Neoadjuvant chemotherapy for high-grade serous ovarian cancer: radiologic-pathologic correlation of response assessment and predictors of progression.

PURPOSE: Neoadjuvant chemotherapy is often administered for high-grade serous ovarian carcinoma (HGSC) prior to cytoreductive surgery. We evaluated treatment response by CT (simplified peritoneal carcinomatosis index [S-PCI]), pathology (chemotherapy response score [CRS]), laboratory markers (serum CA-125), and surgical outcomes, to identify predictors of disease-free survival. METHODS: For this retrospective, HIPAA-compliant, IRB-approved study, we identified 396 women with HGSC receiving neoadjuvant chemotherapy between 2010 and 2019. Two hundred and ninety-nine patients were excluded (surgery not performed; imaging/pathology unavailable). Pre- and post-treatment abdominopelvic CTs were assigned CT S-PCI scores 0-24 (higher score indicating more tumor). Specimens were assigned CRS of 1-3 (minimal to complete response). Clinical data were obtained via chart review. Univariate, multivariate, and survival analyses were performed. RESULTS: Ninety-seven women were studied, with mean age of 65 years ± 10. Interreader agreement was good to excellent for CT S-PCI scores (ICC 0.64-0.77). Despite a significant decrease in CT S-PCI scores after treatment (p < 0.001), mean decrease in CT S-PCI did not differ significantly among CRS categories (p = 0.20) or between patients who were optimally versus suboptimally debulked (p = 0.29). In a survival analysis, lower CRS (more viable tumor) was associated with shorter time to progression (p < 0.001). A joint Cox proportional-hazard models showed that only residual pathologic disease (CRS 1/2) (HR 4.19; p < 0.001) and change in CA-125 (HR 1.79; p = 0.01) predicted progression. CONCLUSION: HGSC response to neoadjuvant therapy by CT S-PCI did not predict pathologic CRS score, optimal debulking, or progression, revealing discordance between imaging, pathologic, biochemical, and surgical assessments of tumor response.

A framework of NGO inside and outside strategies in the commercial determinants of health: findings from a narrative review.

BACKGROUND: Public health scholarship has uncovered a wide range of strategies used by industry actors to promote their products and influence government regulation. Less is known about the strategies used by non-government organisations to attempt to influence commercial practices. This narrative review applies a political science typology to identify a suite of 'inside' and 'outside' strategies used by NGOs to attempt to influence the commercial determinants of health. METHODS: We conducted a systematic search in Web of Science, ProQuest and Scopus. Articles were eligible for inclusion if they comprised an empirical study, explicitly sought to examine 'NGOs', were in English, and identified at least one NGO strategy aimed at commercial and/or government policy and practice. RESULTS: One hundred forty-four studies met the inclusion criteria. Eight industry sectors were identified: extractive, tobacco, food, alcohol, pharmaceuticals, weapons, textiles and asbestos, and a small number of general studies. We identified 18 types of NGO strategies, categorised according to the target (i.e. commercial actor or government actor) and type of interaction with the target (i.e. inside or outside). Of these, five NGO 'inside' strategies targeted commercial actors directly: 1) participation in partnerships and multistakeholder initiatives; 2) private meetings and roundtables; 3) engaging with company AGMs and shareholders; 4) collaborations other than partnerships; and 5) litigation. 'Outside' strategies targeting commercial actors through the mobilisation of public opinion included 1) monitoring and reporting; 2) protests at industry sites; 3) boycotts; 4) directly engaging the public; and 5) creative use of alternative spaces. Four NGO 'inside' strategies directly targeting government actors included: 1) lobbying; 2) drafting legislation, policies and standards; 3) providing technical support and training; and 4) litigation. NGO 'outside' strategies targeting government included 1) protests and public campaigns; 2) monitoring and reporting; 3) forum shifting; and 4) proposing and initiating alternative solutions. We identified three types of NGO impact: substantive, procedural, and normative. CONCLUSION: The analysis presents a matrix of NGO strategies used to target commercial and government actors across a range of industry sectors. This framework can be used to guide examination of which NGO strategies are effective and appropriate, and which conditions enable NGO influence.

A Data-Driven Approach to Predicting 5-Aminolevulinic Acid-Induced Fluorescence and World Health Organization Grade in Newly Diagnosed Diffuse Gliomas.

BACKGROUND: A growing body of evidence has revealed the potential utility of 5-aminolevulinic acid (5-ALA) as a surgical adjunct in selected lower-grade gliomas. However, a reliable means of identifying which lower-grade gliomas will fluoresce has not been established. OBJECTIVE: To identify clinical and radiological factors predictive of intraoperative fluorescence in intermediate-grade gliomas. In addition, given that higher-grade gliomas are more likely to fluoresce than lower-grade gliomas, we also sought to develop a means of predicting glioma grade. METHODS: We investigated a cohort of patients with grade II and grade III gliomas who received 5-ALA before resection at a single institution. Using a logistic regression-based model, we evaluated 14 clinical and molecular variables considered plausible determinants of fluorescence. We then distilled the most predictive features to develop a model for predicting both fluorescence and tumor grade. We also explored the relationship between intraoperative fluorescence and diagnostic molecular markers. RESULTS: One hundered seventy-nine subjects were eligible for inclusion. Our logistic regression classifier accurately predicted intraoperative fluorescence in our cohort with 91.9% accuracy and revealed enhancement as the singular variable in determining intraoperative fluorescence. There was a direct relationship between enhancement on MRI and the likelihood of observed fluorescence. Observed fluorescence correlated with MIB-1 index but not with isocitrate dehydrogenase (IDH) status, 1p19q codeletion, or methylguanine DNA methyltransferase promoter methylation. CONCLUSION: We demonstrate a strong correlation between enhancement on preoperative MRI and the likelihood of visible fluorescence during surgery in patients with intermediate-grade glioma. Our analysis provides a robust method for predicting 5-ALA-induced fluorescence in patients with grade II and grade III gliomas.

A Comprehensive Assessment of 68Ga-PSMA-11 PET in Biochemically Recurrent Prostate Cancer: Results from a Prospective Multicenter Study on 2,005 Patients.

We prospectively investigated the performance of the prostate-specific membrane antigen (PSMA) ligand 68Ga-PSMA-11 for detecting prostate adenocarcinoma in patients with elevated levels of prostate-specific antigen (PSA) after initial therapy. Methods:68Ga-PSMA-11 hybrid PET was performed on 2,005 patients at the time of biochemically recurrent prostate cancer after radical prostatectomy (RP) (50.8%), definitive radiation therapy (RT) (19.7%), or RP with postoperative RT (PORT) (29.6%). The presence of prostate cancer was assessed qualitatively (detection rate = positivity rate) and quantitatively on a per-patient and per-region basis, creating a disease burden estimate from the presence or absence of local (prostate/prostate bed), nodal (N1: pelvis), and distant metastatic (M1: distant soft tissue and bone) disease. The primary study endpoint was the positive predictive value (PPV) of 68Ga-PSMA-11 PET/CT confirmed by histopathology. Results: After RP, the scan detection rate increased significantly with rising PSA level (44.8% at PSA < 0.25%-96.2% at PSA > 10 ng/mL; P < 0.001). The detection rate significantly increased with rising PSA level in each individual region, overall disease burden, prior androgen deprivation, clinical T-stage, and Gleason grading from the RP specimen (P < 0.001). After RT, the detection rate for in-gland prostate recurrence was 64.0%, compared with 20.6% prostate bed recurrence after RP and 13.3% after PORT. PSMA-positive pelvic nodal disease was detected in 42.7% after RP, 40.8% after PORT, and 38.8% after RT. In patients with histopathologic validation, the PPV per patient was 0.82 (146/179). The SUVmax of histologically proven true-positive lesions was significantly higher than that of false-positive lesions (median, 11.0 [interquartile range, 6.3-22.2] vs. 5.1 [interquartile range, 2.2-7.4]; P < 0.001). Conclusion: We confirmed a high PPV for 68Ga-PSMA-11 PET in biochemical recurrence and the PSA level as the main predictor of scan positivity.

Improved detection of air trapping on expiratory computed tomography using deep learning.

BACKGROUND: Radiologic evidence of air trapping (AT) on expiratory computed tomography (CT) scans is associated with early pulmonary dysfunction in patients with cystic fibrosis (CF). However, standard techniques for quantitative assessment of AT are highly variable, resulting in limited efficacy for monitoring disease progression. OBJECTIVE: To investigate the effectiveness of a convolutional neural network (CNN) model for quantifying and monitoring AT, and to compare it with other quantitative AT measures obtained from threshold-based techniques. MATERIALS AND METHODS: Paired volumetric whole lung inspiratory and expiratory CT scans were obtained at four time points (0, 3, 12 and 24 months) on 36 subjects with mild CF lung disease. A densely connected CNN (DN) was trained using AT segmentation maps generated from a personalized threshold-based method (PTM). Quantitative AT (QAT) values, presented as the relative volume of AT over the lungs, from the DN approach were compared to QAT values from the PTM method. Radiographic assessment, spirometric measures, and clinical scores were correlated to the DN QAT values using a linear mixed effects model. RESULTS: QAT values from the DN were found to increase from 8.65% ± 1.38% to 21.38% ± 1.82%, respectively, over a two-year period. Comparison of CNN model results to intensity-based measures demonstrated a systematic drop in the Dice coefficient over time (decreased from 0.86 ± 0.03 to 0.45 ± 0.04). The trends observed in DN QAT values were consistent with clinical scores for AT, bronchiectasis, and mucus plugging. In addition, the DN approach was found to be less susceptible to variations in expiratory deflation levels than the threshold-based approach. CONCLUSION: The CNN model effectively delineated AT on expiratory CT scans, which provides an automated and objective approach for assessing and monitoring AT in CF patients.

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 (PRMrFLAIR+), decreased (PRMrFLAIR-), or unchanged (PRMrFLAIR0) 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 PRMrFLAIR between weeks 10 and 20 and continuously until the PRMrFLAIR+ 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 PRMrFLAIR+ (PFS: p <0.01; OS: p <0.001). PRMrFLAIR+ 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, PRMrFLAIR+ 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: PRMrFLAIR may provide an early biomarker of disease progression in glioblastoma.

Lung T1 mapping magnetic resonance imaging in the assessment of pulmonary disease in children with cystic fibrosis: a pilot study.

BACKGROUND: Assessment tools for early cystic fibrosis (CF) lung disease are limited. Detecting early pulmonary disease is crucial to increasing life expectancy by starting interventions to slow the progression of the pulmonary disease with the many treatment options available. OBJECTIVE: To compare the utility of lung T1-mapping MRI with ultrashort echo time (UTE) MRI in children with cystic fibrosis in detecting early stage lung disease and monitoring pulmonary exacerbations. MATERIALS AND METHODS: We performed a prospective study in 16 children between September 2017 and January 2018. In Phase 1, we compared five CF patients with normal spirometry (mean 11.2 years) to five age- and gender-matched healthy volunteers. In Phase 2, we longitudinally evaluated six CF patients (median 11 years) in acute pulmonary exacerbation. All children had non-contrast lung T1-mapping and UTE MRI and spirometry testing. We compared the mean normalized T1 value and percentage lung volume without T1 value in CF patients and healthy subjects in Phase 1 and during treatment in Phase 2. We also performed cystic fibrosis MRI scoring. We evaluated differences in continuous variables using standard statistical tests. RESULTS: In Phase 1, mean normalized T1 values of the lung were significantly lower in CF patients in comparison to healthy controls (P=0.02) except in the right lower lobe (P=0.29). The percentage lung volume without T1 value was also significantly higher in CF patients (P=0.006). UTE MRI showed no significant differences between CF patients and healthy volunteers (P=0.11). In Phase 2, excluding one outlier case who developed systemic disease in the course of treatment, the whole-lung T1 value increased (P=0.001) and perfusion scoring improved (P=0.02) following therapy. We observed no other significant changes in the MRI scoring. CONCLUSION: Lung T1-mapping MRI can detect early regional pulmonary CF disease in children and might be helpful in the assessment of acute pulmonary exacerbations.

Multicenter evaluation of parametric response mapping as an indicator of bronchiolitis obliterans syndrome after hematopoietic stem cell transplantation.

Parametric response mapping (PRM) is a novel computed tomography (CT) technology that has shown potential for assessment of bronchiolitis obliterans syndrome (BOS) after hematopoietic stem cell transplantation (HCT). The primary aim of this study was to evaluate whether variations in image acquisition under real-world conditions affect the PRM measurements of clinically diagnosed BOS. CT scans were obtained retrospectively from 72 HCT recipients with BOS and graft-versus-host disease from Fred Hutchinson Cancer Research Center, Karolinska Institute, and the University of Michigan. Whole lung volumetric scans were performed at inspiration and expiration using site-specific acquisition and reconstruction protocols. PRM and pulmonary function measurements were assessed. Patients with moderately severe BOS at diagnosis (median forced expiratory volume at 1 second [FEV1] 53.5% predicted) had similar characteristics between sites. Variations in site-specific CT acquisition protocols had a negligible effect on the PRM-derived small airways disease (SAD), that is, BOS measurements. PRM-derived SAD was found to correlate with FEV1% predicted and FEV1/ forced vital capacity (R = -0.236, P = .046; and R = -0.689, P < .0001, respectively), which suggests that elevated levels in the PRM measurements are primarily affected by BOS airflow obstruction and not CT scan acquisition parameters. Based on these results, PRM may be applied broadly for post-HCT diagnosis and monitoring of BOS.

Near real-time intraoperative brain tumor diagnosis using stimulated Raman histology and deep neural networks.

Intraoperative diagnosis is essential for providing safe and effective care during cancer surgery1. The existing workflow for intraoperative diagnosis based on hematoxylin and eosin staining of processed tissue is time, resource and labor intensive2,3. Moreover, interpretation of intraoperative histologic images is dependent on a contracting, unevenly distributed, pathology workforce4. In the present study, we report a parallel workflow that combines stimulated Raman histology (SRH)5-7, a label-free optical imaging method and deep convolutional neural networks (CNNs) to predict diagnosis at the bedside in near real-time in an automated fashion. Specifically, our CNNs, trained on over 2.5 million SRH images, predict brain tumor diagnosis in the operating room in under 150 s, an order of magnitude faster than conventional techniques (for example, 20-30 min)2. In a multicenter, prospective clinical trial (n = 278), we demonstrated that CNN-based diagnosis of SRH images was noninferior to pathologist-based interpretation of conventional histologic images (overall accuracy, 94.6% versus 93.9%). Our CNNs learned a hierarchy of recognizable histologic feature representations to classify the major histopathologic classes of brain tumors. In addition, we implemented a semantic segmentation method to identify tumor-infiltrated diagnostic regions within SRH images. These results demonstrate how intraoperative cancer diagnosis can be streamlined, creating a complementary pathway for tissue diagnosis that is independent of a traditional pathology laboratory.

Effects of plasma glucose levels on regional cerebral 18F-fluorodeoxyglucose uptake: Implications for dementia evaluation with brain PET imaging.

PURPOSE: Hyperglycemia affects FDG uptake in the brain, potentially emulating Alzheimer's disease in normal individuals. This study investigates global and regional cerebral FDG uptake as a function of plasma glucose in a cohort of patients. METHODS: 120 consecutive male patients with FDG PET/CT for initial oncologic staging (July-Dec 2015) were reviewed. Patients with dementia, cerebrovascular accident, structural brain lesion, prior oncology treatment or high metabolic tumor burden (recently shown affecting brain FDG uptake) were excluded. 53 (24 nondiabetic) eligible patients (age 65.7 ± 2.8 mean ± SE) were analyzed with parametric computer software, MIMneuro™. Regional Z-scores were evaluated as a function of plasma glucose and age using multi variable linear mixed effects models with false discovery analysis adjusting for multiple comparisons. If the regression slope was significantly (p < 0.05) different than zero, hyperglycemia effect was present. RESULTS: There was a negative inverse relationship (p < 0.001) between global brain FDG uptake and hyperglycemia. No regional hyperglycemia effect on uptake were present when subjects were normalized using pons or cerebellum. However, regional hyperglycemia effects were seen (p < 0.047-0.001) when normalizing by the whole brain. No obvious pattern was seen in the regions affected. Age had a significant effect using whole brain normalization (p < 0.04-0.01). CONCLUSIONS: Cortical variation in FDG uptake were identified when subjects were hyperglycemic. However, these variations didn't fit a particular pattern of dementia and the severity of the affect is not likely to alter clinical interpretation.

A mixed-effects, spatially varying coefficients model with application to multi-resolution functional magnetic resonance imaging data.

Spatial resolution plays an important role in functional magnetic resonance imaging studies as the signal-to-noise ratio increases linearly with voxel volume. In scientific studies, where functional magnetic resonance imaging is widely used, the standard spatial resolution typically used is relatively low which ensures a relatively high signal-to-noise ratio. However, for pre-surgical functional magnetic resonance imaging analysis, where spatial accuracy is paramount, high-resolution functional magnetic resonance imaging may play an important role with its greater spatial resolution. High spatial resolution comes at the cost of a smaller signal-to-noise ratio. This begs the question as to whether we can leverage the higher signal-to-noise ratio of a standard functional magnetic resonance imaging study with the greater spatial accuracy of a high-resolution functional magnetic resonance imaging study in a pre-operative patient. To answer this question, we propose to regress the statistic image from a high resolution scan onto the statistic image obtained from a standard resolution scan using a mixed-effects model with spatially varying coefficients. We evaluate our model via simulation studies and we compare its performance with a recently proposed model that operates at a single spatial resolution. We apply and compare the two models on data from a patient awaiting tumor resection. Both simulation study results and the real data analysis demonstrate that our newly proposed model indeed leverages the larger signal-to-noise ratio of the standard spatial resolution scan while maintaining the advantages of the high spatial resolution scan.

Impact of Clinical History on Maximum PI-RADS Version 2 Score: A Six-Reader 120-Case Sham History Retrospective Evaluation.

Purpose To assess the impact of clinical history on the maximum Prostate Imaging Recording and Data System (PI-RADS) version 2 (v2) score assigned to multiparametric magnetic resonance (MR) imaging of the prostate. Materials and Methods This retrospective cohort study included 120 consecutively selected multiparametric prostate MR imaging studies performed between November 1, 2016, and December 31, 2016. Sham clinical data in four domains (digital rectal examination, prostate-specific antigen level, plan for biopsy, prior prostate cancer history) were randomly assigned to each case by using a balanced orthogonal design. Six fellowship-trained abdominal radiologists independently reviewed the sham data, actual patient age, and each examination while they were blinded to interreader scoring, true clinical data, and histologic findings. Readers were told the constant sham histories were true, believed the study to be primarily investigating interrater agreement, and were asked to assign a maximum PI-RADS v2 score to each case. Linear regression was performed to assess the association between clinical variables and maximum PI-RADS v2 score designation. Intraclass correlation coefficients (ICCs) were obtained to compare interreader scoring. Results Clinical information had no significant effect on maximum PI-RADS v2 scoring for any of the six readers (P = .09-.99, 42 reader-variable pairs). Distributions of maximum PI-RADS v2 scores in the research context were similar to the distribution of the scores assigned clinically and had fair-to-excellent pairwise interrater agreement (ICC range: 0.53-0.76). Overall interrater agreement was good (ICC: 0.64; 95% confidence interval: 0.57, 0.71). Conclusion Clinical history does not appear to be a substantial bias in maximum PI-RADS v2 score assignment. This is potentially important for clinical nomograms that plan to incorporate PI-RADS v2 score and clinical data into their algorithms (ie, PI-RADS v2 scoring is not confounded by clinical data).

Effects of Tumor Burden on Reference Tissue Standardized Uptake for PET Imaging: Modification of PERCIST Criteria.

Purpose To examine the effect metabolic burden (tumor and/or cardiac myocyte uptake) has on fluorine 18 fluorodeoxyglucose (FDG) distribution in organs and tissues of interest. Materials and Methods Positron emission tomographic (PET)/computed tomographic (CT) scans at the Ann Arbor Veterans Affairs hospital from January to July 2015 were reviewed. A total of 107 scans (50 patients; mean age, 64.3 years ± 13.2 [standard deviation]) had metabolic tissue burden assessed by using total lesion glycolysis (TLG) obtained from autosegmentation of the tumor and/or cardiac tissue. Standardized uptake value (SUV) and subsequent normalized SUV uptake in target organs and tissues were compared with 436 FDG PET/CT scans previously reported in 229 patients as a function of TLG to describe the effect(s) that metabolic burden has on reference tissue (blood pool, liver, and brain) FDG uptake. Subsequent regression by using linear mixed-effects models was used. If the slope of the regression was significantly (P < .05) different than zero, then an effect from TLG was present. Results There was a negative inverse relationship (P < .0001) between FDG uptake within reference tissues (blood pool, liver, and brain) and TLG in comparison to the study population at similar blood glucose levels. This TLG effect was no longer statistically significant (P > .05) when FDG uptake was normalized to a reference tissue (eg, blood pool or liver). Conclusion Metabolic tissue burden can have a significant effect on SUV measurements for PET imaging. This effect can be mitigated by normalizing FDG uptake to a reference tissue. © RSNA, 2018.

Rapid intraoperative histology of unprocessed surgical specimens via fibre-laser-based stimulated Raman scattering microscopy.

Conventional methods for intraoperative histopathologic diagnosis are labour- and time-intensive, and may delay decision-making during brain-tumour surgery. Stimulated Raman scattering (SRS) microscopy, a label-free optical process, has been shown to rapidly detect brain-tumour infiltration in fresh, unprocessed human tissues. Here, we demonstrate the first application of SRS microscopy in the operating room by using a portable fibre-laser-based microscope and unprocessed specimens from 101 neurosurgical patients. We also introduce an image-processing method - stimulated Raman histology (SRH) - which leverages SRS images to create virtual haematoxylin-and-eosin-stained slides, revealing essential diagnostic features. In a simulation of intraoperative pathologic consultation in 30 patients, we found a remarkable concordance of SRH and conventional histology for predicting diagnosis (Cohen's kappa, κ > 0.89), with accuracy exceeding 92%. We also built and validated a multilayer perceptron based on quantified SRH image attributes that predicts brain-tumour subtype with 90% accuracy. Our findings provide insight into how SRH can now be used to improve the surgical care of brain tumour patients.

Pre-Surgical fMRI Data Analysis Using a Spatially Adaptive Conditionally Autoregressive Model.

Spatial smoothing is an essential step in the analysis of functional magnetic resonance imaging (fMRI) data. One standard smoothing method is to convolve the image data with a three-dimensional Gaussian kernel that applies a fixed amount of smoothing to the entire image. In pre-surgical brain image analysis where spatial accuracy is paramount, this method, however, is not reasonable as it can blur the boundaries between activated and deactivated regions of the brain. Moreover, while in a standard fMRI analysis strict false positive control is desired, for pre-surgical planning false negatives are of greater concern. To this end, we propose a novel spatially adaptive conditionally autoregressive model with variances in the full conditional of the means that are proportional to error variances, allowing the degree of smoothing to vary across the brain. Additionally, we present a new loss function that allows for the asymmetric treatment of false positives and false negatives. We compare our proposed model with two existing spatially adaptive conditionally autoregressive models. Simulation studies show that our model outperforms these other models; as a real model application, we apply the proposed model to the pre-surgical fMRI data of two patients to assess peri- and intra-tumoral brain activity.

18F-Choline PET/MRI: The Additional Value of PET for MRI-Guided Transrectal Prostate Biopsies.

UNLABELLED: We assessed the value of fusion (18)F-fluoromethylcholine ((18)F-choline) PET/MRI for image-guided (targeted) prostate biopsies to detect significant prostate cancer (Gleason ≥ 3 + 4) compared with standard (systematic 12-core) biopsies. METHODS: Within an ongoing prospective clinical trial, hybrid (18)F-choline PET/CT and multiparametric 3T MRI (mpMRI) of the pelvis were performed in 36 subjects with a rising prostate-specific antigen for known (n = 15) or suspected (n = 21) prostate cancer before a prostate biopsy procedure. PET and T2-weighted MR volumes of the prostate were spatially registered using commercially available software. Biopsy targets were selected on the basis of visual appearance on MRI and graded as low, intermediate, or high risk for significant disease. Volumes of interest were defined for MR-identified lesions. (18)F-choline uptake measures were obtained from the MR target and a mirrored background volume of interest. The biopsy procedure was performed after registration of real-time transrectal ultrasound with T2-weighted MR and included image-guided cores plus standard cores. Histologic results were determined from standard and targeted biopsy cores as well as prostatectomy specimens (n = 10). RESULTS: Fifteen subjects were ultimately identified with Gleason ≥ 3 + 4 prostate cancer, of which targeted biopsy identified significantly more (n = 12) than standard biopsies (n = 5; P = 0.002). A total of 52 lesions were identified by mpMRI (19 low, 18 intermediate, 15 high risk), and mpMRI-assigned risk was a strong predictor of final pathology (area under the curve = 0.81; P < 0.001). When the mean (18)F-choline target-to-background ratio was used, the addition of (18)F-choline to mpMRI significantly improved the prediction of Gleason ≥ 3 + 4 cancers over mpMRI alone (area under the curve = 0.92; P < 0.001). CONCLUSION: Fusion PET/MRI transrectal ultrasound image registration for targeted prostate biopsies is clinically feasible and accurate. The addition of (18)F-choline PET to mpMRI improves the identification of significant prostate cancer.

Development of a Multiparametric Voxel-Based Magnetic Resonance Imaging Biomarker for Early Cancer Therapeutic Response Assessment.

Quantitative magnetic resonance imaging (MRI)-based biomarkers, which capture physiological and functional tumor processes, were evaluated as imaging surrogates of early tumor response following chemoradiotherapy in glioma patients. A multiparametric extension of a voxel-based analysis, referred as the parametric response map (PRM), was applied to quantitative MRI maps to test the predictive potential of this metric for detecting response. Fifty-six subjects with newly diagnosed high-grade gliomas treated with radiation and concurrent temozolomide were enrolled in a single-site prospective institutional review board-approved MRI study. Apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) maps were acquired before therapy and 3 weeks after therapy was initiated. Multiparametric PRM (mPRM) was applied to both physiological MRI maps and evaluated as an imaging biomarker of patient survival. For comparison, single-biomarker PRMs were also evaluated in this study. The simultaneous analysis of ADC and rCBV by the mPRM approach was found to improve the predictive potential for patient survival over single PRM measures. With an array of quantitative imaging parameters being evaluated as biomarkers of therapeutic response, mPRM shows promise as a new methodology for consolidating physiologically distinct imaging parameters into a single interpretable and quantitative metric.

Detection of human brain tumor infiltration with quantitative stimulated Raman scattering microscopy.

Differentiating tumor from normal brain is a major barrier to achieving optimal outcome in brain tumor surgery. New imaging techniques for visualizing tumor margins during surgery are needed to improve surgical results. We recently demonstrated the ability of stimulated Raman scattering (SRS) microscopy, a nondestructive, label-free optical method, to reveal glioma infiltration in animal models. We show that SRS reveals human brain tumor infiltration in fresh, unprocessed surgical specimens from 22 neurosurgical patients. SRS detects tumor infiltration in near-perfect agreement with standard hematoxylin and eosin light microscopy (κ = 0.86). The unique chemical contrast specific to SRS microscopy enables tumor detection by revealing quantifiable alterations in tissue cellularity, axonal density, and protein/lipid ratio in tumor-infiltrated tissues. To ensure that SRS microscopic data can be easily used in brain tumor surgery, without the need for expert interpretation, we created a classifier based on cellularity, axonal density, and protein/lipid ratio in SRS images capable of detecting tumor infiltration with 97.5% sensitivity and 98.5% specificity. Quantitative SRS microscopy detects the spread of tumor cells, even in brain tissue surrounding a tumor that appears grossly normal. By accurately revealing tumor infiltration, quantitative SRS microscopy holds potential for improving the accuracy of brain tumor surgery.

Integrated multimodal imaging of dynamic bone-tumor alterations associated with metastatic prostate cancer.

Bone metastasis occurs for men with advanced prostate cancer which promotes osseous growth and destruction driven by alterations in osteoblast and osteoclast homeostasis. Patients can experience pain, spontaneous fractures and morbidity eroding overall quality of life. The complex and dynamic cellular interactions within the bone microenvironment limit current treatment options thus prostate to bone metastases remains incurable. This study uses voxel-based analysis of diffusion-weighted MRI and CT scans to simultaneously evaluate temporal changes in normal bone homeostasis along with prostate bone metatastsis to deliver an improved understanding of the spatiotemporal local microenvironment. Dynamic tumor-stromal interactions were assessed during treatment in mouse models along with a pilot prospective clinical trial with metastatic hormone sensitive and castration resistant prostate cancer patients with bone metastases. Longitudinal changes in tumor and bone imaging metrics during delivery of therapy were quantified. Studies revealed that voxel-based parametric response maps (PRM) of DW-MRI and CT scans could be used to quantify and spatially visualize dynamic changes during prostate tumor growth and in response to treatment thereby distinguishing patients with stable disease from those with progressive disease (p<0.05). These studies suggest that PRM imaging biomarkers are useful for detection of the impact of prostate tumor-stromal responses to therapies thus demonstrating the potential of multi-modal PRM image-based biomarkers as a novel means for assessing dynamic alterations associated with metastatic prostate cancer. These results establish an integrated and clinically translatable approach which can be readily implemented for improving the clinical management of patients with metastatic bone disease.

Multi-site clinical evaluation of DW-MRI as a treatment response metric for breast cancer patients undergoing neoadjuvant chemotherapy.

PURPOSE: To evaluate diffusion weighted MRI (DW-MR) as a response metric for assessment of neoadjuvant chemotherapy (NAC) in patients with primary breast cancer using prospective multi-center trials which provided MR scans along with clinical outcome information. MATERIALS AND METHODS: A total of 39 patients with locally advanced breast cancer accrued from three different prospective clinical trials underwent DW-MR examination prior to and at 3-7 days (Hull University), 8-11 days (University of Michigan) and 35 days (NeoCOMICE) post-treatment initiation. Thirteen patients, 12 of which participated in treatment response study, from UM underwent short interval (<1hr) MRI examinations, referred to as "test-retest" for examination of repeatability. To further evaluate stability in ADC measurements, a thermally controlled diffusion phantom was used to assess repeatability of diffusion measurements. MRI sequences included contrast-enhanced T1-weighted, when appropriate, and DW images acquired at b-values of 0 and 800 s/mm2. Histogram analysis and a voxel-based analytical technique, the Parametric Response Map (PRM), were used to derive diffusion response metrics for assessment of treatment response prediction. RESULTS: Mean tumor apparent diffusion coefficient (ADC) values generated from patient test-retest examinations were found to be very reproducible (|ΔADC|<0.1x10-3mm2/s). This data was used to calculate the 95% CI from the linear fit of tumor voxel ADC pairs of co-registered examinations (±0.45x10-3mm2/s) for PRM analysis of treatment response. Receiver operating characteristic analysis identified the PRM metric to be predictive of outcome at the 8-11 (AUC = 0.964, p = 0.01) and 35 day (AUC = 0.770, p = 0.05) time points (p<.05) while whole-tumor ADC changes where significant at the later 35 day time interval (AUC = 0.825, p = 0.02). CONCLUSION: This study demonstrates the feasibility of performing a prospective analysis of DW-MRI as a predictive biomarker of NAC in breast cancer patients. In addition, we provide experimental evidence supporting the use of sensitive analytical tools, such as PRM, for evaluating ADC measurements.