Therapy monitoring of skeletal metastases with whole-body diffusion MRI

Abstract

Current methods of assessing tumor response at skeletal sites with metastatic disease use a combination of imaging tests, serum and urine biochemical markers, and symptoms assessment. These methods do not always enable the positive assessment of therapeutic benefit to be made but instead provide an evaluation of progression, which then guides therapy decisions in the clinic. Functional imaging techniques such as whole-body diffusion magnetic resonance imaging (MRI) when combined with anatomic imaging and other emerging "wet" biomarkers can improve the classification of therapy response in patients with metastatic bone disease. A range of imaging findings can be seen in the clinic depending on the type of therapy and duration of treatment. Successful response to systemic therapy is usually depicted by reductions in signal intensity accompanied by apparent diffusion coefficient (ADC) increases. Rarer patterns of successful treatment include no changes in signal intensity accompanying increases in ADC values (T2 shine-through pattern) or reductions in signal intensity without ADC value changes. Progressive disease results in increases in extent/intensity of disease on high b-value images with variable ADC changes. Diffusion MRI therapy response criteria need to be developed and tested in prospective studies in order to address current, unmet clinical and pharmaceutical needs for reliable measures of tumor response in metastatic bone disease.

Fuzzy C-means clustering of magnetic resonance imaging on apparent diffusion coefficient maps for predicting nodal metastasis in head and neck cancer

“…Additional studies enrolling more cases from different centres are required for confirming our findings and optimizing the cluster number. Some studies 8,[10][11][12][13] Padhani et al 31 indicated that some studies have reported mean values from single or multiple ROIs placed on ADC maps, and these measures may be limited to detecting treatment-related changes in ADC values such as cystic or necrotic areas. They used the cumulative frequency ADC histogram to present the percentile of ADC values.…”

Measurement and Compensation of Respiration-Induced B0 Variations in Lumbar Spine Bone Marrow Fat Quantification

“…-t/T2* [2] where W and F are the amount of water and fat, ∆f is the chemical shift difference between water and fat, ψ is the B0 field inhomogeneity. Total 4 unknowns (W, F, ψ, and T2*) were estimated using the iterative water and fat decomposition algorithm (8), then fat fraction was calculated as follows:…”

“…Fat fraction of the bone marrow has been suggested as an important quantitative parameter in the assessment of treatment response and determination of the benignity in oncologic imaging (1,2) or in the investigation into the association between bone health and bone marrow adiposity (3)(4)(5). Therefore, accurate fat quantification is a prerequisite for the fat fraction to be established as a reliable imaging biomarker.…”

Imaging Bone Metastases in Breast Cancer: Staging and Response Assessment

“…The signal from diffusion-weighted MRI (DW-MRI) depends on the rate of diffusion of water molecules, whereby tumors-which are typically hypercellular-show restricted diffusion compared with normal tissues. This property can be quantified, with the apparent diffusion coefficient representing the rate of signal loss with increasing diffusion weighting (73,74). The apparent diffusion coefficient typically increases with successful therapy as a result of cytotoxicity, reduced cellularity, and loss of cell membrane integrity, allowing water molecules to be more freely diffusible.…”