Impact of physiological noise correction on detecting blood oxygenation level-dependent contrast in the breast.

Physiological fluctuations are expected to be a dominant source of noise in blood oxygenation level-dependent (BOLD) magnetic resonance imaging (MRI) experiments to assess tumour oxygenation and angiogenesis. This work investigates the impact of various physiological noise regressors: retrospective image correction (RETROICOR), heart rate (HR) and respiratory volume per unit time (RVT), on signal variance and the detection of BOLD contrast in the breast in response to a modulated respiratory stimulus. BOLD MRI was performed at 3 T in ten volunteers at rest and during cycles of oxygen and carbogen gas breathing. RETROICOR was optimized using F-tests to determine which cardiac and respiratory phase terms accounted for a significant amount of signal variance. A nested regression analysis was performed to assess the effect of RETROICOR, HR and RVT on the model fit residuals, temporal signal-to-noise ratio, and BOLD activation parameters. The optimized RETROICOR model accounted for the largest amount of signal variance ([Formula: see text]  =  3.3  ±  2.1%) and improved the detection of BOLD activation (P  =  0.002). Inclusion of HR and RVT regressors explained additional signal variance, but had a negative impact on activation parameter estimation (P  <  0.001). Fluctuations in HR and RVT appeared to be correlated with the stimulus and may contribute to apparent BOLD signal reactivity.This work was supported by the NIHR Cambridge Biomedical Research Centre, the Cambridge Experimental Cancer Medicine Centre and the CRUK-EPSRC Cancer Imaging Centre in Cambridge and Manchester (C197/A16465 and C8742/A18097)

Targeted Molecular Imaging in Adrenal Disease—An Emerging Role for Metomidate PET-CT

Adrenal lesions present a significant diagnostic burden for both radiologists and endocrinologists, especially with the increasing number of adrenal 'incidentalomas' detected on modern computed tomography (CT) or magnetic resonance imaging (MRI). A key objective is the reliable distinction of benign disease from either primary adrenal malignancy (e.g., adrenocortical carcinoma or malignant forms of pheochromocytoma/paraganglioma (PPGL)) or metastases (e.g., bronchial, renal). Benign lesions may still be associated with adverse sequelae through autonomous hormone hypersecretion (e.g., primary aldosteronism, Cushing's syndrome, phaeochromocytoma). Here, identifying a causative lesion, or lateralising the disease to a single adrenal gland, is key to effective management, as unilateral adrenalectomy may offer the potential for curing conditions that are typically associated with significant excess morbidity and mortality. This review considers the evolving role of positron emission tomography (PET) imaging in addressing the limitations of traditional cross-sectional imaging and adjunctive techniques, such as venous sampling, in the management of adrenal disorders. We review the development of targeted molecular imaging to the adrenocortical enzymes CYP11B1 and CYP11B2 with different radiolabeled metomidate compounds. Particular consideration is given to iodo-metomidate PET tracers for the diagnosis and management of adrenocortical carcinoma, and the increasingly recognized utility of $^{11}$C-metomidate PET-CT in primary aldosteronism.NIHR Cambridge Biomedical Research Centr

Brain hypoxia mapping in acute stroke: Back-to-back T2′ MR versus 18F-fluoromisonidazole PET in rodents

Background Mapping the hypoxic brain in acute ischemic stroke has considerable potential for both diagnosis and treatment monitoring. PET using (18)F-fluoro-misonidazole (FMISO) is the reference method; however, it lacks clinical accessibility and involves radiation exposure. MR-based T2' mapping may identify tissue hypoxia and holds clinical potential. However, its validation against FMISO imaging is lacking. Here we implemented back-to-back FMISO-PET and T2' MR in rodents subjected to acute middle cerebral artery occlusion. For direct clinical relevance, regions of interest delineating reduced T2' signal areas were manually drawn. Methods Wistar rats were subjected to filament middle cerebral artery occlusion, immediately followed by intravenous FMISO injection. Multi-echo T2 and T2* sequences were acquired twice during FMISO brain uptake, interleaved with diffusion-weighted imaging. Perfusion-weighted MR was also acquired whenever feasible. Immediately following MR, PET data reflecting the history of FMISO brain uptake during MR acquisition were acquired. T2' maps were generated voxel-wise from T2 and T2*. Two raters independently drew T2' lesion regions of interest. FMISO uptake and perfusion data were obtained within T2' consensus regions of interest, and their overlap with the automatically generated FMISO lesion and apparent diffusion coefficient lesion regions of interest was computed. Results As predicted, consensus T2' lesion regions of interest exhibited high FMISO uptake as well as substantial overlap with the FMISO lesion and significant hypoperfusion, but only small overlap with the apparent diffusion coefficient lesion. Overlap of the T2' lesion regions of interest between the two raters was ∼50%. Conclusions This study provides formal validation of T2' to map non-core hypoxic tissue in acute stroke. T2' lesion delineation reproducibility was suboptimal, reflecting unclear lesion borders.This study was funded by an EU Grant (EUSTROKE Health-F2-2008-2022131). DJW was funded by an MRC collaborative grant (G0600986), RM by the NIHR Cambridge Biomedical Research Centre, and UJK by a fellowship from the Deutsche Forschungsgemeinschaft (Je 598/1-1)

Assessment of early treatment response to neoadjuvant chemotherapy in breast cancer using non-mono-exponential diffusion models: a feasibility study comparing the baseline and mid-treatment MRI examinations.

OBJECTIVES: To assess the feasibility of the mono-exponential, bi-exponential and stretched-exponential models in evaluating response of breast tumours to neoadjuvant chemotherapy (NACT) at 3 T. METHODS: Thirty-six female patients (median age 53, range 32-75 years) with invasive breast cancer undergoing NACT were enrolled for diffusion-weighted MRI (DW-MRI) prior to the start of treatment. For assessment of early response, changes in parameters were evaluated on mid-treatment MRI in 22 patients. DW-MRI was performed using eight b values (0, 30, 60, 90, 120, 300, 600, 900 s/mm2). Apparent diffusion coefficient (ADC), tissue diffusion coefficient (D t), vascular fraction (ƒ), distributed diffusion coefficient (DDC) and alpha (α) parameters were derived. Then t tests compared the baseline and changes in parameters between response groups. Repeatability was assessed at inter- and intraobserver levels. RESULTS: All patients underwent baseline MRI whereas 22 lesions were available at mid-treatment. At pretreatment, mean diffusion coefficients demonstrated significant differences between groups (p < 0.05). At mid-treatment, percentage increase in ADC and DDC showed significant differences between responders (49 % and 43 %) and non-responders (21 % and 32 %) (p = 0.03, p = 0.04). Overall, stretched-exponential parameters showed excellent repeatability. CONCLUSION: DW-MRI is sensitive to baseline and early treatment changes in breast cancer using non-mono-exponential models, and the stretched-exponential model can potentially monitor such changes. KEY POINTS: • Baseline diffusion coefficients demonstrated significant differences between complete pathological responders and non-responders. • Increase in ADC and DDC at mid-treatment can discriminate responders and non-responders. • The ƒ fraction at mid-treatment decreased in responders whereas increased in non-responders. • The mono- and stretched-exponential models showed excellent inter- and intrarater repeatability. • Treatment effects can potentially be assessed by non-mono-exponential diffusion models.The study has received funding from the Addenbrookes Charitable Trust and the NIHR comprehensive Biomedical Research Centre (BRC) and the Experimental Cancer Medicine Centre (ECMC) awards to Cambridge University Hospitals NHS Foundation Trust in partnership with the University of Cambridge

Vascular Imaging With 18^{18}F-Fluorodeoxyglucose Positron Emission Tomography Is Influenced by Hypoxia

This study was funded by a programme grant (RG/10/007/28300) from the British Heart Foundation (BHF). Dr. Joshi was supported by a BHF Clinical Research Training Fellowship (FS/12/29/29463), a British Atherosclerosis Society Binks Trust Travel Award, and a Raymond and Beverly Sackler PhD Studentship. Dr. Manavaki is funded by the NIHR Cambridge Biomedical Research Centre. Dr. Rudd is partially supported by the NIHR Cambridge Biomedical Research Centre, the BHF, The Wellcome Trust, and the EPSRC Cambridge Centre for Mathematical Imaging in Healthcare

Pericoronary and periaortic adipose tissue density are associated with inflammatory disease activity in Takayasu arteritis and atherosclerosis.

AimsTo examine pericoronary adipose tissue (PCAT) and periaortic adipose tissue (PAAT) density on coronary computed tomography angiography for assessing arterial inflammation in Takayasu arteritis (TAK) and atherosclerosis.Methods and resultsPCAT and PAAT density was measured in coronary (n = 1016) and aortic (n = 108) segments from 108 subjects [TAK + coronary artery disease (CAD), n = 36; TAK, n = 18; atherosclerotic CAD, n = 32; matched controls, n = 22]. Median PCAT and PAAT densities varied between groups (mPCAT: P P = 0.0002). PCAT density was 7.01 ± standard error of the mean (SEM) 1.78 Hounsfield Unit (HU) higher in coronary segments from TAK + CAD patients than stable CAD patients (P = 0.0002), and 8.20 ± SEM 2.04 HU higher in TAK patients without CAD than controls (P = 0.0001). mPCAT density was correlated with Indian Takayasu Clinical Activity Score (r = 0.43, P = 0.001) and C-reactive protein (r = 0.41, P P = 0.002). mPCAT density above -74 HU had 100% sensitivity and 95% specificity for differentiating active TAK from controls [area under the curve = 0.99 (95% confidence interval 0.97-1)]. The association of PCAT density and coronary arterial inflammation measured by 68Ga-DOTATATE positron emission tomography (PET) equated to an increase of 2.44 ± SEM 0.77 HU in PCAT density for each unit increase in 68Ga-DOTATATE maximum tissue-to-blood ratio (P = 0.002). These findings remained in multivariable sensitivity analyses adjusted for potential confounders.ConclusionsPCAT and PAAT density are higher in TAK than atherosclerotic CAD or controls and are associated with clinical, biochemical, and PET markers of inflammation. Owing to excellent diagnostic accuracy, PCAT density could be useful as a clinical adjunct for assessing disease activity in TAK

Detection of Atherosclerotic Inflammation by 68^{68}Ga-DOTATATE PET Compared to [18^{18}F]FDG PET Imaging

$\textbf{Background}$ Inflammation drives atherosclerotic plaque rupture. Although inflammation can be measured using fluorine-18-labeled fluorodeoxyglucose positron emission tomography ([$^{18}$F]FDG PET), [$^{18}$F]FDG lacks cell specificity, and coronary imaging is unreliable because of myocardial spillover. $\textbf{Objectives}$ Objectives This study tested the efficacy of gallium-68-labeled DOTATATE ($^{68}$Ga-DOTATATE), a somatostatin receptor subtype-2 (SST2)-binding PET tracer, for imaging atherosclerotic inflammation. $\textbf{Methods}$ We confirmed $^{68}$Ga-DOTATATE binding in macrophages and excised carotid plaques. $^{68}$Ga-DOTATATE PET imaging was compared to [$^{18}$F]FDG PET imaging in 42 patients with atherosclerosis. $\textbf{Results}$ Target $\textit{SSTR2}$ gene expression occurred exclusively in “proinflammatory” M1 macrophages, specific $^{68}$Ga-DOTATATE ligand binding to SST$_{2}$ receptors occurred in CD68-positive macrophage-rich carotid plaque regions, and carotid $\textit{SSTR2}$ mRNA was highly correlated with in vivo $^{68}$Ga-DOTATATE PET signals (r = 0.89; 95% confidence interval [CI]: 0.28 to 0.99; p = 0.02). $^{68}$Ga-DOTATATE mean of maximum tissue-to-blood ratios (mTBR$_{max}$) correctly identified culprit versus nonculprit arteries in patients with acute coronary syndrome (median difference: 0.69; interquartile range [IQR]: 0.22 to 1.15; p = 0.008) and transient ischemic attack/stroke (median difference: 0.13; IQR: 0.07 to 0.32; p = 0.003). $^{68}$Ga-DOTATATE mTBR$_{max}$ predicted high-risk coronary computed tomography features (receiver operating characteristics area under the curve [ROC AUC]: 0.86; 95% CI: 0.80 to 0.92; p < 0.0001), and correlated with Framingham risk score (r = 0.53; 95% CI: 0.32 to 0.69; p <0.0001) and [$^{18}$F]FDG uptake (r = 0.73; 95% CI: 0.64 to 0.81; p < 0.0001). [$^{18}$F]FDG mTBR$_{max}$ differentiated culprit from nonculprit carotid lesions (median difference: 0.12; IQR: 0.0 to 0.23; p = 0.008) and high-risk from lower-risk coronary arteries (ROC AUC: 0.76; 95% CI: 0.62 to 0.91; p = 0.002); however, myocardial [$^{18}$F]FDG spillover rendered coronary [$^{18}$F]FDG scans uninterpretable in 27 patients (64%). Coronary $^{68}$Ga-DOTATATE PET scans were readable in all patients. $\textbf{Conclusions}$ We validated $^{68}$Ga-DOTATATE PET as a novel marker of atherosclerotic inflammation and confirmed that $^{68}$Ga-DOTATATE offers superior coronary imaging, excellent macrophage specificity, and better power to discriminate high-risk versus low-risk coronary lesions than [$^{18}$F]FDG. (Vascular Inflammation Imaging Using Somatostatin Receptor Positron Emission Tomography [VISION]; NCT02021188)This study was funded by the Wellcome Trust and supported by the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre and the Cambridge Clinical Trials Unit. Dr. Tarkin is supported by a Wellcome Trust research training fellowship (104492/Z/14/Z). Dr. Evans is supported by a Dunhill Medical Trust fellowship (RTF44/0114). Dr. Chowdhury is supported by Royal College of Surgeons of England and British Heart Foundation (BHF) fellowships (FS/16/29/31957). Drs. Manavaki and Warburton are supported by the NIHR Biomedical Research Centres. Drs. Yu and Frontini are supported by the BHF (RE/13/6/30180). Dr. Fryer is supported by Higher Education Funding Council for England (HEFCE). Dr. Groves is supported by the University College London Hospital NIHR Biomedical Research Centre; and has received grant support from GlaxoSmithKline. Dr. Ouwehand’s laboratory is funded by EU-FP7 project Blueprint (Health-F5-2011-282510), BHF (PG-0310-1002 and RG/09/12/28096), and National Health Service Blood and Transplant. Dr. Bennett is supported by NIHR and BHF. Dr. Davenport is supported by research grants from Wellcome Trust (107715/Z/15/Z), Medical Research Council (MC_PC_14116), and BHF (RE-13-6-3180). Dr. Rudd is supported by the NIHR, BHF, Wellcome Trust, and HEFCE

Imaging tumour hypoxia with positron emission tomography.

Hypoxia, a hallmark of most solid tumours, is a negative prognostic factor due to its association with an aggressive tumour phenotype and therapeutic resistance. Given its prominent role in oncology, accurate detection of hypoxia is important, as it impacts on prognosis and could influence treatment planning. A variety of approaches have been explored over the years for detecting and monitoring changes in hypoxia in tumours, including biological markers and noninvasive imaging techniques. Positron emission tomography (PET) is the preferred method for imaging tumour hypoxia due to its high specificity and sensitivity to probe physiological processes in vivo, as well as the ability to provide information about intracellular oxygenation levels. This review provides an overview of imaging hypoxia with PET, with an emphasis on the advantages and limitations of the currently available hypoxia radiotracers.Cancer Research UK (CRUK) funded the National Cancer Research Institute (NCRI) PET Research Working party to organise a meeting to discuss imaging cancer with hypoxia tracers and Positron Emission Tomography. IF was funded by CRUK and is also supported by the Chief Scientific Office. ALH is supported by CRUK and the Breast Cancer Research Foundation. RM is funded by NIHR Cambridge Biomedical Research Centre.This is the accepted manuscript. The final version is available from Nature Publishing at http://www.nature.com/bjc/journal/vaop/ncurrent/full/bjc2014610a.html