Marco Borri

Changes in functional imaging parameters following induction chemotherapy have important implications for individualised patient-based treatment regimens for advanced head and neck cancer

BACKGROUND When induction chemotherapy (IC) is used prior to chemoradiotherapy (CRT) in head and neck cancer (HNC), functional imaging (FI) may inform adaptation of treatment plans with the aim of optimising outcomes. Understanding the impact of IC on FI parameters is, therefore, essential. PURPOSE To prospectively evaluate the feasibility of acquiring serial FI ((18)F-FDG-PET, diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI) and its role in defining individualised treatment regimens following IC in HNC. METHODS AND MATERIALS Ten patients with stage III and IV HNC underwent conventional (CT and MRI) and functional (DW, DCE-MRI and (18)F-FDG-PET/CT) imaging at baseline and following two cycles of IC prior to definitive CRT. RESULTS One patient withdrew due to claustrophobia. Seven out of nine patients had a complete metabolic response to IC on (18)F-FDG-PET imaging. DCE-MRI showed a significant fall in transfer constant (K(trans)) (0.209 vs 0.129 min(-1)P<0.01) and integrated area under gadolinium curve at 60s (IAUGC6O) (18.4 vs 11.9 mmol/min, P<0.01) and DW-MRI a rise in ADC (0.89 vs 1.06 × 10(-3) mm(2)/s, P<0.01) following IC. CONCLUSIONS Acquiring FI sequences is feasible in HNC. There are marked changes in FI parameters following IC which may guide adaptation of individualised treatment regimens.

Evaluation of diffusion models in breast cancer

PURPOSE The purpose of this study is to investigate whether the microvascular pseudodiffusion effects resulting with non-monoexponential behavior are present in breast cancer, taking into account tumor spatial heterogeneity. Additionally, methodological factors affecting the signal in low and high diffusion-sensitizing gradient ranges were explored in phantom studies. METHODS The effect of eddy currents and accuracy of b-value determination using a multiple b-value diffusion-weighted MR imaging sequence were investigated in test objects. Diffusion model selection and noise were then investigated in volunteers (n = 5) and breast tumor patients (n = 21) using the Bayesian information criterion. RESULTS 54.3% of lesion voxels were best fitted by a monoexponential, 26.2% by a stretched-exponential, and 19.5% by a biexponential intravoxel incoherent motion (IVIM) model. High correlation (0.92) was observed between diffusion coefficients calculated using mono- and stretched-exponential models and moderate (0.59) between monoexponential and IVIM (medians: 0.96/0.84/0.72 × 10(-3) mm(2)/s, respectively). Distortion due to eddy currents depended on the direction of the diffusion gradient and displacement varied between 1 and 6 mm for high b-value images. Shift in the apparent diffusion coefficient due to intrinsic field gradients was compensated for by averaging diffusion data obtained from opposite directions. CONCLUSIONS Pseudodiffusion and intravoxel heterogeneity effects were not observed in approximately half of breast cancer and normal tissue voxels. This result indicates that stretched and IVIM models should be utilized in regional analysis rather than global tumor assessment. Cross terms between diffusion-sensitization gradients and other imaging or susceptibility-related gradients are relevant in clinical protocols, supporting the use of geometric averaging of diffusion-weighted images acquired with diffusion-sensitization gradients in opposite directions.

Quantitative Contrast-Enhanced Magnetic Resonance Lymphangiography of the Upper Limbs in Breast Cancer Related Lymphedema: An Exploratory Study

Abstract Background: Contrast-Enhanced Magnetic Resonance Lymphangiography (CE-MRL) presents some limitations: (i) it does not quantify lymphatic functionality; and (ii) enhancement of vascular structures may confound image interpretation. Furthermore, although CE-MRL is well described in the published literature for the lower limbs, there is a paucity of data with regards to its use in the upper limbs. In this proof-of-principle study, we propose a new protocol to perform CE-MRL in the upper limbs of patients with breast cancer-related lymphedema (BCRL) which addresses these limitations. Methods and Results: CE-MRL was performed using a previously published (morphological) protocol and the proposed protocol (quantitative) on both the ipsilateral (abnormal) and contralateral (normal) arms of patients with BCRL. The quantitative protocol employs contrast agent (CA) intradermal injections at a lower concentration to prevent T2*-related signal decay. Both protocols provided high-resolution three-dimensional images of upper limb lymphatic vessels. CA uptake curves were utilized to distinguish between lymphatic vessels and vascular structures. The quantitative protocol minimized venous enhancement and avoided spurious delays in lymphatic enhancement due to short T2* values, enabling correct CA uptake characterization. The quantitative protocol was therefore employed to measure the lymphatic fluid velocity, which demonstrated functional differences between abnormal and normal arms. The velocity values were in agreement with previously reported lymphoscintigraphy and near infra-red lymphangiography measurements. Conclusions: This work demonstrated the feasibility of CE-MRL of the upper limbs in patients with BRCL, introducing an advanced imaging and analysis protocol suitable for anatomical and functional study of the lymphatic system.

Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data

Purpose To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment. Material and Methods The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters. Results The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters. Conclusion The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes.

Investigating the influence of flip angle and k-space sampling on dynamic contrast-enhanced MRI breast examinations.

Rationale and Objectives To retrospectively investigate the effect of flip angle (FA) and k-space sampling on the performance of dynamic contrast-enhanced (DCE-) magnetic resonance imaging (MRI) breast sequences. Materials and Methods Five DCE-MRI breast sequences were evaluated (10°, 14°, and 18° FAs; radial or linear k-space sampling), with 7–10 patients in each group (n = 45). All sequences were compliant with current technical breast screening guidelines. Contrast agent (CA) uptake curves were constructed from the right mammary artery for each examination. Maximum relative enhancement, Emax, and time-to-peak enhancement, Tmax, were measured and compared between protocols (analysis of variance and Mann–Whitney). For each sequence, calculated values of maximum relative enhancement, Ecalc, were derived from the Bloch equations and compared to Emax. Fat suppression performance (residual bright fat and chemical shift artifact) was rated for each examination and compared between sequences (Fisher exact tests). Results Significant differences were identified between DCE-MRI sequences. Emax increased significantly at higher FAs and with linear k-space sampling (P < .0001; P = .001). Radial protocols exhibited greater Tmax than linear protocols at FAs of both 14° (P = .025) and 18° (P < .0001), suggesting artificially flattened uptake curves. Good correlation was observed between Ecalc and Emax (r = 0.86). Fat suppression failure was more pronounced at an FA of 18° (P = .008). Conclusions This retrospective approach is validated as a tool to compare and optimize breast DCE-MRI sequences. Alterations in FA and k-space sampling result in significant differences in CA uptake curve shape which could potentially affect diagnostic interpretation. These results emphasize the need for careful parameter selection and greater standardization of breast DCE-MRI sequences.

Magnetic Resonance Imaging-Based Assessment of Breast Cancer-Related Lymphoedema Tissue Composition.

Objectives The aim of this study was to propose a magnetic resonance imaging acquisition and analysis protocol that uses image segmentation to measure and depict fluid, fat, and muscle volumes in breast cancer–related lymphoedema (BCRL). This study also aims to compare affected and control (unaffected) arms of patients with diagnosed BCRL, providing an analysis of both the volume and the distribution of the different tissue components. Materials and Methods The entire arm was imaged with a fluid-sensitive STIR and a 2-point 3-dimensional T1W gradient-echo–based Dixon sequences, acquired in sagittal orientation and covering the same imaging volume. An automated image postprocessing procedure was developed to simultaneously (1) contour the external volume of the arm and the muscle fascia, allowing separation of the epifacial and subfascial volumes; and to (2) separate the voxels belonging to the muscle, fat, and fluid components. The total, subfascial, epifascial, muscle (subfascial), fluid (epifascial), and fat (epifascial) volumes were measured in 13 patients with unilateral BCRL. Affected versus unaffected volumes were compared using a 2-tailed paired t test; a value of P < 0.05 was considered to be significant. Pearson correlation was used to investigate the linear relationship between fat and fluid excess volumes. The distribution of fluid, fat, and epifascial excess volumes (affected minus unaffected) along the arm was also evaluated using dedicated tissue composition maps. Results Total arm, epifascial, epifascial fluid, and epifascial fat volumes were significantly different (P < 0.0005), with greater volume in the affected arms. The increase in epifascial volume (globally, 94% of the excess volume) constituted the bulk of the lymphoedematous swelling, with fat comprising the main component. The total fat excess volume summed over all patients was 2.1 times that of fluid. Furthermore, fat and fluid excess volumes were linearly correlated (Pearson r = 0.75), with the fat excess volume being greater than the fluid in 11 subjects. Differences in muscle compartment volume between affected and unaffected arms were not statistically significant, and contributed only 6% to the total excess volume. Considering the distribution of the different tissue excess volumes, fluid accumulated prevalently around the elbow, with substantial involvement of the upper arm in only 3 cases. Fat excess volume was generally greater in the upper arm; however, the relative increase in epifascial volume, which considers the total swelling relative to the original size of the arm, was in 9 cases maximal within the forearm. Conclusions Our measurements indicate that excess of fat within the epifascial layer was the main contributor to the swelling, even when a substantial accumulation of fluid was present. The proposed approach could be used to monitor how the internal components of BCRL evolve after presentation, to stratify patients for treatment, and to objectively assess treatment response. This methodology provides quantitative metrics not currently available during the standard clinical assessment of BCRL and shows potential for implementation in clinical practice.

Quality assurance in MRI breast screening: comparing signal-to-noise ratio in dynamic contrast-enhanced imaging protocols

Abstract MRI has been extensively used in breast cancer staging, management and high risk screening. Detection sensitivity is paramount in breast screening, but variations of signal-to-noise ratio (SNR) as a function of position are often overlooked. We propose and demonstrate practical methods to assess spatial SNR variations in dynamic contrast-enhanced (DCE) breast examinations and apply those methods to different protocols and systems. Four different protocols in three different MRI systems (1.5 and 3.0 T) with receiver coils of different design were employed on oil-filled test objects with and without uniformity filters. Twenty 3D datasets were acquired with each protocol; each dataset was acquired in under 60 s, thus complying with current breast DCE guidelines. In addition to the standard SNR calculated on a pixel-by-pixel basis, we propose other regional indices considering the mean and standard deviation of the signal over a small sub-region centred on each pixel. These regional indices include effects of the spatial variation of coil sensitivity and other structured artefacts. The proposed regional SNR indices demonstrate spatial variations in SNR as well as the presence of artefacts and sensitivity variations, which are otherwise difficult to quantify and might be overlooked in a clinical setting. Spatial variations in SNR depend on protocol choice and hardware characteristics. The use of uniformity filters was shown to lead to a rise of SNR values, altering the noise distribution. Correlation between noise in adjacent pixels was associated with data truncation along the phase encoding direction. Methods to characterise spatial SNR variations using regional information were demonstrated, with implications for quality assurance in breast screening and multi-centre trials.

Time-resolved angiography with stochastic trajectories for dynamic contrast-enhanced MRI in head and neck cancer: Are pharmacokinetic parameters affected?

PURPOSE To investigate the effects of different time-resolved angiography with stochastic trajectories (TWIST) k-space undersampling schemes on calculated pharmacokinetic dynamic contrast-enhanced (DCE) vascular parameters. METHODS A digital perfusion phantom was employed to simulate effects of TWIST on characteristics of signal changes in DCE. Furthermore, DCE-MRI was acquired without undersampling in a group of patients with head and neck squamous cell carcinoma and used to simulate a range of TWIST schemes. Errors were calculated as differences between reference and TWIST-simulated DCE parameters. Parametrical error maps were used to display the averaged results from all tumors. RESULTS For a relatively wide range of undersampling schemes, errors in pharmacokinetic parameters due to TWIST were under 10% for the volume transfer constant, Ktrans, and total extracellular extravascular space volume, Ve. TWIST induced errors in the total blood plasma volume, Vp, were the largest observed, and these were inversely dependent on the area of the fully sampled k-space. The magnitudes of errors were not correlated with Ktrans, Vp and weakly correlated with Ve. CONCLUSIONS The authors demonstrated methods to validate and optimize k-space view-sharing techniques for pharmacokinetic DCE studies using a range of clinically relevant spatial and temporal patient derived data. The authors found a range of undersampling patterns for which the TWIST sequence can be reliably used in pharmacokinetic DCE-MRI. The parameter maps created in the study can help to make a decision between temporal and spatial resolution demands and the quality of enhancement curve characterization.

A novel approach to evaluate spatial resolution of MRI clinical images for optimization and standardization of breast screening protocols

PURPOSE Stringent quality assurance is required in MRI breast screening to ensure that different scanners and imaging protocols reach similar diagnostic performance. The authors propose a methodology, based on power spectrum analysis (PSA), to evaluate spatial resolution in clinical images. To demonstrate this approach, the authors have retrospectively compared two MRI sequences commonly employed in breast screening. METHODS In a novel approach to PSA, spatial frequency response curves (SFRCs) were extracted from the images. The SFRC characterizes spatial resolution describing the spatial frequency content of an image over a range of frequencies. Verification of the SFRCs was performed on MRI images of Eurospin agarose gel tubes acquired with different resolution settings. SFRCs of volunteer and patient images obtained with two clinical MRI sequences were then compared. The two sequences differed primarily in k-space coverage pattern, which was either radial (RAD) or linear (LIN). RESULTS The computed SFRCs were able to demonstrate the differences between RAD and LIN sequences in relatively small groups of subjects. The curves showed a similar pattern of decay in both volunteer and patient images, indicating that the spatial frequency response is mainly determined by the imaging protocol and not by intersubject anatomical differences. The LIN protocol produced images with increased sharpness; this was reflected in the corresponding SFRCs, which showed a higher content of spatial frequencies associated with image details. CONCLUSIONS The SFRC can provide an objective assessment of the presence of spatial details in the image and represent a useful quality assurance tool in the evaluation of different breast screening protocols. With a reference image, a comparative analysis of the SFRCs could ensure that equivalent image quality is achieved across different scanners and sites.

Pre-treatment functional MRI of breast cancer: T2* evaluation at 3 T and relationship to dynamic contrast-enhanced and diffusion-weighted imaging

PURPOSE Baseline T2* relaxation time has been proposed as an imaging biomarker in cancer, in addition to Dynamic Contrast-Enhanced (DCE) MRI and diffusion-weighted imaging (DWI) parameters. The purpose of the current work is to investigate sources of error in T2* measurements and the relationship between T2* and DCE and DWI functional parameters in breast cancer. METHODS Five female volunteers and thirty-two women with biopsy proven breast cancer were scanned at 3 T, with Research Ethics Committee approval. T2* values of the normal breast were acquired from high-resolution, low-resolution and fat-suppressed gradient-echo sequences in volunteers, and compared. In breast cancer patients, pre-treatment T2*, DCE MRI and DWI were performed at baseline. Pathologically complete responders at surgery and non-responders were identified and compared. Principal component analysis (PCA) and cluster analysis (CA) were performed. RESULTS There were no significant differences between T2* values from high-resolution, low-resolution and fat-suppressed datasets (p > 0.05). There were not significant differences between baseline functional parameters in responders and non-responders (p > 0.05). However, there were differences in the relationship between T2* and contrast-agent uptake in responders and non-responders. Voxels of similar characteristics were grouped in 5 clusters, and large intra-tumoural variations of all parameters were demonstrated. CONCLUSION Breast T2* measurements at 3 T are robust, but spatial resolution should be carefully considered. T2* of breast tumours at baseline is unrelated to DCE and DWI parameters and contribute towards describing functional heterogeneity of breast tumours.