Demonstration of accuracy and clinical versatility of mutual information for automatic multimodality image fusion using affine and thin-plate spline warped geometric deformations

Automated marker-free longitudinal infrared breast image registration by GA-PSO

The automated marker-free longitudinal Infrared (IR) breast image registration overcomes several challenges like no anatomic fiducial markers on the body surface, blurry boundaries, heat pattern variation by environmental and physiological factors, nonrigid deformation, etc, has the ability of quantitative pixel-wise analysis with the heat energy and patterns change in a time course study. To achieve the goal, scale-invariant feature transform, Harris corner, and Hessian matrix were employed to generate the feature points as anatomic fiducial markers, and hybrid genetic algorithm and particle swarm optimization minimizing the matching errors was used to find the appropriate corresponding pairs between the 1st IR image and thenth IR image. Moreover, the mechanism of the IR spectrogram hardware system has a high level of reproducibility. The performance of the proposed longitudinal image registration system was evaluated by the simulated experiments and the clinical trial. In the simulated experiments, the mean difference of our system is 1.64 mm, which increases 57.58% accuracy than manual determination and makes a 17.4% improvement than the previous study. In the clinical trial, 80 patients were captured several times of IR breast images during chemotherapy. Most of them were well aligned in the spatiotemporal domain. In the few cases with evident heat pattern dissipation and spatial deviation, it still provided a reliable comparison of vascular variation. Therefore, the proposed system is accurate and robust, which could be considered as a reliable tool for longitudinal approaches to breast cancer diagnosis.

Predictive value of diffusion MRI-based parametric response mapping for prognosis and treatment response in glioblastoma

BACKGROUND

Early detection of treatment response is important for the management of patients with malignant brain tumors such as glioblastoma to assure good quality of life in relation to therapeutic efficacy.

AIM

To investigate whether parametric response mapping (PRM) with diffusion MRI may provide prognostic information at an early stage of standard therapy for glioblastoma.

MATERIALS AND METHODS

This prospective study included 31 patients newly diagnosed with glioblastoma WHO grade IV, planned for primary standard postoperative treatment with radiotherapy 60Gy/30 fractions with concomitant and adjuvant Temozolomide. MRI follow-up including diffusion and perfusion weighting was performed at 3 T at start of postoperative chemoradiotherapy, three weeks into treatment, and then regularly until twelve months postoperatively. Regional mean diffusivity (MD) changes were analyzed voxel-wise using the PRM method (MD-PRM). At eight and twelve months postoperatively, after completion of standard treatment, patients were classified using conventional MRI and clinical evaluation as either having stable disease (SD, including partial response) or progressive disease (PD). It was assessed whether MD-PRM differed between patients having SD versus PD and whether it predicted the risk of disease progression (progression-free survival, PFS) or death (overall survival, OS). A subgroup analysis was performed that compared MD-PRM between SD and PD in patients only undergoing diagnostic biopsy. MGMT-promotor methylation status (O6-methylguanine-DNA methyltransferase) was registered and analyzed with respect to PFS, OS and MD-PRM.

RESULTS

Of the 31 patients analyzed: 21 were operated by resection and ten by diagnostic biopsy. At eight months, 19 patients had SD and twelve had PD. At twelve months, ten patients had SD and 20 had PD, out of which ten were deceased within twelve months and one was deceased without known tumor progression. Median PFS was nine months, and median OS was 17 months. Eleven patients had methylated MGMT-promotor, 16 were MGMT unmethylated, and four had unknown MGMT-status. MD-PRM did not significantly predict patients having SD versus PD neither at eight nor at twelve months. Patients with an above median MD-PRM reduction had a slightly longer PFS (P = 0.015) in Kaplan-Maier analysis, as well as a non-significantly longer OS (P = 0.099). In the subgroup of patients only undergoing biopsy, total MD-PRM change at three weeks was generally higher for patients with SD than for patients with PD at eight months, although no tests were performed. MGMT status strongly predicted both PFS and OS but not MD-PRM change.

CONCLUSION

MD-PRM at three weeks was not demonstrated to be predictive of treatment response, disease progression, or survival. Preliminary results suggested a higher predictive value in non-resected patients, although this needs to be evaluated in future studies.

An approach of gene regulatory network construction using mixed entropy optimizing context-related likelihood mutual information

MOTIVATION

The question of how to construct gene regulatory networks has long been a focus of biological research. Mutual information can be used to measure nonlinear relationships, and it has been widely used in the construction of gene regulatory networks. However, this method cannot measure indirect regulatory relationships under the influence of multiple genes, which reduces the accuracy of inferring gene regulatory networks.

APPROACH

This work proposes a method for constructing gene regulatory networks based on mixed entropy optimizing context-related likelihood mutual information (MEOMI). First, two entropy estimators were combined to calculate the mutual information between genes. Then, distribution optimization was performed using a context-related likelihood algorithm to eliminate some indirect regulatory relationships and obtain the initial gene regulatory network. To obtain the complex interaction between genes and eliminate redundant edges in the network, the initial gene regulatory network was further optimized by calculating the conditional mutual inclusive information (CMI2) between gene pairs under the influence of multiple genes. The network was iteratively updated to reduce the impact of mutual information on the overestimation of the direct regulatory intensity.

RESULTS

The experimental results show that the MEOMI method performed better than several other kinds of gene network construction methods on DREAM challenge simulated datasets (DREAM3 and DREAM5), three real Escherichia coli datasets (E.coli SOS pathway network, E.coli SOS DNA repair network and E.coli community network) and two human datasets.

AVAILABILITY AND IMPLEMENTATION

Source code and dataset are available at https://github.com/Dalei-Dalei/MEOMI/ and http://122.205.95.139/MEOMI/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Research synthesis of information theory measures of uncertainty: Meta-analysis of entropy and mutual information of diagnostic tests

RATIONALE, AIMS, AND OBJECTIVES

Assessing the performance of diagnostic tests requires evaluation of the amount of diagnostic uncertainty a test reduces. Statistical measures, such as sensitivity and specificity, currently dominating the evidence-based medicine (EBM) and related fields, cannot explicitly measure this reduction in diagnostic uncertainty. Mutual information (MI), an information theory statistic, explicitly quantifies diagnostic uncertainty by measuring information gain before vs after diagnostic testing. In this paper, we propose the use of MI as a single measure to express diagnostic test performance and demonstrate how it can be used in the meta-analysis of diagnostic test studies.

METHODS

We use two case studies from the literature to demonstrate the applicability of MI meta-analysis in assessing diagnostic performance. Meta-analysis of studies evaluating (a) ultrasonography (US) to detect endometrial cancer and (b) magnetic resonance angiography to detect arterial stenosis.

RESULTS

The results of MI meta-analyses are comparable to those of traditional statistical measures' meta-analyses. However, the results of MI are easier to understand as it relates directly to the extent of uncertainty a diagnostic test can reduce. For example, the US test, diagnosing endometrial cancer, is 40% specific and 94% sensitive. The combination of these values is difficult to interpret and may lead to inappropriate assessment (eg, one could favour the test due to its high sensitivity, ignoring its low specificity). In terms of MI, however, a single metric shows that the test reduces diagnostic uncertainty by 10%, which many users may consider small under most circumstances.

CONCLUSIONS

We have demonstrated the suitability of MI in assessing the performance of diagnostic tests, which can facilitate easier interpretation of the true utility of diagnostic tests. Similarly, to the guidance for interpretation of effect size of treatment interventions, we also propose the guidelines for interpretation of the utility of diagnostic tests based on the magnitude of reduction in diagnostic uncertainty.

Dopaminergic Regulation of Reward System Connectivity Underpins Pain and Emotional Suffering in Migraine

Purpose

It has been suggested that reward system dysfunction may account for emotion and pain suffering in migraine. However, there is a lack of evidence whether the altered reward system connectivity is directly associated with clinical manifestations, including negative affect and ictal pain severity and, at the molecular level, the dopamine (DA) D2/D3 receptors (D2/3Rs) signaling implicated in encoding motivational and emotional cues.

Patients and Methods

We acquired resting-state functional MRI from interictal episodic migraine (EM) patients and age-matched healthy controls, as well as positron emission tomography (PET) with [¹¹C]raclopride, a selective radiotracer for DA D2/3Rs, from a subset of these participants. The nucleus accumbens (NAc) was seeded to measure functional connectivity (FC) and DA D2/3Rs availability based on its essential involvement in pain-related aversive/reward functions. Associations of the brain measures with positive/negative affect and ictal pain severity were also assessed.

Results

Compared with controls, the EM group showed weaker right NAc connectivity with areas implicated in pain and emotional regulation, such as the amygdala, rostral anterior cingulate cortex, hippocampus, and thalamus; but showed stronger left NAc connectivity with the dorsolateral prefrontal cortex and lingual gyrus. Moreover, among the altered NAc connectivities, only right NAc-amygdala connectivity was inversely correlated with DA D2/3Rs availability in migraine patients (diagnostic group-by-D2/3Rs interaction p < 0.007). At a clinical level, such weaker NAc-amygdala connectivity was associated with lower interictal positive affect and greater ictal pain severity over the head and facial extension area (pain area and intensity number summation, PAINS).

Conclusion

Together, our findings suggest that altered reward system connectivity, specifically between the NAc and amygdala, might be affected by endogenous DA D2/3Rs signaling, and such process might be a neural mechanism that underlies emotional and pain suffering in episodic migraineurs.

Efficacy of non-rigid registration technique for misregistration in 3D-CTA fusion imaging

PURPOSE

To assess whether fusion 3D-CTA images can be corrected using non-rigid registration (NRR) for gastroenterology imaging.

METHODS

This study included 55 patients before gastroenterology surgery who underwent preoperative 3D-CTA prior to gastroenterological surgery. We recorded the coordinate of measurement points on the arterial vessels (X, Y, and Z) in each portal phase, original image of the arterial phase, and arterial phase with NRR. The distance of misregistration between the two points was calculated with the coordinate of the original image with NRR and that of the portal phase as true value.

RESULTS

The distance of misregistration between the two points in the original arterial and portal phase images was significantly higher than that in the arterial phase image with NRR on all directions (p < 0.01).

CONCLUSIONS

This study showed that NRR may correct misregistration on fusion 3D-CTA imaging. Hence, it can visualize correctly the anatomy of the vessel.

SCreg: a registration-based platform to compare unicondylar knee arthroplasty SPECT/CT scans

Background

A combination of conventional computed tomography and single photon emitted computed tomography (SPECT/CT) provides simultaneous data on the intensity and location of osteoblastic activity. Currently, since SPECT/CT scans are not spatially aligned, scans following knee arthroplasty are compared by extracting average and maximal values of osteoblastic activity intensity from large subregions of the structure of interest, which leads to a loss of resolution, and hence, information. Therefore, this paper describes the SPECT/CT registration platform (SCreg) based on the principle of image registration to spatially align SPECT/CT scans following unicondylar knee arthroplasty (UKA) and allow full resolution intra-subject and inter-subject comparisons.

Methods

SPECT-CT scans of 20 patients were acquired before and 1 year after UKA. Firstly, scans were pre-processed to account for differences in voxel sizes and divided in volumes of interest. This was followed by optimization of registration parameters according to their volumetric agreement, and alignment using a combination of rigid, affine and non-rigid registration. Finally, radiotracer uptakes were normalized, and differences between pre-operative and post-operative activity were computed for each voxel. Wilcoxon signed rank sum test was performed to compare Dice similarity coefficients pre- and post-registration.

Results

Qualitative and quantitative validation of the platform assessing the correct alignment of SPECT/CT scans resulted in Dice similarity coefficient values over 80% and distances between predefined anatomical landmarks below the fixed threshold of (2;2;0) voxels. Locations of increased and decreased osteoblastic activity obtained during comparisons of osteoblastic activity before and after UKA were mainly consistent with literature.

Conclusions

Thus, a full resolution comparison performed on the platform could assist surgeons and engineers in optimizing surgical parameters in view of bone remodeling, thereby improving UKA survivorship.

µ-Opioid Activity in Chronic TMD Pain Is Associated with COMT Polymorphism

Clinicians have the dilemma of prescribing opioid or nonopioid analgesics to chronic pain patients; however, the impact of pain on our endogenous µ-opioid system and how our genetic profile (specifically catechol-O-methyltransferase [COMT] polymorphisms) impacts its activation are currently unknown. Twelve chronic temporomandibular disorder (TMD) patients and 12 healthy controls (HCs) were scanned using positron emission tomography (PET) with [11C]carfentanil, a selective radioligand for µ-opioid receptors (µORs). The first 45 min of each PET measured the µOR nondisplaceable binding potential (BPND) at resting state, and the last 45 min consisted of a 20-min masseteric pain challenge with an injection of 5% hypertonic saline. Participants were also genotyped for different COMT alleles. There were no group differences in µOR BPND at resting state (early phase). However, during the masseteric pain challenge (late phase), TMD patients exhibited significant reductions in µOR BPND (decreased [11C]carfentanil binding) in the contralateral parahippocampus (P = 0.002) compared to HCs. The µOR BPND was also significantly lower in TMD patients with longer pain chronicity (P < 0.001). When considering COMT genotype and chronic pain suffering, TMD patients with the COMT158Met substitution had higher pain sensitivity and longer pain chronicity with a 5-y threshold for µOR BPND changes to occur in the parahippocampus. Together, the TMD diagnosis, COMT158Met substitution, and pain chronicity explained 52% of µOR BPND variance in the parahippocampus (cumulative R2 = 52%, P < 0.003, and HC vs. TMD Cohen's effect size d = 1.33 SD). There is strong evidence of dysregulation of our main analgesic and limbic systems in chronic TMD pain. The data also support precision medicine by helping identify TMD patients who may be more susceptible to chronic pain sensitivity and opioid dysfunction based on their genetic profile.

Postmenopausal hormone treatment alters neural pathways but does not improve verbal cognitive function

OBJECTIVE

Cognitive outcomes in trials of postmenopausal hormone treatment have been inconsistent. Differing outcomes may be attributed to hormone formulation, treatment duration and timing, and differential cognitive domain effects. We previously demonstrated treatment benefits on visual cognitive function. In the present study, we describe the effects of hormone treatment on verbal outcomes in the same women, seeking to understand the effects of prior versus current hormone treatment on verbal function.

METHODS

This is a cross-sectional evaluation of 57 women (38 hormone users [25 prior long-term users and 13 current users] and 19 never-users). Hormone users took identical formulations of estrogen or estrogen + progestin (0.625 mg/d conjugated equine estrogens with or without medroxyprogesterone acetate) for at least 10 years, beginning within 2 years of menopause. Women were evaluated with tests of verbal function and functional magnetic resonance imaging (fMRI) of a verbal discrimination task.

RESULTS

All women scored similarly on assessments of verbal function (Hopkins Verbal Learning Test and a verbal discrimination task performed during the fMRI scanning session); however, women ever treated with hormones had more left inferior frontal (T = 3.72; P < 0.001) and right prefrontal cortex (T = 3.53; P < 0.001) activation during the verbal task. Hormone-treated women performed slightly worse on the verbal discrimination task (mean accuracy 81.72 ± 11.57 ever-treated, 85.30 ± 5.87 never-treated, P = 0.14), took longer to respond (mean reaction time 1.10 ± 0.17 s ever-treated, 1.02 ± 0.11 never-treated, P = 0.03), and remembered fewer previously viewed words (mean accuracy 62.21 ± 8.73 ever-treated, 65.45 ± 7.49 never-treated, P = 0.18). Increased posterior cingulate activity was associated with longer response times (R = 0.323, P = 0.015) and worse delayed verbal recall (R = -0.328, P = 0.048), suggesting that increased activation was associated with less efficient cognitive processing. We did not detect between group differences in activation in the left prefrontal cortex, superior frontal cortex, thalamus, or occipital/parietal junction.

CONCLUSIONS

Although current and past hormone treatment was associated with differences in neural pathways used during verbal discrimination, verbal function was not higher than never-users.

Impact of chronic migraine attacks and their severity on the endogenous μ-opioid neurotransmission in the limbic system

OBJECTIVE

To evaluate, in vivo, the impact of ongoing chronic migraine (CM) attacks on the endogenous μ-opioid neurotransmission.

BACKGROUND

CM is associated with cognitive-emotional dysfunction. CM is commonly associated with frequent acute medication use, including opioids.

METHODS

We scanned 15 migraine patients during the spontaneous headache attack (ictal phase): 7 individuals with CM and 8 with episodic migraine (EM), as well as 7 healthy controls (HC), using positron emission tomography (PET) with the selective μ-opioid receptor (μOR) radiotracer [11C]carfentanil. Migraineurs were scanned in two paradigms, one with thermal pain threshold challenge applied to the site of the headache, and one without thermal challenge. Multivariable analysis was performed between the μ-opioid receptor availability and the clinical data.

RESULTS

μOR availability, measured with [11C]carfentanil nondisplaceable binding potential (BPND), in the left thalamus (P-value = 0.005) and left caudate (P-value = 0.003) were decreased in CM patients with thermal pain threshold during the ictal phase relative to HC. Lower μOR BPND in the right parahippocampal region (P-value = 0.001) and right amygdala (P-value = 0.002) were seen in CM relative to EM patients. Lower μOR BPND values indicate either a decrease in μOR concentration or an increase in endogenous μ-opioid release in CM patients. In the right amygdala, 71% of the overall variance in μOR BPND levels was explained by the type of migraine (CM vs. EM: partial-R2 = 0.47, P-value<0.001, Cohen's effect size d = 2.6SD), the severity of the attack (pain area and intensity number summation [P.A.I.N.S.]: partial-R2 = 0.16, P-value = 0.031), and the thermal pain threshold (allodynia: partial-R2 = 0.08).

CONCLUSIONS

Increased endogenous μ-opioid receptor-mediated neurotransmission is seen in the limbic system of CM patients, especially in right amygdala, which is highly modulated by the attack frequency, pain severity, and sensitivity. This study demonstrates for the first time the negative impact of chronification and exacerbation of headache attacks on the endogenous μ-opioid mechanisms of migraine patients. ClinicalTrials.gov identifier: NCT03004313.

Radiomics signature on 3T dynamic contrast-enhanced magnetic resonance imaging for estrogen receptor-positive invasive breast cancers: Preliminary results for correlation with Oncotype DX recurrence scores

To evaluate the ability of a radiomics signature based on 3T dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) to distinguish between low and non-low Oncotype DX (OD) risk groups in estrogen receptor (ER)-positive invasive breast cancers.Between May 2011 and March 2016, 67 women with ER-positive invasive breast cancer who performed preoperative 3T MRI and OD assay were included. We divided the patients into low (OD recurrence score [RS] <18) and non-low risk (RS ≥18) groups. Extracted radiomics features included 8 morphological, 76 histogram-based, and 72 higher-order texture features. A radiomics signature (Rad-score) was generated using the least absolute shrinkage and selection operator (LASSO). Univariate and multivariate logistic regression analyses were performed to investigate the association between clinicopathologic factors, MRI findings, and the Rad-score with OD risk groups, and the areas under the receiver operating characteristic curves (AUC) were used to assess classification performance of the Rad-score.The Rad-score was constructed for each tumor by extracting 10 (6.3%) from 158 radiomics features. A higher Rad-score (odds ratio [OR], 65.209; P <.001), Ki-67 expression (OR, 17.462; P = .007), and high p53 (OR = 8.449; P = .077) were associated with non-low OD risk. The Rad-score classified low and non-low OD risk with an AUC of 0.759.The Rad-score showed the potential for discrimination between low and non-low OD risk groups in patients with ER-positive invasive breast cancers.

Image Stacks as Parametric Surfaces: Application to Image Registration

We introduce a framework in which a stack of images is considered to be a 2-D parametric surface embedded in a higher dimensional space. This is a simple yet powerful idea, known in the literature but not exploited to its fullest. We discuss the properties of image stacks as parametric surfaces, apply this framework to image registration by presenting the image stack surface relative area (ISSRA) registration measure. We show the power of ISSRA as an effective objective function for image registration. Essentially, it shows good performance across a variety of different categories of registration problems: pairwise, groupwise, affine, and non-rigid. Mutual information (MI)-a classical and effective approach for registration-is widely considered to be a good choice for multimodal and pairwise registration while being difficult to extend to the groupwise setting. We discuss the deficiency of MI in the groupwise case from a theoretical point of view, present its connection to ISSRA in the pairwise case, and then show the ready extensibility of ISSRA to the groupwise setting. Experiments and comparisons are performed on different categories of image registration to showcase ISSRA's wide range of applicability to registration problems in practice.

Accurate validation of ultrasound imaging of prostate cancer: a review of challenges in registration of imaging and histopathology

As the development of modalities for prostate cancer (PCa) imaging advances, the challenge of accurate registration between images and histopathologic ground truth becomes more pressing. Localization of PCa, rather than detection, requires a pixel-to-pixel validation of imaging based on histopathology after radical prostatectomy. Such a registration procedure is challenging for ultrasound modalities; not only the deformations of the prostate after resection have to be taken into account, but also the deformation due to the employed transrectal probe and the mismatch in orientation between imaging planes and pathology slices. In this work, we review the latest techniques to facilitate accurate validation of PCa localization in ultrasound imaging studies and extrapolate a general strategy for implementation of a registration procedure.

Combining multiparametric MRI with receptor information to optimize prediction of pathologic response to neoadjuvant therapy in breast cancer: preliminary results

Pathologic complete response following neoadjuvant therapy (NAT) is used as a short-term surrogate marker of eventual outcome in patients with breast cancer. Analyzing voxel-level heterogeneity in MRI-derived parametric maps, obtained before and after the first cycle of NAT ([Formula: see text]), in conjunction with receptor status, may improve the predictive accuracy of tumor response to NAT. Toward that end, we incorporated two MRI-derived parameters, the apparent diffusion coefficient and efflux rate constant, with receptor status in a logistic ridge-regression model. The area under the curve (AUC) and Brier score of the model computed via 10-fold cross validation were 0.94 (95% CI: 0.85, 0.99) and 0.11 (95% CI: 0.06, 0.16), respectively. These two statistics strongly support the hypothesis that our proposed model outperforms the other models that we investigated (namely, models without either receptor information or voxel-level information). The contribution of the receptor information was manifested by an 8% to 15% increase in AUC and a 14% to 21% decrease in Brier score. These data indicate that combining multiparametric MRI with hormone receptor status has a high likelihood of improved prediction of pathologic response to NAT in breast cancer.

A graphical approach to optimizing variable-kernel smoothing parameters for improved deformable registration of CT and cone beam CT images

A systematic method is presented for determining optimal parameters in variable-kernel deformable image registration of cone beam CT and CT images, in order to improve accuracy and convergence for potential use in online adaptive radiotherapy. Assessed conditions included the noise constant (symmetric force demons), the kernel reduction rate, the kernel reduction percentage, and the kernel adjustment criteria. Four such parameters were tested in conjunction with reductions of 5, 10, 15, 20, 30, and 40%. Noise constants ranged from 1.0 to 1.9 for pelvic images in ten prostate cancer patients. A total of 516 tests were performed and assessed using the structural similarity index. Registration accuracy was plotted as a function of iteration number and a least-squares regression line was calculated, which implied an average improvement of 0.0236% per iteration. This baseline was used to determine if a given set of parameters under- or over-performed. The most accurate parameters within this range were applied to contoured images. The mean Dice similarity coefficient was calculated for bladder, prostate, and rectum with mean values of 98.26%, 97.58%, and 96.73%, respectively; corresponding to improvements of 2.3%, 9.8%, and 1.2% over previously reported values for the same organ contours. This graphical approach to registration analysis could aid in determining optimal parameters for Demons-based algorithms. It also establishes expectation values for convergence rates and could serve as an indicator of non-physical warping, which often occurred in cases  >0.6% from the regression line.

Parametric response mapping of dynamic CT: enhanced prediction of survival in hepatocellular carcinoma patients treated with transarterial chemoembolization

PURPOSE

The aim of this study was to evaluate the prognostic significance of parametric response mapping (PRM) analysis for hepatocellular carcinoma (HCC) patients undergoing transarterial chemoembolization (TACE).

METHODS

We recruited 65 HCC patients who underwent TACE. These patients underwent longitudinal multiphasic CT before and after TACE. We applied PRM analysis to the baseline CT before TACE and first/second follow-up CTs. The results of PRM analyses were used to stratify patients into responders and non-responders. Overall survival was compared between the two groups. An independent survival analysis using conventional radiological assessments was performed, and the results were compared with PRM results. Univariate and multivariate analyses were performed to identify clinical factors affecting survival.

RESULTS

The PRM analyses demonstrated that the responding group had a median survival of 529 days, while the non-responding group had a median survival of 263 days [hazard ratio (HR) 12.9, p < 0.05 for differences in survival]. The manual analyses indicated median survivals of 491 and 329 days for the responding and non-responding groups, respectively (HR 2.7, p < 0.05). Tumor size, albumin level, and PRM values were found to be significantly related to overall survival after univariate and multivariate analyses.

CONCLUSIONS

The PRM analysis could be a better predictor of overall survival for patients with HCC undergoing TACE than conventional radiological assessments.

Application of off-the-shelf stereo-cameras for the 3D assessment of morphometric variations caused by rhinoplasty

The present paper shows how a non-invasive and low-cost photogrammetric stereo device allows the assessment of morphometric variations of the nose following rhinoplasty. Six female patients, aged between 24 and 37 years, underwent 3D stereo-photogrammetric scanning. Three-dimensional computerised models were generated, extracting also information related to the coordinates of facial landmarks, distances between landmarks, angles, in pre- and postoperative situation. Two kinds of analysis were carried out: (i) statistical correlation between size variations and (ii) morphometric analysis, including General Procrustes Analysis (GPA), Principal Components Analysis (PCA) and Warping. The study shows the usefulness of the stereo-photogrammetric facial digitisation for morphometric analysis of the human face. Three-dimensional computerised models are also an important tool for the assessment of the surgeon's performance in the event of dispute between doctor and patient. Moreover, confirmation of the PCA as an analytical tool for the identification of components characterising the morphometric structure of the nose is highlighted.

Imaging analysis of Parkinson's disease patients using SPECT and tractography

Parkinson's disease (PD) is a degenerative disorder that affects the central nervous system. PD-related alterations in structural and functional neuroimaging have not been fully explored. This study explored multi-modal PD neuroimaging and its application for predicting clinical scores on the Movement Disorder Society-sponsored Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Multi-modal imaging that combined 123I-Ioflupane single-photon emission computed tomography (SPECT) and diffusion tensor imaging (DTI) were adopted to incorporate complementary brain imaging information. SPECT and DTI images of normal controls (NC; n = 45) and PD patients (n = 45) were obtained from a database. The specific binding ratio (SBR) was calculated from SPECT. Tractography was performed using DTI. Group-wise differences between NC and PD patients were quantified using SBR of SPECT and structural connectivity of DTI for regions of interest (ROIs) related to PD. MDS-UPDRS scores were predicted using multi-modal imaging features in a partial least-squares regression framework. Three regions and four connections within the cortico-basal ganglia thalamocortical circuit were identified using SBR and DTI, respectively. Predicted MDS-UPDRS scores using identified regions and connections and actual MDS-UPDRS scores showed a meaningful correlation (r = 0.6854, p < 0.001). Our study provided insight on regions and connections that are instrumental in PD.

Prognostic and predictive values of diffusion and perfusion MRI in paediatric intracranial ependymomas in a large national study

OBJECTIVE

To assess the relative cerebral blood volume (rCBV) and apparent diffusion coefficient (ADC) derived, respectively, from perfusion and diffusion pre-operative MRI of intracranial ependymomas and their predictive and prognostic values.

METHODS

Pre-operative MRI and clinical data for intracranial ependymomas diagnosed between January 2000 and December 2013 were retrospectively retrieved from a web-based national database. MRI data included diffusion (62 patients) and perfusion (20 patients) MRI. Patient age, histopathological diagnosis, tumour location, ADC, relative ADC (rADC) and rCBV were considered as potential factors in a survival analysis. Survival rates were estimated using the Kaplan-Meier method. Univariate analyses were performed using the log-rank test to compare groups. We also performed a multivariate analysis, applying the Cox proportional hazards model.

RESULTS

ADC and rADC values within hypointense regions differed significantly between grades II and III (p = 0.01). The 75th percentile of ADC within hypointense regions and the 25th percentile of rCBV within non-enhancing lesions were prognostic of disease-free survival (p = 0.004, p = 0.05). A significant correlation was found between the 75th percentile of rCBV and the 25th percentile of rADC (p = 0.01) in enhancing regions of grade-III tumours.

CONCLUSION

Pre-operative rADC and rCBV could be used as prognostic factors for clinical outcome and to predict histological grade in paediatric ependymomas.

ADVANCES IN KNOWLEDGE

Prognostic value of diffusion and perfusion MRI in paediatric ependymoma was found and may play a role in the prognostic classification of patients in order to design more tailored treatment strategies.

Preoperative Three-Dimensional Diagnosis of Neurovascular Relationships at the Root Exit Zones During Microvascular Decompression for Hemifacial Spasm

OBJECTIVE

Hemifacial spasm occurs when a blood vessel compresses against an area near the root exit zone of the facial nerve. Developments in diagnostic neuroimaging have allowed three-dimensional (3D) observation of artery and nerve locations, an effective aid for treatment selection. However, an accurate interpretation of the 3D data remains challenging because imaging representations of complex small vessels are drowned out by noise. We used a noise elimination method to analyze artery and nerve locations and to determine their 3D relationship.

METHODS

Fifteen patients treated for hemifacial spasm were included. Images fused from 3 modalities of magnetic resonance imaging, 3D computed tomography, and angiography were used as source images. Using the images, models of the nerve and candidate vessels were created and shown in 3D to observe how the arteries were compressing the nerve and to identify the portions of the offending vessels that were closest to the nerve. These preoperative results were then compared with operative field observations during surgery. 3D models of the unaffected side were created and evaluated as controls.

RESULTS

We confirmed that these models were accurate reconstructions of the source images as the tubular nerve and artery cross-sections showed good alignment onto magnetic resonance imaging axial slice images. The preoperative diagnoses of the compression sites and offending arteries all matched intraoperative findings.

CONCLUSIONS

An accurate identification of the offending arteries and compression sites was possible, and this method is anticipated to offer effective means of preoperative simulation.

Identification of a candidate biomarker from perfusion MRI to anticipate glioblastoma progression after chemoradiation

OBJECTIVE

To identify relevant relative cerebral blood volume biomarkers from T2* dynamic-susceptibility contrast magnetic resonance imaging to anticipate glioblastoma progression after chemoradiation.

METHODS

Twenty-five patients from a prospective study with glioblastoma, primarily treated by chemoradiation, were included. According to the last follow-up MRI confirmed status, patients were divided into: relapse group (n = 13) and control group (n = 12). The time of last MR acquisition was t_end; MR acquisitions performed at t_end-2M, t_end-4M and t_end-6M (respectively 2, 4 and 6 months before t_end) were analyzed to extract relevant variations among eleven perfusion biomarkers (B). These variations were assessed through R(B), as the absolute value of the ratio between ∆B from t_end-4M to t_end-2M and ∆B from t_end-6M to t_end-4M. The optimal cut-off for R(B) was determined using receiver-operating-characteristic curve analysis.

RESULTS

The fraction of hypoperfused tumor volume (F_hP_g) was a relevant biomarker. A ratio R(F_hP_g) ≥ 0.61 would have been able to anticipate relapse at the next follow-up with a sensitivity/specificity/accuracy of 92.3 %/63.6 %/79.2 %. High R(F_hPg) (≥0.61) was associated with more relapse at t_end compared to low R(F_hPg) (75 % vs 12.5 %, p = 0.008).

CONCLUSION

Iterative analysis of F_hP_g from consecutive examinations could provide surrogate markers to predict progression at the next follow-up.

KEY POINTS

• Related rCBV biomarkers from DSC were assessed to anticipate GBM progression. • Biomarkers were assessed through their patterns of variation during the follow-up. • The fraction of hypoperfused tumour volume (F_hP _g ) seemed to be a relevant biomarker. • An innovative ratio R(F_hP _g ) could be an early surrogate marker of relapse. • A significant time gain could be achieved in the management of GBM patients.

Energy minimization in medical image analysis: Methodologies and applications

Energy minimization is of particular interest in medical image analysis. In the past two decades, a variety of optimization schemes have been developed. In this paper, we present a comprehensive survey of the state-of-the-art optimization approaches. These algorithms are mainly classified into two categories: continuous method and discrete method. The former includes Newton-Raphson method, gradient descent method, conjugate gradient method, proximal gradient method, coordinate descent method, and genetic algorithm-based method, while the latter covers graph cuts method, belief propagation method, tree-reweighted message passing method, linear programming method, maximum margin learning method, simulated annealing method, and iterated conditional modes method. We also discuss the minimal surface method, primal-dual method, and the multi-objective optimization method. In addition, we review several comparative studies that evaluate the performance of different minimization techniques in terms of accuracy, efficiency, or complexity. These optimization techniques are widely used in many medical applications, for example, image segmentation, registration, reconstruction, motion tracking, and compressed sensing. We thus give an overview on those applications as well.

Parametric response mapping of dynamic CT for predicting intrahepatic recurrence of hepatocellular carcinoma after conventional transcatheter arterial chemoembolization

OBJECTIVES

The aim of our study was to determine the diagnostic value of a novel image analysis method called parametric response mapping (PRM) for prediction of intrahepatic recurrence of hepatocellular carcinoma (HCC) treated with conventional transcatheter arterial chemoembolization (TACE).

METHODS

This retrospective study was approved by the IRB. We recruited 55 HCC patients who achieved complete remission (CR) after TACE and received longitudinal multiphasic liver computed tomography (CT). The patients fell into two groups: the recurrent tumour group (n = 29) and the non-recurrent tumour group (n = 26). We applied the PRM analysis to see if this technique could distinguish between the two groups. The results of the PRM analysis were incorporated into a prediction algorithm. We retrospectively removed data from the last time point and attempted to predict the response to therapy of the removed data.

RESULTS

The PRM analysis was able to distinguish between the non-recurrent and recurrent groups successfully. The prediction algorithm detected response to therapy with an area under the curve (AUC) of 0.76, while the manual approach had AUC 0.64.

CONCLUSIONS

Adopting PRM analysis can potentially distinguish between recurrent and non-recurrent HCCs and allow for prediction of response to therapy after TACE.

KEY POINTS

Parametric response mapping (PRM) could help assess patients with recurrent HCCs after TACE. Parametric response mapping could direct patients to individualized therapy. Longitudinal CT images were analyzed with advanced image analysis method.

Sparse/Low Rank Constrained Reconstruction for Dynamic PET Imaging

In dynamic Positron Emission Tomography (PET), an estimate of the radio activity concentration is obtained from a series of frames of sinogram data taken at ranging in duration from 10 seconds to minutes under some criteria. So far, all the well-known reconstruction algorithms require known data statistical properties. It limits the speed of data acquisition, besides, it is unable to afford the separated information about the structure and the variation of shape and rate of metabolism which play a major role in improving the visualization of contrast for some requirement of the diagnosing in application. This paper presents a novel low rank-based activity map reconstruction scheme from emission sinograms of dynamic PET, termed as SLCR representing Sparse/Low Rank Constrained Reconstruction for Dynamic PET Imaging. In this method, the stationary background is formulated as a low rank component while variations between successive frames are abstracted to the sparse. The resulting nuclear norm and l₁ norm related minimization problem can also be efficiently solved by many recently developed numerical methods. In this paper, the linearized alternating direction method is applied. The effectiveness of the proposed scheme is illustrated on three data sets.

Prognostic value of combined visualization of MR diffusion and perfusion maps in glioblastoma

We analyzed whether the combined visualization of decreased apparent diffusion coefficient (ADC) values and increased cerebral blood volume (CBV) in perfusion imaging can identify prognosis-related growth patterns in patients with newly diagnosed glioblastoma. Sixty-five consecutive patients were examined with diffusion and dynamic susceptibility-weighted contrast-enhanced perfusion weighted MRI. ADC and CBV maps were co-registered on the T1-w image and a region of interest (ROI) was manually delineated encompassing the enhancing lesion. Within this ROI pixels with ADC values <the 30th percentile (ADCmin), pixels with CBV values >the 70th percentile (CBVmax) and the intersection of pixels with ADCmin and CBVmax were automatically calculated and visualized. Initially, all tumors with a mean intersection greater than the upper quartile of the normally distributed mean intersection of all patients were subsumed to the first growth pattern termed big intersection (BI). Subsequently, the remaining tumors' growth patterns were categorized depending on the qualitative representation of ADCmin, CBVmax and their intersection. Log-rank test exposed a significantly longer overall survival of BI (n = 16) compared to non-BI group (n = 49) (p = 0.0057). Thirty-one, four and 14 patients of the non-BI group were classified as predominant ADC-, CBV- and mixed growth group, respectively. In a multivariate Cox regression model, the BI-, CBV- and mixed groups had significantly lower adjusted hazard ratios (p-value, α(Bonferroni) < 0.006) when compared to the reference group ADC: 0.29 (0.0027), 0.11 (0.038) and 0.33 (0.0059). Our study provides evidence that the combination of diffusion and perfusion imaging allows visualization of different glioblastoma growth patterns that are associated with prognosis. A possible biological hypothesis for this finding could be the interpretation of the ADCmin fraction as the invasion-front of tumor cells while the CBVmax fraction might represent the vascular rich tumor border that is "trailing behind" the invasion-front in the ADC group.

Distinct cognitive effects of estrogen and progesterone in menopausal women

The effects of postmenopausal hormone treatment on cognitive outcomes are inconsistent in the literature. Emerging evidence suggests that cognitive effects are influenced by specific hormone formulations, and that progesterone is more likely to be associated with positive outcomes than synthetic progestin. There are very few studies of unopposed progesterone in postmenopausal women, and none that use functional neuroimaging, a sensitive measure of neurobiological function. In this study of 29 recently postmenopausal women, we used functional MRI and neuropsychological measures to separately assess the effects of estrogen or progesterone treatment on visual and verbal cognitive function. Women were randomized to receive 90 days of either estradiol or progesterone counterbalanced with placebo. After each treatment arm, women were given a battery of verbal and visual cognitive function and working memory tests, and underwent functional MRI including verbal processing and visual working memory tasks. We found that both estradiol and progesterone were associated with changes in activation patterns during verbal processing. Compared to placebo, women receiving estradiol treatment had greater activation in the left prefrontal cortex, a region associated with verbal processing and encoding. Progesterone was associated with changes in regional brain activation patterns during a visual memory task, with greater activation in the left prefrontal cortex and right hippocampus compared to placebo. Both treatments were associated with a statistically non-significant increase in number of words remembered following the verbal task performed during the fMRI scanning session, while only progesterone was associated with improved neuropsychological measures of verbal working memory compared to placebo. These results point to potential cognitive benefits of both estrogen and progesterone.

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.

A Radiation-Induced Hippocampal Vascular Injury Surrogate Marker Predicts Late Neurocognitive Dysfunction

PURPOSE

We aimed to develop a hippocampal vascular injury surrogate marker for early prediction of late neurocognitive dysfunction in patients receiving brain radiation therapy (RT).

METHODS AND MATERIALS

Twenty-seven patients (17 males and 10 females, 31-80 years of age) were enrolled in an institutional review board-approved prospective longitudinal study. Patients received diagnoses of low-grade glioma or benign tumor and were treated by (3D) conformal or intensity-modulated RT with a median dose of 54 Gy (50.4-59.4 Gy in 1.8-Gy fractions). Six dynamic-contrast enhanced MRI scans were performed from pre-RT to 18-month post-RT, and quantified for vascular parameters related to blood-brain barrier permeability, K(trans), and the fraction of blood plasma volume, Vp. The temporal changes in the means of hippocampal transfer constant K(trans) and Vp after starting RT were modeled by integrating the dose effects with age, sex, hippocampal laterality, and presence of tumor or edema near a hippocampus. Finally, the early vascular dose response in hippocampi was correlated with neurocognitive dysfunction at 6 and 18 months post-RT.

RESULTS

The mean K(trans) Increased significantly from pre-RT to 1-month post-RT (P<.0004), which significantly depended on sex (P<.0007) and age (P<.00004), with the dose response more pronounced in older females. Also, the vascular dose response in the left hippocampus of females correlated significantly with changes in memory function at 6 (r=-0.95, P<.0006) and 18-months (r=-0.88, P<.02) post-RT.

CONCLUSIONS

The early hippocampal vascular dose response could be a predictor of late neurocognitive dysfunction. A personalized hippocampus sparing strategy may be considered in the future.

Endogenous Opioid Mechanisms Are Implicated in Obesity and Weight Loss in Humans

CONTEXT

Successful long-term weight loss is challenging. Brain endogenous opioid systems regulate associated processes; however, their role in the maintenance of weight loss has not been adequately explored in humans.

OBJECTIVE

In a preliminary study, the objective was to assess central μ-opioid receptor (MOR) system involvement in eating behaviors and their relationship to long-term maintenance of weight loss.

DESIGN

This was a case-control study with follow-up of the treatment group at 1 year after intervention.

SETTING

The study was conducted at a tertiary care university medical center.

PARTICIPANTS

Lean healthy (n = 7) and chronically obese (n = 7) men matched for age and ethnicity participated in the study.

INTERVENTIONS

MOR availability measures were acquired with positron emission tomography and [(11)C]carfentanil. Lean healthy men were scanned twice under both fasted and fed conditions. Obese men were placed on a very low-calorie diet to achieve 15% weight loss from baseline weight and underwent two positron emission tomography scans before and two after weight loss, incorporating both fasted and fed states.

MAIN OUTCOME MEASURES

Brain MOR availability and activation were measured by reductions in MOR availability (nondisplaceable binding potential) from the fed compared with the fasted-state scans.

RESULTS

Baseline MOR nondisplaceable binding potential was reduced in obese compared with the lean and partially recovered obese after weight loss in regions that regulate homeostatic, hedonic, and emotional responses to feeding. Reductions in negative affect and feeding-induced MOR system activation in the right temporal pole were highly correlated in leans but not in obese men. A trend for an association between MOR activation in the right temporal pole before weight loss and weight regain 1 year was found.

CONCLUSIONS

Although these preliminary studies have a small sample size, these results suggest that obesity and diet-induced weight loss impact central MOR binding and endogenous opioid system function. MOR system activation in response to an acute meal may be related to the risk of weight regain.

Evaluation of GMI and PMI diffeomorphic-based demons algorithms for aligning PET and CT Images

Fusion of anatomic information in computed tomography (CT) and functional information in F18‐FDG positron emission tomography (PET) is crucial for accurate differentiation of tumor from benign masses, designing radiotherapy treatment plan and staging of cancer. Although current PET and CT images can be acquired from combined F18‐FDG PET/CT scanner, the two acquisitions are scanned separately and take a long time, which may induce potential positional errors in global and local caused by respiratory motion or organ peristalsis. So registration (alignment) of whole‐body PET and CT images is a prerequisite for their meaningful fusion. The purpose of this study was to assess the performance of two multimodal registration algorithms for aligning PET and CT images. The proposed gradient of mutual information (GMI)‐based demons algorithm, which incorporated the GMI between two images as an external force to facilitate the alignment, was compared with the point‐wise mutual information (PMI) diffeomorphic‐based demons algorithm whose external force was modified by replacing the image intensity difference in diffeomorphic demons algorithm with the PMI to make it appropriate for multimodal image registration. Eight patients with esophageal cancer(s) were enrolled in this IRB‐approved study. Whole‐body PET and CT images were acquired from a combined F18‐FDG PET/CT scanner for each patient. The modified Hausdorff distance (dMH) was used to evaluate the registration accuracy of the two algorithms. Of all patients, the mean values and standard deviations (SDs) of dMH were 6.65 (± 1.90) voxels and 6.01 (± 1.90) after the GMI‐based demons and the PMI diffeomorphic‐based demons registration algorithms respectively. Preliminary results on oncological patients showed that the respiratory motion and organ peristalsis in PET/CT esophageal images could not be neglected, although a combined F18‐FDG PET/CT scanner was used for image acquisition. The PMI diffeomorphic‐based demons algorithm was more accurate than the GMI‐based demons algorithm in registering PET/CT esophageal images.

PACS numbers: 87.57.nj, 87.57. Q‐, 87.57.uk

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.

Dynamic interactions between plasma IL-1 family cytokines and central endogenous opioid neurotransmitter function in humans

Evidence in animal models suggests IL-1 family cytokines interact with central endogenous opioid neurotransmitter systems, inducing or perpetuating pathological states such as persistent pain syndromes, depression, substance use disorders, and their comorbidity. Understanding these interactions in humans is particularly relevant to understanding pathological states wherein this neurotransmitter system is implicated (ie, persistent pain, mood disorders, substance use disorders, etc). Here, we examined relationships between IL-1β, IL-1ra, and functional measures of the endogenous opioid system in 34 healthy volunteers, in the absence and presence of a standardized sustained muscular pain challenge, a psychophysical challenge with emotionally and physically stressful components. Mu-opioid receptor availability in vivo was examined with [(11)C]carfentanil positron emission tomography (PET) scanning. Sex and neuroticism impacted IL-1 family cytokines; higher baseline IL-1β and IL-1ra was identified in females with lower neuroticism. Higher baseline IL-1β was also associated with reduced μ-opioid receptor availability (amygdala) and greater pain sensitivity. The pain challenge increased IL-1β in females with high neuroticism. Strong associations between IL-1ra (an anti-nociceptive cytokine) and μ-opioid receptor activation (VP/NAcc) were identified during the pain challenge and the resulting analgesic effect of μ-opioid receptor activation was moderated by changes in IL-1β whereby volunteers with greater pain induced increase in IL-1β experienced less endogenous opioid analgesia. This study demonstrates the presence of relationships between inflammatory factors and a specific central neurotransmitter system and circuitry, of relevance to understanding interindividual variations in regulation of responses to pain and other physical and emotional stressors.

Deformable registration for quantifying longitudinal tumor changes during neoadjuvant chemotherapy

PURPOSE

To evaluate DRAMMS, an attribute-based deformable registration algorithm, compared to other intensity-based algorithms, for longitudinal breast MRI registration, and to show its applicability in quantifying tumor changes over the course of neoadjuvant chemotherapy.

METHODS

Breast magnetic resonance images from 14 women undergoing neoadjuvant chemotherapy were analyzed. The accuracy of DRAMMS versus five intensity-based deformable registration methods was evaluated based on 2,380 landmarks independently annotated by two experts, for the entire image volume, different image subregions, and patient subgroups. The registration method with the smallest landmark error was used to quantify tumor changes, by calculating the Jacobian determinant maps of the registration deformation.

RESULTS

DRAMMS had the smallest landmark errors (6.05 ± 4.86 mm), followed by the intensity-based methods CC-FFD (8.07 ± 3.86 mm), NMI-FFD (8.21 ± 3.81 mm), SSD-FFD (9.46 ± 4.55 mm), Demons (10.76 ± 6.01 mm), and Diffeomorphic Demons (10.82 ± 6.11 mm). Results show that registration accuracy also depends on tumor versus normal tissue regions and different patient subgroups.

CONCLUSIONS

The DRAMMS deformable registration method, driven by attribute-matching and mutual-saliency, can register longitudinal breast magnetic resonance images with a higher accuracy than several intensity-matching methods included in this article. As such, it could be valuable for more accurately quantifying heterogeneous tumor changes as a marker of response to treatment.

Parametric response mapping as an indicator of bronchiolitis obliterans syndrome after hematopoietic stem cell transplantation

The management of bronchiolitis obliterans syndrome (BOS) after hematopoietic cell transplantation presents many challenges, both diagnostically and therapeutically. We developed a computed tomography (CT) voxel-wise methodology termed parametric response mapping (PRM) that quantifies normal parenchyma, functional small airway disease (PRM(fSAD)), emphysema, and parenchymal disease as relative lung volumes. We now investigate the use of PRM as an imaging biomarker in the diagnosis of BOS. PRM was applied to CT data from 4 patient cohorts: acute infection (n = 11), BOS at onset (n = 34), BOS plus infection (n = 9), and age-matched, nontransplant control subjects (n = 23). Pulmonary function tests and bronchoalveolar lavage were used for group classification. Mean values for PRM(fSAD) were significantly greater in patients with BOS (38% ± 2%) when compared with those with infection alone (17% ± 4%, P < .0001) and age-matched control subjects (8.4% ± 1%, P < .0001). Patients with BOS had similar PRM(fSAD) profiles, whether a concurrent infection was present or not. An optimal cut-point for PRM(fSAD) of 28% of the total lung volume was identified, with values >28% highly indicative of BOS occurrence. PRM may provide a major advance in our ability to identify the small airway obstruction that characterizes BOS, even in the presence of concurrent infection.

Valence-specific effects of BDNF Val66Met polymorphism on dopaminergic stress and reward processing in humans

Brain-derived neurotrophic factor (BDNF) levels in dopaminergic (DA) cells within the ventral tegmental area (VTA)/nucleus accumbens (NAc) circuitry appear to be a candidate mechanism for the neuroadaptive changes that follow stress and reward responses in animal models. However, the role of the BDNF gene variants in responses to salient cues through DA neurotransmission in humans remains unexplored. Here, we studied the effect of the common functional BDNF Val(66)Met (rs6265) polymorphism on rewarding experiences in the striatum and DA-mediated responses to stress. Seventy-two healthy controls were genotyped for the BDNF Val(66)Met polymorphism and underwent the monetary incentive delay task during an functional magnetic resonance imaging (fMRI) session. Forty-nine of them also underwent a sustained pain challenge with and without placebo administration with potential analgesic properties during PET measures of DA D2/3-receptor-mediated neurotransmission. Neuroimaging results revealed a significant effect of BDNF (Met(66) carriers > Val/Val) on brain responses during the anticipation of monetary losses, baseline D2/3 receptor availability, and pain-stress-induced DA release in the NAc. Conversely, BDNF Met(66) carriers showed no activation in response to monetary gains and a blunted DA response to the analgesic placebo in the NAc. These results provide initial human evidence regarding the effect of the BDNF Val(66)Met polymorphism on DA-mediated responses to stress, its cognitive regulation by positive expectations, and the anticipatory responses to monetary gains and losses in the VTA-NAc pathway. Our results are of relevance to the neurobiology of stress and reward interactions and the pathophysiology of stress-related disorders.

Parametric response mapping of dynamic CT as an imaging biomarker to distinguish viability of hepatocellular carcinoma treated with transcatheter arterial chemoembolization

PURPOSE

Accurate assessment of viability of hepatocellular carcinoma (HCC) after transcatheter arterial chemoembolization (TACE) is important for therapy planning. The purpose of this study is to determine the diagnostic value of a novel image analysis method called parametric response mapping (PRM) in predicting viability of tumor in HCC treated with TACE for dynamic CT images.

METHODS

35 patients who had 35 iodized-oil defect areas (IODAs) in HCCs treated with TACE were included in our study. These patients were divided into two groups, one group with viable tumors (n = 22) and the other group with non-viable tumors (n = 13) in the IODA. All patients were followed up using triple-phase dynamic CT after the treatment. We compared (a) manual analysis, (b) using PRM results, and (c) using PRM results with automatic classifier to distinguish between two tumor groups based on dynamic CT images from two longitudinal exams. Two radiologists performed the manual analysis. The PRM approach was implemented using prototype software. We adopted an off-the-shelf k nearest neighbor (kNN) classifier and leave-one-out cross-validation for the third approach. The area under the curve (AUC) values were compared for three approaches.

RESULTS

Manual analysis yielded AUC of 0.74, using PRM results yielded AUC of 0.84, and using PRM results with an automatic classifier yielded AUC of 0.87.

CONCLUSIONS

We improved upon the standard manual analysis approach by adopting a novel image analysis method of PRM combined with an automatic classifier.

μ-Opioid activation in the midbrain during migraine allodynia - brief report II

We investigated in vivo the allodynic response of the central μ-opioid system during spontaneous migraine headaches, following a sustained pain threshold challenge on the trigeminal ophthalmic region. Six migraineurs were scanned during the ictal and interictal phases using positron emission tomography (PET) with the selective μ-opioid receptor (μOR) radiotracer [11C]carfentanil. Females were scanned during the mid-late follicular phase of two separate cycles. Patients showed ictal trigeminal allodynia during the thermal challenge that was concurrent and positively correlated with μOR activation in the midbrain, extending from red nucleus to ventrolateral periaqueductal gray matter. These findings demonstrate for the first time in vivo the high μOR activation in the migraineurs' brains in response to their allodynic experience.

Association of μ-Opioid Activation in the Prefrontal Cortex with Spontaneous Migraine Attacks - Brief Report I

We evaluated in vivo the μ-opioid system during spontaneous episodic migraine headaches. Seven patients were scanned at different phases of their migraine using positron emission tomography with the selective μ-opioid receptor (μOR) radiotracer [11C]carfentanil. In the ictal phase, there was μOR activation in the medial prefrontal cortex, which was strongly associated with the μOR availability level during the interictal phase. Furthermore, μ-opioid binding changes showed moderate negative correlation with the combined extension and severity of the attacks. These results indicate for the first time that there is high μOR activation in the migraineurs' brains during headache attacks in response to their pain.