based T10 calculations are essential when quantitative Tofts-based PK analysis in heterogeneous tumors is needed. In the absence of T10 mapping capability, when a relative, qualitative analysis is deemed sufficient, a value of T 10 p,n = 0.800 s can be used as an estimate for T10 for both the primary tumor and the affected nodes in head and neck cancers at all the time points considered. © 2010 American Association of Physicists in Medicine. DOI: 10.1118/1.3427487

RATIONALE: Early detection of tumor response to therapy is a key goal. Finding measurement algorithms capable of early detection of tumor response could individualize therapy treatment as well as reduce the cost of bringing new drugs to market. On an individual basis, the urgency arises from the desire to prevent continued treatment of the patient with a high-cost and/or high-risk regimen with no demonstrated individual benefit and rapidly switch the patient to an alternative efficacious therapy for that patient. In the context of bringing new drugs to market, such algorithms could demonstrate efficacy in much smaller populations, which would allow phase 3 trials to achieve statistically significant decisions with fewer subjects in shorter trials. MATERIALS AND METHODS: This consensus-based article describes multiple, image modality-independent means to assess the relative performance of algorithms for measuring tumor change in response to therapy. In this setting, we describe specifically the example of measurement of tumor volume change from anatomic imaging as well as provide an overview of other promising generic analytic methods that can be used to assess change in heterogeneous tumors. To support assessment of the relative performance of algorithms for measuring small tumor change, data sources of truth are required. RESULTS: Very short interval clinical imaging examinations and phantom scans provide known truth for comparative evaluation of algorithms. CONCLUSIONS: For a given category of measurement methods, the algorithm that has the smallest measurement noise and least bias on average will perform best in early detection of true tumor change.

This article describes methods and issues that are specific to the assessment of change in tumor characteristics as measured using quantitative magnetic resonance (MR) techniques and how this relates to the establishment of quantitative MR imaging (MRI) biomarkers of patient response to therapy. The initial focus is on the various sources of bias and variance in the measurement of microvascular parameters and diffusion parameters as such parameters are being used relatively commonly as secondary or exploratory end points in current phase 1/2 clinical trails of conventional and targeted therapies. Several ongoing initiatives that seek to identify the magnitude of some of the sources of measurement variations are then discussed. Finally, resources being made available through the National Cancer Institute Reference Image Database to Evaluate Response (RIDER) project that might be of use in investigations of quantitative MRI biomarker change analysis are described. These resources include 1) data from phantom-based assessment of system response, including short-term (1 hour) and moderate-term (1 week) contrast response and relaxation time measurement, 2) data obtained from repeated dynamic contrast agent-enhanced MRI studies in intracranial tumors, and 3) data obtained from repeated diffusion MRI studies in both breast and brain. A concluding section briefly discusses issues that must be addressed to allow the transition of MR-based imaging biomarker measures from their current role as secondary/exploratory end points in clinical trials to primary/surrogate markers of response and, ultimately, in clinical application.

Repeat imaging data sets performed on patients with cancer are becoming publicly available. The potential utility of these data sets for addressing important questions in imaging biomarker development is vast. In particular, these data sets may be useful to help characterize the variability of quantitative parameters derived from imaging. This article reviews statistical analysis that may be performed to use results of repeat imaging to 1) calculate the level of change in parameter value that may be seen in individual patients to confidently characterize that patient as showing true parameter change, 2) calculate the level of change in parameters value that may be seen in individual patients to confidently categorize that patient as showing true lack of parameter change, 3) determine if different imaging devices are interchangeable from the standpoint of repeatability, and 4) estimate the numbers of patients needed to precisely calculate repeatability. In addition, we recommend a set of statistical parameters that should be reported when the repeatability of continuous parameters is studied.

Purpose To quantify the repeatability of apparent diffusion coefficient (ADC) and fractional anisotropy (FA) in patients with glioblastoma multiforme. Materials and Methods IRB approval and informed consent were obtained for this Health Insurance Portability and Accountability Act-compliant study. Sixteen patients with glioblastoma multiforme underwent MR imaging at two time points without interval intervention. ADC and FA maps were registered to the contrast-enhanced and fluid-attenuated inversion recovery (FLAIR) image volumes. Volumes of tumor-related enhancement (TRE) and FLAIR signal abnormality (FSA) were defined using a semiautomated segmentation technique. Results Repeated observations of mean ADC and mean FA were highly consistent within both TRE (ADC: r = 0.947,P < 0.0001; FA: r = 0.947, P < 0.0001) and FSA (ADC: r = 0.979, P < 0.0001; FA: r = 0.972, P < 0.0001). Within TRE, repeatability coefficients and 95% confidence intervals (CIs) for change measured 0.104 × 10−3 mm2S−1 and 7.4% (ADC) and 0.0196 and 13.9% (FA), respectively. Within FSA, repeatability coefficients and 95% CI for change measured 0.071 × 10−3 mm2S−1 and 5.2% (ADC) and 0.0159 and 8.7% (FA), respectively. To detect 10% changes in mean ADC, sample sizes of nine (TRE) and six (FSA) patients would be required. The same change in mean FA would require sample sizes of 21 (TRE) and 10 (FSA) patients, respectively. Conclusion Changes after therapy greater than the repeatability coefficient or 95% CI for change are unlikely to be related to variability in the measurement of ADC and FA. J. Magn. Reson. Imaging 2009;29:1199–1205. © 2009 Wiley-Liss, Inc.

To compare the performance of three physiologically-based pharmacokinetic (PBPK) models for predicting gadolinium contrast agent concentration-time curves (Gd-CTCs) obtained in superior sagittal sinus (SSS), cerebral cortex, and psoas muscle.Three published whole-body PBPK models were modified to predict Gd-CTCs in normal-appearing tissue. The models differed in the number of organs modeled and total number of compartments, and were designated as the "well-mixed," "delay," and "dispersion" models. The suitability of the three models to predict Gd-CTC was studied using data from dynamic contrast-enhanced MR perfusion imaging obtained at 1.5T from 10 patients with glioblastoma multiforme and at 3.0T from five patients with liver metastases.The dispersion model produced better fits than the delay model in the SSS (P0.0001) and cerebral cortex (P0.0001), and better fits than the well-mixed model in psoas muscle (P0.005). No model produced better fits than the dispersion model at any of the three locations.In this evaluation, the dispersion model was most robust for prediction of Gd-CTCs derived from dynamic contrast-enhanced (DCE)-MRI. This represents a preliminary step in the development of a PBPK model useful for predicting Gd-CTCs at a time resolution appropriate for dynamic MRI applications.

The objective of our study was to test the hypothesis that the finding of hyperintense hippocampal signal intensity on T2-weighted MR images soon after febrile status epilepticus is associated with subsequent hippocampal volume loss and persistent abnormal signal intensity on T2-weighted images (i.e., mesial temporal sclerosis).Eleven children (mean age, 25 months) underwent initial MRI that included coronal temporal lobe imaging within 72 hours of febrile status epilepticus and follow-up imaging from 3 to 23 months later (mean, 9 months). A neuroradiologist blinded to clinical history graded initial and follow-up hippocampal signal intensity on a scale from 0 (normal) to 4 (markedly increased). Two blinded observers measured hippocampal volumes on initial and follow-up MR studies using commercially available software and volumes from 30 healthy children (mean age, 6.3 years). Initial signal intensity and hippocampal volume changes were compared using Kendall tau correlation coefficients.On initial imaging, hyperintense signal intensity ranging from 1 (minimally increased) to 4 (markedly increased) was seen in seven children. Four children had at least one hippocampus with moderate or marked signal abnormality, three children had a hippocampus with mild or minimal abnormality, and four children had normal signal intensity. The Kendall tau correlation coefficient between signal intensity increase and volume change was -0.68 (p0.01). Five children (two with temporal lobe epilepsy and two with complex partial seizures) had hippocampal volume loss and increased signal intensity on follow-up imaging, meeting the criteria for mesial temporal sclerosis.MRI findings of a markedly hyperintense hippocampus in children with febrile status epilepticus was highly associated with subsequent mesial temporal sclerosis.

Purpose: Structural and functional alterations in tumor vasculature are thought to contribute to tumor hypoxia which is a primary driver of malignancy through its negative impact on the efficacy of radiation, immune surveillance, apoptosis, genomic stability, and accelerated angiogenesis. We performed a prospective, multicenter study to test the hypothesis that abnormal tumor vasculature and hypoxia, as measured with MRI and PET, will negatively impact survival in patients with newly diagnosed glioblastoma. Experimental Design: Prior to the start of chemoradiation, patients with glioblastoma underwent MRI scans that included dynamic contrast enhanced and dynamic susceptibility contrast perfusion sequences to quantitate tumor cerebral blood volume/flow (CBV/CBF) and vascular permeability (ktrans) as well as 18F-Fluoromisonidazole (18F-FMISO) PET to quantitate tumor hypoxia. ROC analysis and Cox regression models were used to determine the association of imaging variables with progression-free and overall survival. Results: Fifty patients were enrolled of which 42 had evaluable imaging data. Higher pretreatment 18F-FMISO SUVpeak (P = 0.048), mean ktrans (P = 0.024), and median ktrans (P = 0.045) were significantly associated with shorter overall survival. Higher pretreatment median ktrans (P = 0.021), normalized RCBV (P = 0.0096), and nCBF (P = 0.038) were significantly associated with shorter progression-free survival. SUVpeak [AUC = 0.75; 95% confidence interval (CI), 0.59–0.91], nRCBV (AUC = 0.72; 95% CI, 0.56–0.89), and nCBF (AUC = 0.72; 95% CI, 0.56–0.89) were predictive of survival at 1 year. Conclusions: Increased tumor perfusion, vascular volume, vascular permeability, and hypoxia are negative prognostic markers in newly diagnosed patients with gioblastoma, and these important physiologic markers can be measured safely and reliably using MRI and 18F-FMISO PET. Clin Cancer Res; 22(20); 5079–86. ©2016 AACR.

A recent joint meeting was held on January 30, 2014, with the US Food and Drug Administration (FDA), National Cancer Institute (NCI), clinical scientists, imaging experts, pharmaceutical and biotech companies, clinical trials cooperative groups, and patient advocate groups to discuss imaging endpoints for clinical trials in glioblastoma. This workshop developed a set of priorities and action items including the creation of a standardized MRI protocol for multicenter studies. The current document outlines consensus recommendations for a standardized Brain Tumor Imaging Protocol (BTIP), along with the scientific and practical justifications for these recommendations, resulting from a series of discussions between various experts involved in aspects of neuro-oncology neuroimaging for clinical trials. The minimum recommended sequences include: (i) parameter-matched precontrast and postcontrast inversion recovery-prepared, isotropic 3D T1-weighted gradient-recalled echo; (ii) axial 2D T2-weighted turbo spin-echo acquired after contrast injection and before postcontrast 3D T1-weighted images to control timing of images after contrast administration; (iii) precontrast, axial 2D T2-weighted fluid-attenuated inversion recovery; and (iv) precontrast, axial 2D, 3-directional diffusion-weighted images. Recommended ranges of sequence parameters are provided for both 1.5 T and 3 T MR systems.

BACKGROUND AND PURPOSE: For more widespread clinical use advanced imaging methods such as relative cerebral blood volume must be both accurate and repeatable. The aim of this study was to determine the repeatability of relative CBV measurements in newly diagnosed glioblastoma multiforme by using several of the most commonly published estimation techniques. MATERIALS AND METHODS: The relative CBV estimates were calculated from dynamic susceptibility contrast MR imaging in double-baseline examinations for 33 patients with treatment-naive and pathologically proved glioblastoma multiforme (men = 20; mean age = 55 years). Normalized and standardized relative CBV were calculated by using 6 common postprocessing methods. The repeatability of both normalized and standardized relative CBV, in both tumor and contralateral brain, was examined for each method with metrics of repeatability, including the repeatability coefficient and within-subject coefficient of variation. The minimum sample size required to detect a parameter change of 10% or 20% was also determined for both normalized relative CBV and standardized relative CBV for each estimation method. RESULTS: When ordered by the repeatability coefficient, methods using postprocessing leakage correction and ΔR2*(t) techniques offered superior repeatability. Across processing techniques, the standardized relative CBV repeatability in normal-appearing brain was comparable with that in tumor ( P = .31), yet inferior in tumor for normalized relative CBV ( P = .03). On the basis of the within-subject coefficient of variation, tumor standardized relative CBV estimates were less variable (13%–20%) than normalized relative CBV estimates (24%–67%). The minimum number of participants needed to detect a change of 10% or 20% is 118–643 or 30–161 for normalized relative CBV and 109–215 or 28–54 for standardized relative CBV. CONCLUSIONS: The ΔR2* estimation methods that incorporate leakage correction offer the best repeatability for relative CBV, with standardized relative CBV being less variable and requiring fewer participants to detect a change compared with normalized relative CBV.

Diffusion-weighted magnetic resonance (MR) imaging and perfusion MR imaging are advanced techniques that provide information not available from conventional MR imaging. In particular, these techniques have a number of applications with regard to characterization of tumors and assessment of tumor response to therapy. In this review, the authors describe the fundamental principles of diffusion-weighted and perfusion MR imaging and provide an overview of the ways in which these techniques are being used to characterize tumors by helping distinguish tumor types, assess tumor grade, and attempt to determine tumor margins. In addition, the role of these techniques for evaluating response to tumor therapy is outlined.

The purpose of our study was to determine the degree to which carotid canal fracture and other CT findings are associated with internal carotid artery (ICA) injury in patients with head trauma.Three neuroradiologists retrospectively evaluated CT scans and cerebral angiograms of 43 patients who underwent cerebral angiography within 7 days after blunt cranial trauma over a 5-year period. Seventeen patients underwent unilateral and 26 had bilateral carotid angiography. Angiograms were evaluated for ICA injury and CT scans were evaluated for carotid canal fracture, brain contusion, subarachnoid hemorrhage, basilar skull fracture, subdural hematoma, soft-tissue swelling, sphenoid sinus air-fluid level, and other skull fracture. We recorded the number of true-positive (+CT, +angiogram), true-negative (-CT, -angiogram), false-positive (+CT, -angiogram), and false-negative (-CT, +angiogram) studies. We determined the sensitivity, specificity, positive predictive value, and negative predictive value for each CT finding.We identified 21 carotid canal fractures in 17 patients. Eleven ICA injuries were seen in 10 patients. Six patients with ICA injury had a carotid canal fracture. The presence of a carotid canal fracture had a sensitivity of 60% and specificity of 67% for detection of injury to the ICA passing through that canal. These values were similar to those for other CT findings.Sensitivity, specificity, positive predictive value, and negative predictive value of carotid canal fracture were only moderately good for determining the presence of ICA injury and were similar to other CT findings not typically associated with ICA injury.

The advent of diffusion-weighted MR imaging and diffusion tensor MR imaging has had little impact on brain tumor detection. Diffusion-weighted imaging has been effective in characterizing specific types of masses, particularly in distinguishing epidermoids from arachnoid cysts, and cystic tumors from intracerebral abscesses. Presurgical planning using tractography with diffusion tensor MR imaging, and perhaps the evaluation of tumor response to chemotherapy and radiation therapy with diffusion-weighted imaging, may become important applications in the near future.

To compare fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET) with the current standard, magnetic resonance (MR) imaging, to determine the sensitivity and specificity of FDG PET for detection of cerebral metastases and to determine the factors that may affect lesion conspicuity.Forty patients underwent brain PET and contrast material-enhanced brain MR imaging, with a maximum of 30 days between examinations. PET and MR images were each retrospectively reviewed by two independent readers who were blinded to the clinical history and results of the other technique. Presence of metastatic disease was recorded for each modality. Sensitivity and specificity of FDG PET were determined with MR imaging as the standard. Statistical analysis was performed with the Fisher exact test and the logistic regression model.Sixteen patients had cerebral metastases at MR imaging, and in 12 of these, PET scans were interpreted as showing metastatic disease (in four, scans were false-negative). Twenty-four patients had no cerebral metastases at MR imaging, and 20 of these had PET scans interpreted as normal (in four, scans were false-positive). For identification of patients with cerebral metastases, FDG PET had a sensitivity of 75% (12 of 16) and a specificity of 83% (20 of 24). Thirty-eight metastatic lesions were seen at MR imaging; 23 (61%) of these were identified at PET. Size was a statistically significant factor that influenced lesion detection at PET (P.001).Only 61% of metastatic lesions in the brain were identified at PET. In particular, detection of small lesions was difficult.

© 2015, Spandidos Publications. All rights reserved. Functional diffusion mapping (fDM) is a cancer imaging technique that quantifies voxelwise changes in apparent diffusion coefficient (ADC). Previous studies have shown value of fDMs in bevacizumab therapy for recurrent glioblastoma multiforme (GBM). The aim of the present study was to implement explicit criteria for diffusion MRI quality control and independently evaluate fDM performance in a multicenter clinical trial (RTOG 0625/ACRIN 6677). A total of 123 patients were enrolled in the current multicenter trial and signed institutional review board-approved informed consent at their respective institutions. MRI was acquired prior to and 8 weeks following therapy. A 5-point QC scoring system was used to evaluate DWI quality. fDM performance was evaluated according to the correlation of these metrics with PFS and OS at the first follow-up time-point. Results showed ADC variability of 7.3% in NAWM and 10.5% in CSF. A total of 68% of patients had usable DWI data and 47% of patients had high quality DWI data when also excluding patients that progressed before the first follow-up. fDM performance was improved by using only the highest quality DWI. High pre-treatment contrast enhancing tumor volume was associated with shorter PFS and OS. A high volume fraction of increasing ADC after therapy was associated with shorter PFS, while a high volume fraction of decreasing ADC was associated with shorter OS. In summary, DWI in multicenter trials are currently of limited value due to image quality. Improvements in consistency of image quality in multicenter trials are necessary for further advancement of DWI biomarkers.

CNS metastases are the most common cause of malignant brain tumours in adults. Historically, patients with brain metastases have been excluded from most clinical trials, but their inclusion is now becoming more common. The medical literature is difficult to interpret because of substantial variation in the response and progression criteria used across clinical trials. The Response Assessment in Neuro-Oncology Brain Metastases (RANO-BM) working group is an international, multidisciplinary effort to develop standard response and progression criteria for use in clinical trials of treatment for brain metastases. Previous efforts have focused on aspects of trial design, such as patient population, variations in existing response and progression criteria, and challenges when incorporating neurological, neuro-cognitive, and quality-of-life endpoints into trials of patients with brain metastases. Here, we present our recommendations for standard response and progression criteria for the assessment of brain metastases in clinical trials. The proposed criteria will hopefully facilitate the development of novel approaches to this difficult problem by providing more uniformity in the assessment of CNS metastases across trials.

To measure mean cerebral blood flow (CBF) in ischemic and nonischemic territories and in low-attenuation regions in patients with acute stroke by using deconvolution-derived hemodynamic imaging.Twelve patients with acute middle cerebral artery stroke and 12 control patients were examined by using single-section computed tomography (CT) perfusion scanning. Analysis was performed with a deconvolution-based algorithm. Comparisons of mean CBF, cerebral blood volume (CBV), and mean transit time (MTT) were determined between hemispheres in all patients and between low- and normal-attenuation regions in patients with acute stroke. Two independent readers examined the images for extent of visually apparent regional perfusion abnormalities. The data were compared with extent of final infarct in seven patients with acute stroke who underwent follow-up CT or magnetic resonance imaging.Significant decreases in CBF (-50%, P =.001) were found in the affected hemispheres of patients with acute stroke. Significant changes in CBV (-26%, P =.03) and MTT (+111%, P =.004) were also seen. Significant alterations in perfusion were also seen in low- compared with normal-attenuation areas. Pearson correlation between readers for extent of CBF abnormality was 0.94 (P =.001). Intraobserver variation was 8.9% for CBF abnormalities.Deconvolution analysis of CT perfusion data is a promising method for evaluation of cerebral hemodynamics in patients with acute stroke.

To quantify the test-retest repeatability of mean diffusivity (MD) and fractional anisotropy (FA) derived from diffusion tensor imaging (DTI) tractography in a cohort of paediatric patients with localization-related epilepsy.30 patients underwent 2 DTI acquisitions [repetition time/echo time (ms), 7000/90; flip, 90°; b-value, 1000 s mm(-2); voxel (mm), 2 × 2 × 2]. Two observers used Diffusion Toolkit and TrackVis ( www.trackvis.org ) to segment and analyse the following tracts: corpus callosum, corticospinal tracts, arcuate fasciculi, inferior longitudinal fasciculi and inferior fronto-occipital fasciculi. Mean MD and mean FA were calculated for each tract. Each observer independently analysed one of the DTI data sets for every patient.Segmentation identified all tracts in all subjects, except the arcuate fasciculus. There was a highly consistent relationship between repeated observations of MD (r = 0.993; p 0.0001) and FA (r = 0.990; p 0.0001). For each tract, coefficients of variation ranged from 0.9% to 2.1% for MD and from 1.5% to 2.8% for FA. The 95% confidence limits (CLs) for change ranged from 2.8% to 6% for MD and from 4.3% to 8.6% for FA. For the arcuate fasciculus, Cohen's κ for agreement between the observers (identifiable vs not identifiable) was 1.0.We quantified the repeatability of two commonly utilized scalar metrics derived from DTI tractography. For an individual patient, changes greater than the repeatability coefficient or 95% CLs for change are unlikely to be related to variability in their measurement.Reproducibility of these metrics will aid in the design of future studies and might one day be used to guide management in patients with epilepsy.

Purpose: Glioblastoma is the most common malignant brain tumor. It is characterized by low median survival time and high survival variability. Survival prognosis for glioblastoma is very important for optimized treatment planning. Imaging features observed in magnetic resonance (MR) images were shown to be a good predictor of survival. However, manual assessment of MR features is time-consuming and can be associated with a high inter-reader variability as well as inaccuracies in the assessment. In response to this limitation, the authors proposed and evaluated a computer algorithm that extracts important MR image features in a fully automatic manner. Methods: The algorithm first automatically segmented the available volumes into a background region and four tumor regions. Then, it extracted ten features from the segmented MR imaging volumes, some of which were previously indicated as predictive of clinical outcomes. To evaluate the algorithm, the authors compared the extracted features for 73 glioblastoma patients to the reference standard established by manual segmentation of the tumors. Results: The experiments showed that their algorithm was able to extract most of the image features with moderate to high accuracy. High correlation coefficients between the automatically extracted value and reference standard were observed for the tumor location, minor and major axis length as well as tumor volume. Moderately high correlation coefficients were also observed for proportion of enhancing tumor, proportion of necrosis, and thickness of enhancing margin. The correlation coefficients for all these features were statistically significant (p < 0.0001). Conclusions: The authors proposed and evaluated an algorithm that, given a set of MR volumes of a glioblastoma patient, is able to extract MR image features that correlate well with their reference standard. Future studies will evaluate how well the computer-extracted features predict survival.

Purpose: Our purpose was to show the computed tomography (CT) and magnetic resonance (MR) imaging features of vertex epidural hematomas (EDHs) and emphasize pitfalls in the diagnosis of this entity. Subjects and methods: The neuroradiologic studies of four patients (CT in four, MR imaging and MR venography in one) were evaluated for EDH shape, size and appearance. Results: EDHs were biconvex in three patients and crescentic in one patient. CT appearances included a collection that was hyperdense (two patients), generally isodense with a few regions of hyperdensity (one patient) and mixed hyperdense and hypodense (one patient). MR imaging findings in one patient consisted of hyperintense signal on T1-weighted images and hypointense signal on T2-weighted images. Inferior displacement of the superior sagittal sinus was seen in two patients. Diagnosis of a small vertex EDH was difficult on routine axial CT in one patient, but apparent on MR imaging and MR venography. Conclusions: Small vertex EDHs can be difficult to diagnose on routine CT. MR imaging or thin section CT should be performed to exclude the diagnosis in patients with trauma to the skull vertex.

This paper reviews published post-mortem brain and in-vivo proton magnetic resonance spectroscopy (1H-MRS) studies in Alzheimer's disease (AD) and focuses on the emerging role of N-acetylaspartate (NAA) as a prognostic marker of neuronal function. Post-mortem brain studies have reported significantly lower NAA levels in AD brains than in control brains, and some have correlated the low levels with neuropathological findings (i.e. amyloid plaques and neurofibrillary tangles). Similarly, almost all published in-vivo studies have reported lower NAA levels in AD patients compared to elderly controls. While some studies have found changes in metabolite levels that were considered useful for the diagnosis of AD, most have found that 1H-MRS provided little or no advantages over other, more common diagnostic tools. Instead, recent studies in AD and other neuropsychiatric disorders suggest that NAA may be more useful as a prognostic marker for monitoring neurodegeneration, stabilization, or improvement, and for evaluating therapeutic response to novel drugs.

Article abstract Hippocampal sulcal cavities are usually considered incidental findings on brain MRI. In a group of 92 elderly volunteers, the authors graded the number and size of hippocampal sulcal cavities with brain MRI to obtain a cavity score. Cavity scores increased with age, and were higher in subjects carrying the APOE ε4 or ε2 alleles than in subjects with the ε3/3 genotype. Age-related morphologic changes in the hippocampus may be mediated by the APOE genotype.