Diffusion Imaging: Insight to Cell Status and Cytoarchitecture

Temporal dynamics of neonatal hypoxic-ischemic encephalopathy injuries on magnetic resonance imaging

Moderate to severe perinatal hypoxic-ischemic encephalopathy occurs in ~ 1 to 3/1000 live births in high-income countries and is associated with a significant risk of death or neurodevelopmental disability. Detailed assessment is important to help identify high-risk infants, to help families, and to support appropriate interventions. A wide range of monitoring tools is available to assess changes over time, including urine and blood biomarkers, neurological examination, and electroencephalography. At present, magnetic resonance imaging is unique as although it is expensive and not suited to monitoring the early evolution of hypoxic-ischemic encephalopathy by a week of life it can provide direct insight into the anatomical changes in the brain after hypoxic-ischemic encephalopathy and so offers strong prognostic information on the long-term outcome after hypoxic-ischemic encephalopathy. This review investigated the temporal dynamics of neonatal hypoxic-ischemic encephalopathy injuries, with a particular emphasis on exploring the correlation between the prognostic implications of magnetic resonance imaging scans in the first week of life and their relationship to long-term outcome prediction, particularly for infants treated with therapeutic hypothermia. A comprehensive literature search, from 2016 to 2024, identified 20 pertinent articles. This review highlights that while the optimal timing of magnetic resonance imaging scans is not clear, overall, it suggests that magnetic resonance imaging within the first week of life provides strong prognostic accuracy. Many challenges limit the timing consistency, particularly the need for intensive care and clinical monitoring. Conversely, although most reports examined the prognostic value of scans taken between 4 and 10 days after birth, there is evidence from small numbers of cases that, at times, brain injury may continue to evolve for weeks after birth. This suggests that in the future it will be important to explore a wider range of times after hypoxic-ischemic encephalopathy to fully understand the optimal timing for predicting long-term outcomes.

Tri-Compartmental Restriction Spectrum Imaging Based on 18F-FDG PET/MR for Identification of Primary Benign and Malignant Lung Lesions

BACKGROUND

Restriction spectrum imaging (RSI), as an advanced quantitative diffusion-weighted magnetic resonance imaging technique, has the potential to distinguish primary benign and malignant lung lesions.

OBJECTIVE

To explore how well the tri-compartmental RSI performs in distinguishing primary benign from malignant lung lesions compared with diffusion-weighted imaging (DWI), and to further explore whether positron emission tomography/magnetic resonance imaging (PET/MRI) can improve diagnostic efficacy.

STUDY TYPE

Prospective.

POPULATION

137 patients, including 108 malignant and 29 benign lesions (85 males, 52 females; average age = 60.0 ± 10.0 years).

FIELD STRENGTH/SEQUENCE

T2WI, T1WI, multi-b value DWI, MR-based attenuation correction, and PET imaging on a 3.0 T whole-body PET/MR system.

ASSESSMENT

The apparent diffusion coefficient (ADC), RSI-derived parameters (restricted diffusionf 1 , hindered diffusionf 2 , and free diffusionf 3 ) and the maximum standardized uptake value (SUVmax) were calculated and analyzed for diagnostic efficacy individually or in combination.

STATISTICAL TESTS

Student's t-test, Mann-Whitney U test, receiver operating characteristic (ROC) curves, Delong test, Spearman's correlation analysis. P < 0.05 was considered statistically significant.

RESULTS

Thef 1 , SUVmax were significantly higher, andf 3 , ADC were significantly lower in the malignant group [0.717 ± 0.131, 9.125 (5.753, 13.058), 0.194 ± 0.099, 1.240 (0.972, 1.407)] compared to the benign group [0.504 ± 0.236, 3.390 (1.673, 6.030), 0.398 ± 0.195, 1.485 ± 0.382]. The area under the ROC curve (AUC) values ranked from highest to lowest as follows: AUC (SUVmax) > AUC (f 3 ) > AUC (f 1 ) > AUC (ADC) > AUC (f 2 ) (AUC = 0.819, 0.811, 0.770, 0.745, 0549). The AUC (AUC = 0.900) of the combined model of RSI with PET was significantly higher than that of either single-modality imaging.

CONCLUSION

RSI-derived parameters (f 1 ,f 3 ) might help to distinguish primary benign and malignant lung lesions and the discriminatory utility off 2 was not observed. The RSI exhibits comparable or potentially enhanced performance compared with DWI, and the combined RSI and PET model might improve diagnostic efficacy.

LEVEL OF EVIDENCE: 2

TECHNICAL EFFICACY

Stage 2.

MRI Characteristics of Primary Brain Tumors and Advanced Diagnostic Imaging Techniques

Extensive descriptions of MRI characteristics of canine and feline brain tumors allow for relatively accurate lesion detection, discrimination, and presumptive diagnosis on MRI. Ambiguous and overlapping MRI features between brain lesion and tumor as well as tumor types is a limitation that necessitates histopathology for final diagnosis, which is often not available antemortem. Non-invasive advanced diagnostic imaging techniques continue to be developed to enhance sensitivity and specificity for brain tumor diagnosis on MRI in dogs and cats.

Brain MRI Protocol and Systematic Approach to Interpretation of Brain Tumors on MRI

MRI plays an integral role in the diagnosis of brain tumors in dogs and cats. Optimized image acquisition protocols in addition to a systematic approach to brain tumor evaluation on MRI using imaging characteristic interpretation criteria may allow for enhanced lesion detection, accurate presumptive diagnoses, and formulation of a prioritized differential diagnosis list.

Comparative diagnostic accuracy of multiparametric magnetic resonance imaging-ultrasound fusion-guided biopsy versus systematic biopsy for clinically significant prostate cancer

Purpose

To examine the accuracy of transperineal magnetic resonance imaging (MRI)-ultrasound (US) fusion biopsy (FB) in identifying men with prostate cancer (PCa) that has reached a clinically relevant stage.

Methods

This investigation enrolled 459 males. In 210 of these patients (FB group), transperineal MRI/US fusion-guided biopsies were performed on the suspicious region, and in 249 others, a systematic biopsy (SB) was performed (SB group). We compared these groups using Gleason scores and rates of cancer detection.

Results

PCa cases counted 198/459 (43.1%), including 94/249 (37.8%) in the SB group and 104/210 (49.5%) in the FB group. FB was associated with higher overall diagnostic accuracy relative to SB (88.5% and 72.3%, P = 0.024). FB exhibited greater sensitivity than SB (88.9% and 71.2%, P = 0.025). The area under the curve for FB and SB approaches was 0.837 and 0.737, respectively, such that FB was associated with an 11.9% increase in accuracy as determined based upon these AUC values. Relative to SB, FB was better able to detect high-grade tumors (GS ≥ 7) (78.85% vs. 60.64%, P = 0.025).

Conclusion

Transperineal MRI-US fusion targeted biopsy is superior to the systematic one as an approach to diagnosing clinically significant PCa, as it is a viable technical approach to prostate biopsy.

Diffusion-weighted imaging (DWI) in diagnosis, staging, and treatment response assessment of multiple myeloma: a systematic review and meta-analysis

OBJECTIVE

To evaluate the role of diffusion-weighted imaging (DWI) in the initial diagnosis, staging, and assessment of treatment response in patients with multiple myeloma (MM).

MATERIALS AND METHODS

A systematic literature review was conducted in PubMed, the Cochrane Library, EMBASE, Scopus, and Web of Science databases. The primary endpoints were defined as the diagnostic performance of DWI for disease detection, staging of MM, and assessing response to treatment in these patients.

RESULTS

Of 5881 initially reviewed publications, 33 were included in the final qualitative and quantitative meta-analysis. The diagnostic performance of DWI in the detection of patients with MM revealed pooled sensitivity and specificity of 86% (95% CI: 84-89) and 63% (95% CI: 56-70), respectively, with a diagnostic odds ratio (OR) of 14.98 (95% CI: 4.24-52.91). The pooled risk difference of 0.19 (95% CI: - 0.04-0.42) was reported in favor of upstaging with DWI compared to conventional MRI (P value = 0.1). Treatment response evaluation and ADC_mean value changes across different studies showed sensitivity and specificity of approximately 78% (95% CI: 72-83) and 73% (95% CI: 61-83), respectively, with a diagnostic OR of 7.21 in distinguishing responders from non-responders.

CONCLUSIONS

DWI is not only a promising tool for the diagnosis of MM, but it is also useful in the initial staging and re-staging of the disease and treatment response assessment. This can aid clinicians with earlier initiation or change in treatment strategy, which could have prognostic significance for patients.

Mathematical modelling of the dynamics of image-informed tumor habitats in a murine model of glioma

Tumors exhibit high molecular, phenotypic, and physiological heterogeneity. In this effort, we employ quantitative magnetic resonance imaging (MRI) data to capture this heterogeneity through imaging-based subregions or "habitats" in a murine model of glioma. We then demonstrate the ability to model and predict the growth of the habitats using coupled ordinary differential equations (ODEs) in the presence and absence of radiotherapy. Female Wistar rats (N = 21) were inoculated intracranially with 10⁶ C6 glioma cells, a subset of which received 20 Gy (N = 5) or 40 Gy (N = 8) of radiation. All rats underwent diffusion-weighted and dynamic contrast-enhanced MRI at up to seven time points. All MRI data at each visit were subsequently clustered using k-means to identify physiological tumor habitats. A family of four models consisting of three coupled ODEs were developed and calibrated to the habitat time series of control and treated rats and evaluated for predictive capability. The Akaike Information Criterion was used for model selection, and the normalized sum-of-square-error (SSE) was used to evaluate goodness-of-fit in model calibration and prediction. Three tumor habitats with significantly different imaging data characteristics (p < 0.05) were identified: high-vascularity high-cellularity, low-vascularity high-cellularity, and low-vascularity low-cellularity. Model selection resulted in a five-parameter model whose predictions of habitat dynamics yielded SSEs that were similar to the SSEs from the calibrated model. It is thus feasible to mathematically describe habitat dynamics in a preclinical model of glioma using biology-based ODEs, showing promise for forecasting heterogeneous tumor behavior.

Retinal and optic nerve magnetic resonance diffusion-weighted imaging in acute non-arteritic central retinal artery occlusion

OBJECTIVES

Diffusion weighted imaging hyperintensity (DWI-H) has been described in the retina and optic nerve during acute central retinal artery occlusion (CRAO). We aimed to determine whether DWI-H can be accurately identified on standard brain magnetic resonance imaging (MRI) in non-arteritic CRAO patients at two tertiary academic centers.

MATERIALS AND METHODS

Retrospective cross-sectional study that included all consecutive adult patients with confirmed acute non-arteritic CRAO and brain MRI performed within 14 days of CRAO. At each center, two neuroradiologists masked to patient clinical data reviewed each MRI for DWI-H in the retina and optic nerve, first independently then together. Statistical analysis for inter-rater reliability and correlation with clinical data was performed.

RESULTS

We included 204 patients [mean age 67.9±14.6 years; 47.5% females; median time from CRAO to MRI 1 day (IQR 1-4.3); 1.5 T in 127/204 (62.3%) and 3.0 T in 77/204 (37.7%)]. Inter-rater reliability varied between centers (κ = 0.27 vs. κ = 0.65) and was better for retinal DWI-H. Miss and error rates significantly differed between neuroradiologists at each center. After consensus review, DWI-H was identified in 87/204 (42.6%) patients [miss rate 117/204 (57.4%) and error rate 11/87 (12.6%)]. Significantly more patients without DWI-H had good visual acuity at follow-up (p = 0.038).

CONCLUSIONS

In this real-world case series, differences in agreement and interpretation accuracy among neuroradiologists limited the role of DWI-H in diagnosing acute CRAO on standard MRI. DWI-H was identified in 42.6% of patients and was more accurately detected in the retina than in the optic nerve. Further studies are needed with standardized novel MRI protocols.

Relationship between Apparent Diffusion Coefficient Distribution and Cancer Grade in Prostate Cancer and Benign Prostatic Hyperplasia

The aim of this paper was to assess the associations between prostate cancer aggressiveness and histogram-derived apparent diffusion coefficient (ADC) parameters and determine which ADC parameters may help distinguish among stromal hyperplasia (SH), glandular hyperplasia (GH), and low-grade, intermediate-grade, and high-grade prostate cancers. The mean, median, minimum, maximum, and 10th and 25th percentile ADC values were determined from the ADC histogram and compared among two benign prostate hyperplasia (BPH) groups and three Gleason score (GS) groups. Seventy lesions were identified in 58 patients who had undergone proctectomy. Thirty-nine lesions were prostate cancers (GS 6 = 7 lesions, GS 7 = 19 lesions, GS 8 = 11 lesions, GS 9 = 2 lesions), and thirty-one lesions were BPH (SH = 15 lesions, GH = 16 lesions). There were statistically significant differences in 10th percentile and 25th percentile ADC values when comparing GS 6 to GS 7 (p < 0.05). The 10th percentile ADC values yielded the highest area under the curve (AUC). Tenth and 25th percentile ADCs can be used to more accurately differentiate lesions with GS 6 from those with GS 7 than other ADC parameters. Our data indicate that the major challenge with ADC mapping is to differentiate between SH and GS 6, and SH and GS 7.

Parametric Response Mapping of FLAIR MRI Provides an Early Indication of Progression Risk in Glioblastoma

RATIONALE AND OBJECTIVES

Glioblastoma image evaluation utilizes Magnetic Resonance Imaging contrast-enhanced, T1-weighted, and noncontrast T2-weighted fluid-attenuated inversion recovery (FLAIR) acquisitions. Disease progression assessment relies on changes in tumor diameter, which correlate poorly with survival. To improve treatment monitoring in glioblastoma, we investigated serial voxel-wise comparison of anatomically-aligned FLAIR signal as an early predictor of GBM progression.

MATERIALS AND METHODS

We analyzed longitudinal normalized FLAIR images (rFLAIR) from 52 subjects using voxel-wise Parametric Response Mapping (PRM) to monitor volume fractions of increased (PRM_rFLAIR+), decreased (PRM_rFLAIR-), or unchanged (PRM_rFLAIR0) rFLAIR intensity. We determined response by rFLAIR between pretreatment and 10 weeks posttreatment. Risk of disease progression in a subset of subjects (N = 26) with stable disease or partial response as defined by Response Assessment in Neuro-Oncology (RANO) criteria was assessed by PRM_rFLAIR between weeks 10 and 20 and continuously until the PRM_rFLAIR+ exceeded a defined threshold. RANO defined criteria were compared with PRM-derived outcomes for tumor progression detection.

RESULTS

Patient stratification for progression-free survival (PFS) and overall survival (OS) was achieved at week 10 using RANO criteria (PFS: p <0.0001; OS: p <0.0001), relative change in FLAIR-hyperintense volume (PFS: p = 0.0011; OS: p <0.0001), and PRM_rFLAIR+ (PFS: p <0.01; OS: p <0.001). PRM_rFLAIR+ also stratified responding patients' progression between weeks 10 and 20 (PFS: p <0.05; OS: p = 0.01) while changes in FLAIR-volume measurements were not predictive. As a continuous evaluation, PRM_rFLAIR+ exceeding 10% stratified patients for PFA after 5.6 months (p<0.0001), while RANO criteria did not stratify patients until 15.4 months (p <0.0001).

CONCLUSION

PRM_rFLAIR may provide an early biomarker of disease progression in glioblastoma.

The prominent value of apparent diffusion coefficient in assessing high-risk factors and prognosis for patients with endometrial carcinoma before treatment

BACKGROUND

To date, there are no consensus methods to evaluate the high-risk factors and prognosis for managing the personalized treatment schedule of patients with endometrial carcinoma (EC) before treatment. Apparent diffusion coefficient (ADC) is regarded as a kind of technique to assess heterogeneity of malignant tumor.

PURPOSE

To explore the role of ADC value in assessing the high-risk factors and prognosis of EC.

MATERIAL AND METHODS

A retrospective analysis was made on 185 patients with EC who underwent 1.5-T magnetic resonance imaging (MRI). Mean ADC (mADC), minimum ADC (minADC), and maximum ADC (maxADC) were measured and compared in different groups.

RESULTS

Among the 185 patients with EC, the mADC and maxADC values in those with high-risk factors (type 2, deep myometrial invasion, and lymph node metastasis) were significantly lower than in those without. According to receiver operating characteristic (ROC) curve analysis, the areas under the curve (AUC) were significant for mADC, minADC, and maxADC predicting high-risk factors. Furthermore, the AUCs were significant for mADC and maxADC predicting lymph node metastasis but were not significant for minADC. Patients with lower mADC were associated with worse overall survival and disease-free survival; the opposite was true for patients with higher mADC.

CONCLUSION

Our study showed that ADC values could be applied to assess the high-risk factors of EC before treatment and might significantly relate to the prognosis of EC. It might contribute to managing initial individualized treatment schedule and improve outcome in patients with EC.

Diagnostic utility of Restriction Spectrum Imaging in the characterization of the peritumoral brain zone in glioblastoma: Analysis of overall and progression-free survival

PURPOSE

We studied the ability of Restriction Spectrum Imaging (RSI), a novel advanced diffusion imaging technique, to estimate levels of cellularity in different glioblastoma regions, evaluated their prognostic value compared with established clinical diffusion metrics such as fractional anisotropy (FA) and mean diffusivity (MD).

METHODS

Forty-two patients with untreated glioblastoma, IDH-wildtype, were examined with an advanced MRI tumor protocol. The region of interest (ROI) was obtained from the contrast-enhancing part of tumor and the peritumoral brain zones and then co-registered with RSI-cellularity index, FA and MD maps. Histogram parameters of diffusion metrics were assessed for all ROI locations and compared to MGMT promoter methylation status and survival. The ability of RSI-cellularity index, FA, and MD to stratify survival and were assessed by Cox proportional hazard regression, adjusted for significant clinical predictors.

RESULTS

The highest RSI-cellularity index was measured in contrast-enhancing tumor core with a negative gradient from tumor core to the periphery of peritumoral zone with predictive accuracy 81 % (P < 0.001). Shorter overall survival was significant associated with higher RSI-cellularity index (hazard ratio (HR) 3.6, 95 % confidence interval (CI) 1.3-9.5, P = 0.002) with synchronal decrease in MD (HR 0.31, 95 %CI 0.1-0.8, P = 0.008) in the contrast-enhanced tumor core. This association was also consistent for RSI-cellularity index value measured in the peri-enhancing zone (HR 3.6, 95 % CI 1.0-12.3, P = 0.041). No statistically significant differences were noted between RSI-cellularity index, FA, nor MD and MGMT promoter methylation.

CONCLUSION

RSI-cellularity index may be used as prognostic biomarker to improve risk stratification in patients with glioblastoma.

Preclinical Applications of Magnetic Resonance Imaging in Oncology

The evolving possibilities of molecular imaging (MI) are fundamentally changing the way we look at cancer, with imaging paradigms now shifting away from basic morphological measures toward the longitudinal assessment of functional, metabolic, cellular, and molecular information in vivo. Recent developments of imaging methodology and probe molecules utilizing the vast number of novel animal models of human cancers have enhanced our ability to non-invasively characterize neoplastic tissue and follow anticancer treatments. While preclinical molecular imaging offers a whole palette of excellent methodology to choose from, we will focus on magnetic resonance imaging (MRI) techniques, since they provide excellent molecular imaging capabilities and bear high potential for clinical translation. Prerequisites and consequences of using animal models as surrogates of human cancers in preclinical molecular imaging are outlined. We present physical principles, values, and limitations of MRI as molecular imaging modality and comment on its high potential to non-invasively assess information on metabolism, hypoxia, angiogenesis, and cell trafficking in preclinical cancer research.

Interventions to reduce the time to diagnosis of brain tumours

BACKGROUND

Brain tumours are recognised as one of the most difficult cancers to diagnose because presenting symptoms, such as headache, cognitive symptoms, and seizures, may be more commonly attributable to other, more benign conditions. Interventions to reduce the time to diagnosis of brain tumours include national awareness initiatives, expedited pathways, and protocols to diagnose brain tumours, based on a person's presenting symptoms and signs; and interventions to reduce waiting times for brain imaging pathways. If such interventions reduce the time to diagnosis, it may make it less likely that people experience clinical deterioration, and different treatment options may be available.

OBJECTIVES

To systematically evaluate evidence on the effectiveness of interventions that may influence: symptomatic participants to present early (shortening the patient interval), thresholds for primary care referral (shortening the primary care interval), and time to imaging diagnosis (shortening the secondary care interval and diagnostic interval). To produce a brief economic commentary, summarising the economic evaluations relevant to these interventions.

SEARCH METHODS

For evidence on effectiveness, we searched CENTRAL, MEDLINE, and Embase from January 2000 to January 2020; Clinicaltrials.gov to May 2020, and conference proceedings from 2014 to 2018. For economic evidence, we searched the UK National Health Services Economic Evaluation Database from 2000 to December 2014.

SELECTION CRITERIA

We planned to include studies evaluating any active intervention that may influence the diagnostic pathway, e.g. clinical guidelines, direct access imaging, public health campaigns, educational initiatives, and other interventions that might lead to early identification of primary brain tumours. We planned to include randomised and non-randomised comparative studies. Included studies would include people of any age, with a presentation that might suggest a brain tumour.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed titles identified by the search strategy, and the full texts of potentially eligible studies. We resolved discrepancies through discussion or, if required, by consulting another review author.

MAIN RESULTS

We did not identify any studies for inclusion in this review. We excluded 115 studies. The main reason for exclusion of potentially eligible intervention studies was their study design, due to a lack of control groups. We found no economic evidence to inform a brief economic commentary on this topic.

AUTHORS' CONCLUSIONS

In this version of the review, we did not identify any studies that met the review inclusion criteria for either effectiveness or cost-effectiveness. Therefore, there is no evidence from good quality studies on the best strategies to reduce the time to diagnosis of brain tumours, despite the prioritisation of research on early diagnosis by the James Lind Alliance in 2015. This review highlights the need for research in this area.

Assessment of early treatment response on MRI in multiple myeloma: Comparative study of whole-body diffusion-weighted and lumbar spinal MRI

Objectives

To compare remission status at completion of chemotherapy for multiple myeloma (MM) with changes in total diffusion volume (tDV) calculated from whole-body diffusion-weighted imaging (WB-DWI) and fat fraction (FF) of lumbar bone marrow (BM) by modified Dixon Quant (mDixon Quant) soon after induction of chemotherapy, and to assess the predictive value of MRI.

Methods

Fifty patients (mean age, 66.9 ± 10.5 years) with symptomatic myeloma were examined before and after two cycles of chemotherapy. From WB-DWI data, tDV was obtained with the threshold for positive BM involvement. Mean FF was calculated from lumbar BM using the mDixon Quant sequence. At the completion of chemotherapy, patients were categorized into a CR/very good PR (VGPR) group (n = 15; mean age, 67.6 ± 10.3 years) and a PR, SD or PD group (n = 35; mean age, 69.1 ± 8.6 years). ROC curves were plotted to assess performance in predicting achievement of CR/VGPR.

Results

At second examination, serum M protein, β₂-microglobulin, and tDV were significantly decreased and hemoglobin, mean ADC, and FF were significantly increased in the CR/VGPR group and serum M protein was significantly increased in the PR/SD/PD group. The general linear model demonstrated that percentage changes in FF and M protein contributed significantly to achieving CR/VGPR (P = 0.02, P = 0.04, respectively). AUCs of ROC curves were 0.964 for FF and 0.847 for M protein.

Conclusions

Early change in FF of lumbar BM and serum M protein soon after induction of chemotherapy contributed significantly to prediction of CR/VGPR.

Risk of Gleason Score 3+4=7 prostate cancer upgrading at radical prostatectomy is significantly reduced by targeted versus standard biopsy

BACKGROUND

The aim of this study is to evaluate if multiparametric magnetic resonance (mpMRI)-transrectal ultrasound (TRUS) fusion targeted biopsy (TBx) versus untargeted standard biopsy (SBx) may decrease the rate of pathological upgrading of Gleason Score (GS) 3+4 prostate cancer (PCa) at radical prostatectomy (RP). We also evaluated the impact of percent pattern 4 and cribriform glands at biopsy in the risk of GS 3+4=7 upgrading.

METHODS

A total of 301 patients with GS 3+4 PCa on biopsy (159 SBx and 142 TBx) who underwent laparoscopic robot-assisted RP were sequentially enrolled. Histological data from RP sections were used as reference standard. The concordance of biopsy with pathological GS, as well as the GS 3+4 upgrading at RP were evaluated in different univariate and multivariate binary logistic regression models, testing age, PSA, fPSA%, tumor volume, PI-RADS, clinical stage, percentage of Gleason pattern 4 (GP) and/or presence of cribriform sub-type at biopsy.

RESULTS

Of the 301 biopsies, the median of GP 4 was 16% of the tissue. Minimal GP 4 (≤16%) cancers had a significant lower median volume (1.7 mL) than those with GP4 >16% (2.9 mL), (P<0.001). Pathological GS 3+4 was confirmed for 58.8% and 82.2% for SBx and TBx patients, respectively. The rate of upgraded and downgraded GS on SBx versus TBx was 38.8% vis. 16.7% and 1.8% and 2.1%, respectively. The rate of upgrading was significantly associated with the presence of GP4 >16% versus ≤16% (OR 4.4, 95% CI 1.4-12.0; P=0.021) and with the presence of cribriform sub-type at biopsy specimens (OR 6.2, 95% CI 2.2-18.7; P<0.001).

CONCLUSIONS

We demonstrated that TBx technique significantly reduced the risk of GS 3+4 upgrading at RP, compared to SBx one. The rate of upgrading was significantly associated with GP4>16%, mostly when cribriform sub-type was present at biopsy specimens.

Previous glucocorticoid treatment in childhood and adolescence is associated with long-term differences in subcortical grey matter volume and microstructure

BACKGROUND

Glucocorticoids are widely used in the treatment of several pediatric diseases with undisputed disease-related benefits. Perinatal exposure to high levels of glucocorticoids can have long-term adverse cerebral effects. In adults, glucocorticoid treatment has been associated with smaller volumes of subcortical grey matter structures. Recently, we observed smaller total brain volumes in children and adolescents treated with glucocorticoid during childhood compared to healthy controls. The possible long-term effects of glucocorticoid treatment during childhood on subcortical brain volume and microstructure remain unknown.

METHOD

We examined 30 children and adolescents, who had previously been treated with glucocorticoids for nephrotic syndrome or rheumatic disease, and 30 healthy volunteers. Patients and healthy control groups were matched by age, gender, and level of parent education. Participants underwent 3 T magnetic resonance (MR) brain imaging. T1-weighted and diffusion-weighted images were acquired. Volume and mean diffusivity (MD) measures were extracted for hippocampus, amygdala, nucleus accumbens, caudate nucleus and putamen. Multiple linear regression analyses were used to assess differences between patients and controls, and to evaluate possible dose-response relationships. A priori, we expected patients to display lower hippocampal and amygdala volumes.

RESULTS

While children previously treated with glucocorticoids displayed smaller right hippocampal volumes than controls, this difference did not survive correction for multiple comparisons. Furthermore, patients as compared to controls showed lower right hippocampal MD, which remained when correcting for global changes in MD. The longer the time between the glucocorticoid treatment termination and MR-scan, the more right hippocampal MD values resembled that of healthy controls. Patient and controls did not differ in amygdala volume or MD. Analyses of the nucleus accumbens, caudate nucleus and putamen only revealed smaller putamen volumes in patients compared to controls, which remained significant when controlling for total brain volume.

CONCLUSION

The results suggest that extra-cerebral diseases during childhood treated with glucocorticoids may be associated with reduced subcortical grey matter volumes and lower right hippocampal mean diffusivity later in life. Our findings warrant replication and elaboration in larger, preferably prospective and longitudinal studies. Such studies may also allow disentangling disease-specific effects from possible glucocorticoid treatment effects.

Investigation of dacomitinib on reducing cell necrosis and enhancing cell apoptosis in C6 glioma rat model by MRI

BACKGROUND

Glioma is one of the most epidemic and obstinate types of cancer in the central nervous system (CNS) with poor survival rate. Dacomitinib inhibited cell viability and proliferation of epidermal growth factor receptor (EGFR)-amplified glioma. In the present study, the regional effects of Dacomitinib on tumor necrosis was investigated.

METHODS

A C6 rat glioma model was evaluated using proton magnetic resonance spectroscopy (¹H-MRS), diffusion weighted imaging (DWI), and morphological T2-weighted imaging (T2W). The effects of Dacomitinib on glioma cells were investigated using methods of immunohistochemistry and Hematoxylin and Eosin (H&E) staining.

RESULTS

The obtained data indicated that metabolite ratios were significantly decreased (all P<0.05) in the Dacomitinib-treated group compared with C6 glioma control group. The ADC value of necrotic core in Dacomitinib group was significantly lower than that in control group. In addition, the expression of Ki-67 in Dacomitinib-treated group (50.32 ± 5.61) was significantly lower than that in control group (P<0.05). The apoptotic index (AI) (28.01 ± 2.37) in Dacomitinib-treated group was significantly higher than that in control group (11.58 ± 3.17).

CONCLUSION

The results demonstrated that the Dacomitinib could suppress glioma cell necrosis and proliferation.

Metanephric adenoma with low apparent diffusion coefficient value mimicking renal cell carcinoma: A case report

RATIONALE

Metanephric adenoma (MA) is a rare and often benign tumor. Most MAs were misdiagnosed as renal cell carcinomas (RCCs) preoperatively. Diffusion weighted imaging (DWI) and apparent diffusion coefficient (ADC) mapping can help to differentiate benign and malignant tumors. However, there are still pitfalls in using DWI and ADC to discriminate benign and malignant lesions.

PATIENT CONCERNS

A 56-year-old woman had a right renal metanephric adenoma. The tumor showed very low ADC value preoperatively and was misdiagnosed as a renal cell carcinoma.

DIAGNOSIS

Intraoperative ultrasound-guided percutaneous biopsy of tumor was performed. Based on the histopathological findings and immunohistochemical stains, a diagnosis of metanephric adenoma was suggested.

INTERVENTIONS

The patient received percutaneous cryoablation of this tumor. Five years later, she underwent right partial nephrectomy because local recurrence was revealed on a follow-up computed tomography (CT).

OUTCOMES

MA was confirmed again by histological examination. The patient was uneventful after surgery.

LESSONS

ADC mapping can be used for differentiating RCCs from other benign tumors by their lower ADC values. However, some benign and malignant lesions have overlapped low ADC values. This case illustrated that a benign lesion such as MA could mimic RCC on ADC, by its highly cellular component. Cryoablation is an optional treatment, which has an increased risk of local recurrence. Follow-up CT or MRI is useful and necessary for detection of local recurrence by depicting enhancing solid parts in a tumor over time.

Differentiation of Edematous, Tumoral and Normal Areas of Brain Using Diffusion Tensor and Neurite Orientation Dispersion and Density Imaging

BACKGROUND

Presurigical planning for glioma tumor resection and radiotherapy treatment require proper delineation of tumoral and peritumoral areas of brain. Diffusion tensor imaging (DTI) is the most common mathematical model applied for diffusion weighted MRI data. Neurite orientation dispersion and density imaging (NODDI) is another mathematical model for DWI data modeling.

OBJECTIVE

We studied whether extracted parameters of DTI, and NODDI models can be used to differentiate between edematous, tumoral, and normal areas in brain white matter (WM).

MATERIAL AND METHODS

12 patients with peritumoral edema underwent 3T multi-shell diffusion imaging with b-values of 1000 and 2000 smm-2 in 30 and 64 gradient directions, respectively. We fitted DTI and NODDI to data in manually drawn regions of interest and used their derived parameters to characterize edematous, tumoral and normal brain areas.

RESULTS

We found that DTI parameters fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) all significantly differentiated edematous from contralateral normal brain WM (p<0.005). However, only FA was found to distinguish between edematous WM fibers and tumor invaded fibers (p = 0.001). Among NODDI parameters, the intracellular volume fraction (ficvf) had the best distinguishing power with (p = 0.001) compared with the isotropic volume fraction (fiso), the orientation dispersion index (odi), and the concentration parameter of Watson distribution (κ), while comparing fibers inside normal, tumoral, and edematous areas.

CONCLUSION

The combination of two diffusion based methods, i.e. DTI and NODDI parameters can distinguish and characterize WM fibers involved in edematus, tumoral, and normal brain areas with reasonable confidence. Further studies will be required to improve the detectability of WM fibers inside the solid tumor if they hypothetically exist in tumoral parenchyma.

Correlation Between Aquaporin 4 Expression and Different DWI Parameters in Grade I Meningioma

PURPOSE

Diffusion-weighted imaging (DWI) measures water diffusion in biological tissues. Cellular water transport depends on aquaporins (AQPs). The expression of aquaporins might differ in several pathologic disorders. Therefore, the aim of this study was to evaluate the associations between AQP4 expression and different DWI parameters in meningioma.

PROCEDURES

Twenty-three patients with meningioma grade I were included in this retrospective study. DWI was obtained with three b values (0; 500; 1000) using a 1.5-T device. ADC_mean, ADC_min, ADC_max, and true diffusion coefficients (D) were obtained in every patient. Aquaporin 4 expression was quantified immunohistochemically in four immunoreactivity levels.

RESULTS

The estimated DWI parameters (mean value ± standard deviation, 10^-3 mm² s^-1) of the tumors were as follows: ADC_min 0.67 ± 0.16, ADC_mean 0.94 ± 0.23, ADC_max 1.29 ± 0.50, and D 0.65 ± 0.23. The mean level of the AQP4 expression was 2.02 ± 0.75 points. A statistically significant correlation between AQP4 expression and ADC_max was identified (r = 0.508, p = 0.013). No significant correlations between AQP4 and other DWI parameters were found.

CONCLUSIONS

A clear correlation between AQP4 expression and ADC_max values in grade I meningioma was identified. There were no significant correlations between AQP4 expression and other DWI parameters, such as ADC_min, ADC_mean, and D.

Apparent diffusion coefficient changes predict survival after intra-arterial bevacizumab treatment in recurrent glioblastoma

PURPOSE

Superselective intra-arterial cerebral infusion (SIACI) of bevacizumab (BV) has emerged as a novel therapy in the treatment of recurrent glioblastoma (GB). This study assessed the use of apparent diffusion coefficient (ADC) in predicting length of survival after SIACI BV and overall survival in patients with recurrent GB.

METHODS

Sixty-five patients from a cohort enrolled in a phase I/II trial of SIACI BV for treatment of recurrent GB were retrospectively included in this analysis. MR imaging with a diffusion-weighted (DWI) sequence was performed before and after treatment. ROIs were manually delineated on ADC maps corresponding to the enhancing and non-enhancing portions of the tumor. Cox and logistic regression analyses were performed to determine which ADC values best predicted survival.

RESULTS

The change in minimum ADC in the enhancing portion of the tumor after SIACI BV therapy was associated with an increased risk of death (hazard ratio = 2.0, 95% confidence interval(CI) [1.04-3.79], p = 0.038), adjusting for age, tumor size, BV dose, and prior IV BV treatments. Similarly, the change in ADC after SIACI BV therapy was associated with greater likelihood of surviving less than 1 year after therapy (odds ratio = 7.0, 95% CI [1.08-45.7], p = 0.04). Having previously received IV BV was associated with increased risk of death (OR 18, 95% CI [1.8-180.0], p = 0.014).

CONCLUSION

In patients with recurrent GB treated with SIACI BV, the change in ADC value after treatment is predictive of overall survival.

Comparisons among MRI signs, apparent diffusion coefficient, and fractional anisotropy in dogs with a solitary intracranial meningioma or histiocytic sarcoma

Although MRI has become widely used in small animal practice, little is known about the validity of advanced MRI techniques such as diffusion-weighted imaging and diffusion tensor imaging. The aim of this retrospective analytical observational study was to investigate the characteristics of diffusion parameters, that is the apparent diffusion coefficient and fractional anisotropy, in dogs with a solitary intracranial meningioma or histiocytic sarcoma. Dogs were included based on the performance of diffusion MRI and histological confirmation. Statistical analyses were performed to compare apparent diffusion coefficient and fractional anisotropy for the two types of tumor in the intra- and peritumoral regions. Eleven cases with meningioma and six with histiocytic sarcoma satisfied the inclusion criteria. Significant differences in apparent diffusion coefficient value (× 10^-3 mm² /s) between meningioma vs. histiocytic sarcoma were recognized in intratumoral small (1.07 vs. 0.76) and large (1.04 vs. 0.77) regions of interest, in the peritumoral margin (0.93 vs. 1.08), and in the T2 high region (1.21 vs. 1.41). Significant differences in fractional anisotropy values were found in the peritumoral margin (0.29 vs. 0.24) and the T2 high region (0.24 vs. 0.17). The current study identified differences in measurements of apparent diffusion coefficient and fractional anisotropy for meningioma and histiocytic sarcoma in a small sample of dogs. In addition, we observed that all cases of intracranial histiocytic sarcoma showed leptomeningeal enhancement and/or mass formation invading into the sulci in the contrast study. Future studies are needed to determine the sensitivity of these imaging characteristics for differentiating between these tumor types.

Semiautomated Workflow for Clinically Streamlined Glioma Parametric Response Mapping

Management of glioblastoma multiforme remains a challenging problem despite recent advances in targeted therapies. Timely assessment of therapeutic agents is hindered by the lack of standard quantitative imaging protocols for determining targeted response. Clinical response assessment for brain tumors is determined by volumetric changes assessed at 10 weeks post-treatment initiation. Further, current clinical criteria fail to use advanced quantitative imaging approaches, such as diffusion and perfusion magnetic resonance imaging. Development of the parametric response mapping (PRM) applied to diffusion-weighted magnetic resonance imaging has provided a sensitive and early biomarker of successful cytotoxic therapy in brain tumors while maintaining a spatial context within the tumor. Although PRM provides an earlier readout than volumetry and sometimes greater sensitivity compared with traditional whole-tumor diffusion statistics, it is not routinely used for patient management; an automated and standardized software for performing the analysis and for the generation of a clinical report document is required for this. We present a semiautomated and seamless workflow for image coregistration, segmentation, and PRM classification of glioblastoma multiforme diffusion-weighted magnetic resonance imaging scans. The software solution can be integrated using local hardware or performed remotely in the cloud while providing connectivity to existing picture archive and communication systems. This is an important step toward implementing PRM analysis of solid tumors in routine clinical practice.

Diffusion MRI in early cancer therapeutic response assessment

Imaging biomarkers for the predictive assessment of treatment response in patients with cancer earlier than standard tumor volumetric metrics would provide new opportunities to individualize therapy. Diffusion-weighted MRI (DW-MRI), highly sensitive to microenvironmental alterations at the cellular level, has been evaluated extensively as a technique for the generation of quantitative and early imaging biomarkers of therapeutic response and clinical outcome. First demonstrated in a rodent tumor model, subsequent studies have shown that DW-MRI can be applied to many different solid tumors for the detection of changes in cellularity as measured indirectly by an increase in the apparent diffusion coefficient (ADC) of water molecules within the lesion. The introduction of quantitative DW-MRI into the treatment management of patients with cancer may aid physicians to individualize therapy, thereby minimizing unnecessary systemic toxicity associated with ineffective therapies, saving valuable time, reducing patient care costs and ultimately improving clinical outcome. This review covers the theoretical basis behind the application of DW-MRI to monitor therapeutic response in cancer, the analytical techniques used and the results obtained from various clinical studies that have demonstrated the efficacy of DW-MRI for the prediction of cancer treatment response. Copyright © 2016 John Wiley & Sons, Ltd.

Demonstration of Non-Gaussian Restricted Diffusion in Tumor Cells Using Diffusion Time-Dependent Diffusion-Weighted Magnetic Resonance Imaging Contrast

The diffusion-weighted magnetic resonance imaging (DWI) technique enables quantification of water mobility for probing microstructural properties of biological tissue and has become an effective tool for collecting information about the underlying pathology of cancerous tissue. Measurements using multiple b-values have indicated biexponential signal attenuation, ascribed to “fast” (high ADC) and “slow” (low ADC) diffusion components. In this empirical study, we investigate the properties of the diffusion time (Δ)-dependent components of the diffusion-weighted (DW) signal in a constant b-value experiment. A xenograft gliobastoma mouse was imaged using Δ = 11 ms, 20 ms, 40 ms, 60 ms, and b = 500–4000 s/mm² in intervals of 500 s/mm². Data were corrected for EPI distortions, and the Δ-dependence on the DW-signal was measured within three regions of interest [intermediate- and high-density tumor regions and normal-appearing brain (NAB) tissue regions]. In this study, we verify the assumption that the slow decaying component of the DW-signal is non-Gaussian and dependent on Δ, consistent with restricted diffusion of the intracellular space. As the DW-signal is a function of Δ and is specific to restricted diffusion, manipulating Δ at constant b-value (cb) provides a complementary and direct approach for separating the restricted from the hindered diffusion component. We found that Δ-dependence is specific to the tumor tissue signal. Based on an extended biexponential model, we verified the interpretation of the diffusion time-dependent contrast and successfully estimated the intracellular restricted ADC, signal volume fraction, and cell size within each ROI.

Quantification of diffusion and anisotropy in intracranial epidermoids using diffusion tensor metrics and p: q tensor decomposition

PURPOSE

To quantitatively evaluate the diffusion tensor metrics p, q, L and fractional anisotropy in intracranial epidermoids in comparison with normal white matter in the splenium of the corpus callosum.

METHODS

This retrospective study included 20 consecutive patients referred to our institute. All patients had a magnetic resonance imaging (MRI) study on a 1.5-Tesla MR system. A spin-echo echo-planar DTI sequence with diffusion gradients along 30 non-collinear directions was performed. The eigen values (λ₁, λ₂, λ₃) were computed for each voxel and, using p: q tensor decomposition, the DTI metrics p, q and L-values and fractional anositropy (FA) were calculated. The region of interest (ROI) (6 pixels each) was placed within the lesion in all the cases and in the splenium of the corpus callosum.

RESULTS

The mean FA in the lesion and splenium were 0.50 and 0.88 respectively, with a statistically significant difference between them (P<0.01). On p: q tensor decomposition, the mean p-value in the epidermoid was 1.55±0.24 and 1.35±0.20 in the splenium; the mean q-values in the epidermoid was 0.67±0.13 and 1.27±0.17 in the splenium; the differences were statistically significant (P=0.01 and <0.01 respectively). The significant difference between p- and q-values in epidermoids compared with the splenium of callosum was probably due to structural and orientation differences in the keratin flakes in epidermoids and white matter bundles in the callosum. However, no significant statistical difference in L-values was noted (P=0.44).

CONCLUSION

DTI metrics p and q have the potential to quantify the diffusion and anisotropy in various tissues thereby gaining information about their internal architecture. The results also suggest that significant differences of DTI metrics p and q between epidermoid and the splenium of the corpus callosum are due to the difference in structural organization within them.

Non-parametric intravoxel incoherent motion analysis in patients with intracranial lesions: Test-retest reliability and correlation with arterial spin labeling

Intravoxel incoherent motion (IVIM) analysis of diffusion imaging data provides biomarkers of true passive water diffusion and perfusion properties. A new IVIM algorithm with variable adjustment of the b-value threshold separating diffusion and perfusion effects was applied for cerebral tissue characterization in healthy volunteers, computation of test-retest reliability, correlation with arterial spin labeling, and assessment of applicability in a small cohort of patients with malignant intracranial masses. The main results of this study are threefold: (i) accounting for regional differences in the separation of the perfusion and the diffusion components improves the reliability of the model parameters; (ii) if differences in the b-value threshold are not accounted for, a significant tissue-dependent systematic bias of the IVIM parameters occurs; (iii) accounting for voxel-wise differences in the b-value threshold improves the correlation with CBF measurements in healthy volunteers and patients. The proposed algorithm provides a robust characterization of regional micro-vascularization and cellularity without a priori assumptions on tissue diffusion properties. The glioblastoma multiforme with its inherently high variability of tumor vascularization and tumor cell density may benefit from a non-invasive clinical characterization of diffusion and perfusion properties.

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The novel IVIM algorithm accounts for regional differences in the separation of the perfusion and the diffusion components.

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The algorithm improves the reliability of IVIM parameters.

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The algorithm improves the correlation with CBF in healthy volunteers and patients.

Restriction spectrum imaging predicts response to bevacizumab in patients with high-grade glioma

BACKGROUND

Diffusion-weighted imaging has shown initial promise for evaluating response to bevacizumab in patients with high-grade glioma (HGG). However, it is well recognized that the apparent diffusion coefficient (ADC) is influenced by bevacizumab-induced reductions in edema, which may limit its prognostic value. We demonstrate that an advanced diffusion-weighted imaging technique, restriction spectrum imaging (RSI), improves the evaluation of response to bevacizumab because unlike ADC, RSI is not affected by resolution of edema.

METHODS

RSI and ADC maps were analyzed for 40 patients with HGG prior to and following initiation of bevacizumab. Volumes of interest were drawn for regions of contrast enhancement (CE) and fluid attenuated inversion recovery (FLAIR) hyperintensity and histogram percentiles within volumes of interest were calculated for ADC 10th percentile (ADC-CE_10%, ADC-FLAIR_10%) and for RSI 90th percentile (RSI-CE_90%, RSI-FLAIR_90%). Cox proportional hazard models were used to evaluate the relationship between imaging parameters, progression-free survival (PFS), and overall survival (OS).

RESULTS

An increase in RSI-FLAIR_90% following bevacizumab was the strongest predictor of poor PFS (P= .016) and OS (P= .004), whereas decreases in ADC-FLAIR_10% showed a weaker association with OS only (P= .041). Within the CE region, increases in RSI-CE_90% alone were associated with poorer OS. Correlational analysis revealed that decreases in FLAIR volume were associated with decreases in ADC-FLAIR_10%, but not with changes in RSI-FLAIR_90%.

CONCLUSION

RSI is less influenced by changes in edema, conferring an advantage of RSI over ADC for evaluating response to anti-angiogenic therapy in patients with HGG.

Normalized Apparent Diffusion Coefficient in the Prognostication of Patients with Glioblastoma Multiforme

BACKGROUND

Glioblastoma multiforme (GBM) is known to have poor prognosis, with no available imaging marker that can predict survival at the time of diagnosis. Diffusion weighted images are used in characterisation of cellularity and necrosis of GBM. The purpose of this study was to assess whether pattern or degree of diffusion restriction could help in the prognostication of patients with GBM.

MATERIAL AND METHODS

We retrospectively analyzed 84 consecutive patients with confirmed GBM on biopsy or resection. The study was approved by the institutional ethics committee. The total volume of the tumor and total volume of tumor showing restricted diffusion were calculated. The lowest Apparent Diffusion Coefficient (ADC) in the region of the tumor and in the contralateral Normal Appearing White Matter were calculated in order to calculate the nADC. Treatment and follow-up data in these patients were recorded. Multivariate analsysis was completed to determine significant correlations between different variables and the survival of these patients.

RESULTS

Patient survival was significantly related to the age of the patient (p<0.0001; 95% CI-1.022-1.043) and the nADC value (p=0.014; 95% CI-0.269-0.860) in the tumor. The correlation coefficients of age and nADC with survival were -0.335 (p=0.002) and 0.390 (p<0.001), respectively. Kaplan Meier survival function, grouped by normalized Apparent Diffusion Coefficient cut off value of 0.75, was significant (p=0.007).

CONCLUSION

The survival of patients with GBM had small, but significant, correlations with the patient's age and nADC within the tumor.

Large-volume low apparent diffusion coefficient lesions predict poor survival in bevacizumab-treated glioblastoma patients

BACKGROUND

Glioblastomas treated with bevacizumab may develop low-signal apparent diffusion coefficient (low-ADC) lesions, which may reflect increased tumor cellularity or atypical necrosis. The purpose of this study was to examine the relationship between low-ADC lesions and overall survival (OS). We hypothesized that growing low-ADC lesions would be associated with shorter OS.

METHODS

We retrospectively identified 52 patients treated with bevacizumab for the first (n = 42, 81%) or later recurrence of primary glioblastoma, who had low-ADC lesions and 2 post-bevacizumab scans ≤90 days apart. Low-ADC lesion volumes were measured, and normalized 5th percentile histogram low-ADC values were recorded. Using OS as the primary endpoint, semiparametric Cox models were fitted to ascertain univariate and multivariate hazard ratios (HRs) with significance at P = .05.

RESULTS

Median OS was 9.1 months (95% CI = 7.2-14.3). At the second post-bevacizumab scan, the volume of the low-ADC lesion (median: 12.94 cm(3)) was inversely associated with OS, with larger volumes predicting shorter OS (HR = 1.014 [95% CI = 1.003-1.025], P = .009). The percent change in low-ADC volume (median: 6.8%) trended toward increased risk of death with growing volumes (P = .08). Normalized 5th percentile low-ADC value and its percent change were not associated with OS (P > .51). Also correlated with shorter OS were the pre-bevacizumab nonenhancing volume (P = .025), the first post-bevacizumab enhancing volume (P = .040), and the second post-bevacizumab enhancing volume (P = .004).

CONCLUSIONS

The volume of low-ADC lesions at the second post-bevacizumab scan predicted shorter OS. This suggests that low-ADC lesions may be considered important imaging markers and included in treatment decision algorithms.

Comparison between magnetic resonance spectroscopy and diffusion weighted imaging in the evaluation of gliomas response after treatment

PURPOSE

To compare magnetic resonance spectroscopy (MRS) and diffusion weighted imaging (DWI) in the assessment of progression and regression of brain tumors in order to assess whether there is correlation between MRS and DWI in the monitoring of patients with primary tumors after therapy.

METHODS

Magnetic resonance imaging (MRI) has been performed in 80 patients, 48 affected by high grade gliomas (HGG) and 32 affected by low grade gliomas (LGG). The variation of apparent diffusion coefficient (ADC) value and metabolite ratios before and after treatment has been used to test DWI sequences and MRS as predictor to response to therapy. Comparison between post contrast-enhancement sequences, MRS and DWI has been done in terms of accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Moreover statistical correlation of ADC deviations with MRS metabolites variations before and after therapy have been studied.

RESULTS

In the case of HGG, MRS shows better sensitivity, specificity, PPV, NPV and accuracy compared to DWI, especially when considering the Choline/N-acetylaspartate (Cho/NAA) ratio. Regarding the LGG, the technique that better evaluates the response to treatment appears to be the DWI. A moderate correlation between ADC deviations and Cho, Lipide (Lip) and Lactate (Lac) has been found in LGG; while NAA revealed to be weakly correlated to ADC variation. Considering HGG, a weak correlation has been found between ADC deviations and MRS metabolites.

CONCLUSION

Combination of DWI and MRS can help to characterize different changes related to treatment and to evaluate brain tumor response to treatment.

Individual differences in subcortical microstructure organization reflect reaction time performances during a flanker task: a diffusion tensor imaging study in children with and without ADHD

The results of several previous magnetic resonance imaging studies suggest that the fronto-striato-thalamic circuitry is involved in the pathophysiology of attention-deficit/hyperactivity disorder (ADHD). However, few studies have investigated the putative association between quantitative diffusion tensor imaging measurements of subcortical gray matter and subject task performances in children with ADHD. Here, we examined whether reaction time (RT) parameters during a flanker task were correlated with mean diffusivity (MD) measurements in the basal ganglia and thalamus in children with ADHD and in controls. For the study group as a whole, both the mean RT and the intra-individual variability in RTs were found to be significantly correlated with MD measurements in the right and left caudate, putamen and thalamus. In contrast, the correlation between the interference effect and MD failed to reach statistical significance. The present results may advance our understanding of the anatomical substrates of ADHD.

OKN-007 decreases tumor necrosis and tumor cell proliferation and increases apoptosis in a preclinical F98 rat glioma model

BACKGROUND

Glioblastoma is a malignant World Health Organization (WHO) grade IV glioma with a poor prognosis in humans. New therapeutics are desperately required. The nitrone OKN-007 (2,4-disulfophenyl-PBN) has demonstrated effective anti-glioma properties in several rodent models and is currently being used as a clinical investigational drug for recurrent gliomas. We assessed the regional effects of OKN-007 in the tumor necrotic core and non-necrotic tumor parenchyma.

METHODS

An F98 rat glioma model was evaluated using proton magnetic resonance spectroscopy ((1) H-MRS), diffusion-weighted imaging (DWI), morphological T2-weighted imaging (T2W) at 7 Tesla (30 cm-bore MRI), as well as immunohistochemistry and microarray assessments, at maximum tumor volumes (15-23 days following cell implantation in untreated (UT) tumors, and 18-35 days in OKN-007-treated tumors).

RESULTS

(1) H-MRS data indicates that Lip0.9/Cho, Lip0.9/Cr, Lip1.3/Cho, and Lip1.3/Cr ratios are significantly decreased (all P < 0.05) in the OKN-007-treated group compared with UT F98 gliomas. The Cho/Cr ratio is also significantly decreased in the OKN-007-treated group compared with UT gliomas. In addition, the OKN-007-treated group demonstrates significantly lower ADC values in the necrotic tumor core and the nonnecrotic tumor parenchyma (both P < 0.05) compared with the UT group. There was also an increase in apoptosis following OKN-007 treatment (P < 0.01) compared with UT.

CONCLUSION

OKN-007 reduces both necrosis and tumor cell proliferation, as well as seems to mediate multiple effects in different tumor regions (tumor necrotic core and nonnecrotic tumor parenchyma) in F98 gliomas, indicating the efficacy of OKN-007 as an anti-cancer agent and its potential clinical use.

Advanced magnetic resonance imaging of the physical processes in human glioblastoma

The most common malignant primary brain tumor, glioblastoma multiforme (GBM) is a devastating disease with a grim prognosis. Patient survival is typically less than two years and fewer than 10% of patients survive more than five years. Magnetic resonance imaging (MRI) can have great utility in the diagnosis, grading, and management of patients with GBM as many of the physical manifestations of the pathologic processes in GBM can be visualized and quantified using MRI. Newer MRI techniques such as dynamic contrast enhanced and dynamic susceptibility contrast MRI provide functional information about the tumor hemodynamic status. Diffusion MRI can shed light on tumor cellularity and the disruption of white matter tracts in the proximity of tumors. MR spectroscopy can be used to study new tumor tissue markers such as IDH mutations. MRI is helping to noninvasively explore the link between the molecular basis of gliomas and the imaging characteristics of their physical processes. We, here, review several approaches to MR-based imaging and discuss the potential for these techniques to quantify the physical processes in glioblastoma, including tumor cellularity and vascularity, metabolite expression, and patterns of tumor growth and recurrence. We conclude with challenges and opportunities for further research in applying physical principles to better understand the biologic process in this deadly disease. See all articles in this Cancer Research section, "Physics in Cancer Research."

Diffusion-weighted imaging in cancer: physical foundations and applications of restriction spectrum imaging

Diffusion-weighted imaging (DWI) has been at the forefront of cancer imaging since the early 2000s. Before its application in clinical oncology, this powerful technique had already achieved widespread recognition due to its utility in the diagnosis of cerebral infarction. Following this initial success, the ability of DWI to detect inherent tissue contrast began to be exploited in the field of oncology. Although the initial oncologic applications for tumor detection and characterization, assessing treatment response, and predicting survival were primarily in the field of neurooncology, the scope of DWI has since broadened to include oncologic imaging of the prostate gland, breast, and liver. Despite its growing success and application, misconceptions about the underlying physical basis of the DWI signal exist among researchers and clinicians alike. In this review, we provide a detailed explanation of the biophysical basis of diffusion contrast, emphasizing the difference between hindered and restricted diffusion, and elucidating how diffusion parameters in tissue are derived from the measurements via the diffusion model. We describe one advanced DWI modeling technique, called restriction spectrum imaging (RSI). This technique offers a more direct in vivo measure of tumor cells, due to its ability to distinguish separable pools of water within tissue based on their intrinsic diffusion characteristics. Using RSI as an example, we then highlight the ability of advanced DWI techniques to address key clinical challenges in neurooncology, including improved tumor conspicuity, distinguishing actual response to therapy from pseudoresponse, and delineation of white matter tracts in regions of peritumoral edema. We also discuss how RSI, combined with new methods for correction of spatial distortions inherent in diffusion MRI scans, may enable more precise spatial targeting of lesions, with implications for radiation oncology and surgical planning. See all articles in this Cancer Research section, "Physics in Cancer Research."

Diffusion tensor magnetic resonance imaging for predicting the consistency of intracranial meningiomas

BACKGROUND

The ability of preoperative MRI-sequences to predict the consistency of intracranial meningiomas has not yet been clearly defined. We aim to demonstrate that diffusion tensor imaging (DTI) improves the prediction of intracranial meningiomas consistency.

METHODS

We prospectively studied 110 meningioma patients operated on in a single center from March 1st to the 25th of May 2012. Demographic data, location and size of the tumor, peritumoral edema, T1WI, T2WI, proton density weighted (PDWI), fluid-attenuated inversion recover (FLAIR) sequences, and arterial spin labeling (ASL) perfusion were studied and compared with the gray matter signal to predict meningioma consistency. Diffusion tensor imaging (DTI) with fractional anisotropy (FA) and mean diffusivity (MD) maps were included in the preoperative MRI. Meningioma consistency was evaluated by the operating surgeon who was unaware of the neuroradiological findings.

RESULTS

In univariate analysis, meningioma size (diameter > 2 cm) and supratentorial or sphenoidal wing location were more frequently associated with hard-consistency meningiomas (p < 0.05). In addition, isointense signal on MD maps (p = 0.009), hyperintense signal on FA maps, and FA value > 0.3 (p = 0.00001) were associated with hard-consistency tumors. Age and sex, T1WI, T2WI, PDWI, FLAIR, or ASL perfusion sequences and peritumoral edema were not significantly associated with meningioma consistency. In logistic regression analysis, the most accurate model (AUC: 0.9459) for predicting a hard-consistency meningioma shows that an isointense signal in MD-maps, a hyperintense signal in FA-maps, and an FA value of more than 0.3 have a significant predictive value.

CONCLUSIONS

FA value and MD and FA maps are useful for prediction of meningioma consistency and, therefore, may be considered in the preoperative routine MRI examination of all patients with intracranial meningiomas.

MRI molecular imaging using GLUT1 antibody-Fe3O4 nanoparticles in the hemangioma animal model for differentiating infantile hemangioma from vascular malformation

The purpose of this study is to evaluate the efficacy of glucose transporter protein 1 (GLUT1) antibody-conjugated iron oxide nanoparticles (Fe3O4 NPs) as magnetic resonance imaging (MRI) molecular imaging agents for differentiating infantile hemangioma from vascular malformation in the hemangioma animal model. The conjugation of Fe3O4 NPs with anti-GLUT1 antibodies leads to a significantly increased uptake of NPs by human umbilical vein endothelial cells. MRI imaging following the intravenous injection of GLUT1 antibody-Fe3O4 NPs yielded a significantly lower signal intensity than did unconjugated Fe3O4 NPs. Upon histological examination of the GLUT1 antibody-Fe3O4 NPs, Prussian blue-stained NPs were identified in CD31-positive endothelial cells of hemangioma. In contrast, when treated with unconjugated Fe3O4 NPs, Prussian blue-stained NPs were found in macrophages rather than in endothelial cells. GLUT1 antibody conjugation can effectively target the injected Fe3O4 NPs to GLUT1-positive tumor cells in infantile hemangioma.

Longitudinal restriction spectrum imaging is resistant to pseudoresponse in patients with high-grade gliomas treated with bevacizumab

BACKGROUND AND PURPOSE

Antiangiogenic therapies, such as bevacizumab, decrease contrast enhancement and FLAIR hyperintensity in patients with high-grade gliomas in a manner that may not correlate with actual tumor response. This study evaluated the ability of an advanced DWI technique, restriction spectrum imaging, to improve conspicuity within regions of restricted diffusion compared with ADC in patients treated with bevacizumab and to demonstrate that unlike ADC, restriction spectrum imaging is less affected by bevacizumab-induced reductions in FLAIR hyperintensity.

MATERIALS AND METHODS

Restriction spectrum imaging cellularity maps and DWI were available for 12 patients with recurrent high-grade gliomas at baseline and following initiation of bevacizumab. VOIs were drawn for regions of restricted diffusion, surrounding FLAIR hyperintensity, and normal-appearing white matter; and intensity values within regions of restricted diffusion and FLAIR hyperintensity were normalized to normal-appearing white matter. Normalized values were compared between restriction spectrum imaging cellularity maps and ADC at baseline and on treatment by using repeated-measures ANOVA.

RESULTS

All patients exhibited decreases in contrast enhancement and FLAIR hyperintensity following treatment. Normalized intensity values were higher on restriction spectrum imaging cellularity maps compared with ADC in regions of restricted diffusion, whereas intensity values were higher on ADC compared with restriction spectrum imaging cellularity maps in regions of FLAIR hyperintensity. Bevacizumab-induced decreases in FLAIR hyperintensity had a greater effect on ADC than on the restriction spectrum imaging cellularity maps, with the relative sensitivity of ADC to changes in FLAIR hyperintensity being >20 times higher than that on restriction spectrum imaging cellularity maps.

CONCLUSIONS

Restriction spectrum imaging is less influenced by reductions in FLAIR hyperintensity compared with ADC, which may confer an advantage of restriction spectrum imaging over ADC for interpreting tumor response on imaging following antiangiogenic therapy.

Predictive significance of mean apparent diffusion coefficient value for responsiveness of temozolomide-refractory malignant glioma to bevacizumab: preliminary report

BACKGROUND

Recurrent glioblastoma after initial radiotherapy plus concomitant and adjuvant temozolomide is problematic. Here, patients with temozolomide-refractory high-grade gliomas were treated with bevacizumab (BV) and evaluated using apparent diffusion coefficient (ADC) for response.

METHODS

Nine post-temozolomide recurrent or progressive high-grade glioma patients (seven with glioblastoma and two with anaplastic astrocytoma) were treated with BV monotherapy. Average age was 57 years (range, 22-78), median Karnofsky Performance Scale (KPS) was 70 (30-80) and median BV line number was 2 (2-5). Two had additional stereotactic radiotherapy within 6 months prior to BV. Magnetic resonance (MR) imaging after BV therapy was performed within 2 weeks with calculation of mean ADC (mADC) values of enhancing tumor contours.

RESULTS

Post-BV treatment MR imaging showed decreased tumor volumes in eight of nine cases (88.9 %). Partial response was obtained in four cases (44.4 %), four cases had stable disease, and one had progressive disease. Of 15 evaluable enhancing lesions, 11 shrank and four did not. Pretreatment mADC values were above 1100 (10(-6) mm(2)/s) in all responding tumors, while all non-responding lesions scored below 1100 (p = 0.001). mADC decreased after the first BV treatment in all lesions except one. KPS improved in four cases (44.4 %). Median progression-free survival and overall survival for those having all lesions with high mADC (>1100) were significantly longer than those with a low mADC (<1100) lesion (p = 0.018 and 0.046, respectively).

CONCLUSIONS

Bevacizumab monotherapy is effective in patients with temozolomide-refractory recurrent gliomas and tumor mean ADC value can be a useful marker for prediction of BV response and survival.

Preclinical molecular imaging using PET and MRI

Molecular imaging fundamentally changes the way we look at cancer. Imaging paradigms are now shifting away from classical morphological measures towards the assessment of functional, metabolic, cellular, and molecular information in vivo. Interdisciplinary driven developments of imaging methodology and probe molecules utilizing animal models of human cancers have enhanced our ability to non-invasively characterize neoplastic tissue and follow anti-cancer treatments. Preclinical molecular imaging offers a whole palette of excellent methodology to choose from. We will focus on positron emission tomography (PET) and magnetic resonance imaging (MRI) techniques, since they provide excellent and complementary molecular imaging capabilities and bear high potential for clinical translation. Prerequisites and consequences of using animal models as surrogates of human cancers in preclinical molecular imaging are outlined. We present physical principles, values and limitations of PET and MRI as molecular imaging modalities and comment on their high potential to non-invasively assess information on hypoxia, angiogenesis, apoptosis, gene expression, metabolism, and cell trafficking in preclinical cancer research.

Improved conspicuity and delineation of high-grade primary and metastatic brain tumors using "restriction spectrum imaging": quantitative comparison with high B-value DWI and ADC

BACKGROUND AND PURPOSE

Restriction spectrum imaging is a sensitive DWI technique for probing separable water diffusion compartments in tissues. Here, we evaluate RSI-CMs derived from the spherically-restricted water compartment for improved tumor conspicuity and delineation from nontumor tissue and reduced sensitivity to edema compared with high-b-value DWI and ADC.

MATERIALS AND METHODS

RSI was performed in 10 presurgical patients: 4 with glioblastoma, 3 with primary CNS lymphoma, and 3 with metastatic brain tumors. Multidirectional DWI data were collected at b = 500, 1500, and 4000 s/mm(2). Quantification of tumor conspicuity, edema conspicuity, and relative sensitivity to edema for RSI-CMs; DWI at b = 4000 (DWI-4000); and ADC were compared in manually drawn VOIs. Receiver operating characteristic curves were used to evaluate the sensitivity and specificity of each method for delineating tumor from normal-appearing WM.

RESULTS

Significant TC was seen with both RSI-CMs and DWI-4000, but not ADC. Significant EC was seen with ADC, but not RSI-CMs or DWI-4000. Significantly greater TC was seen with RSI-CMs compared with DWI-4000. Significantly reduced RSE was seen with RSI-CMs compared with both DWI-4000 and ADC. Greater sensitivity and specificity for delineating tumor from normal-appearing WM were seen with RSI-CMs (AUC = 0.91) compared with both DWI-4000 (AUC = 0.77) and ADC (AUC = 0.66).

CONCLUSIONS

RSI-CMs offer improved conspicuity and delineation of high-grade primary and metastatic brain tumors and reduced sensitivity to edema compared with high-b-value DWI and ADC.

DCE and DW-MRI monitoring of vascular disruption following VEGF-Trap treatment of a rat glioma model

Vascular-targeted therapies have shown promise as adjuvant cancer treatment. As these agents undergo clinical evaluation, sensitive imaging biomarkers are needed to assess drug target interaction and treatment response. In this study, dynamic contrast enhanced MRI (DCE-MRI) and diffusion-weighted MRI (DW-MRI) were evaluated for detecting response of intracerebral 9 L gliosarcomas to the antivascular agent VEGF-Trap, a fusion protein designed to bind all forms of Vascular Endothelial Growth Factor-A (VEGF-A) and Placental Growth Factor (PGF). Rats with 9 L tumors were treated twice weekly for two weeks with vehicle or VEGF-Trap. DCE- and DW-MRI were performed one day prior to treatment initiation and one day following each administered dose. Kinetic parameters (K(trans), volume transfer constant; k(ep), efflux rate constant from extravascular/extracellular space to plasma; and v(p), blood plasma volume fraction) and the apparent diffusion coefficient (ADC) over the tumor volumes were compared between groups. A significant decrease in kinetic parameters was observed 24 hours following the first dose of VEGF-Trap in treated versus control animals (p < 0.05) and was accompanied by a decline in ADC values. In addition to the significant hemodynamic effect, VEGF-Trap treated animals exhibited significantly longer tumor doubling times (p < 0.05) compared to the controls. Histological findings were found to support imaging response metrics. In conclusion, kinetic MRI parameters and change in ADC have been found to serve as sensitive and early biomarkers of VEGF-Trap anti-vascular targeted therapy.