Limits...
Diffusion-weighted magnetic resonance imaging for tumour response assessment: why, when and how?

Afaq A, Andreou A, Koh DM - Cancer Imaging (2010)

Bottom Line: The technique is quick to perform without the need for administration of exogenous contrast medium, and enables the apparent diffusion coefficient (ADC) of tissues to be quantified.Studies have shown that ADC increases in response to a variety of treatments including chemotherapy, radiotherapy, minimally invasive therapies and novel therapeutics.In this article, we review the rationale of applying DWI for tumour assessment, the evidence for ADC measurements in relation to specific treatments and some of the practical considerations for using ADC to evaluate treatment response.

View Article: PubMed Central - PubMed

Affiliation: Royal Marsden Hospital, Downs Road, Sutton, UK.

ABSTRACT
Diffusion-weighted magnetic resonance imaging (DWI) is increasingly being used to assess tumour response to a variety of anticancer treatments. The technique is quick to perform without the need for administration of exogenous contrast medium, and enables the apparent diffusion coefficient (ADC) of tissues to be quantified. Studies have shown that ADC increases in response to a variety of treatments including chemotherapy, radiotherapy, minimally invasive therapies and novel therapeutics. In this article, we review the rationale of applying DWI for tumour assessment, the evidence for ADC measurements in relation to specific treatments and some of the practical considerations for using ADC to evaluate treatment response.

Show MeSH

Related in: MedlinePlus

Parametric response map. A 72-year-old man with metastatic prostate cancer. (a) Pre-treatment T1-weighted image of the pelvis showing extensive metastatic bone disease. A region of interest (in red) is drawn encompassing a metastasis in the left ilium. (b) Post-treatment T1-weighted image. Colours displayed within region of interest indicate voxels that show increase (red), decrease (blue) or no change (green) in ADC values relative to threshold determined by pre-treatment standard deviation of ADC values. (c) Scatter plot of ADC values on a voxel-by-voxel basis before and after treatment shows a large percentage of voxels showing increase in ADC values (in red) indicating treatment effects within tumour volume. (Maps generated using Oncotreat software, Siemens Medical system, Erlangen, Germany).
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC2967137&req=5

Figure 7: Parametric response map. A 72-year-old man with metastatic prostate cancer. (a) Pre-treatment T1-weighted image of the pelvis showing extensive metastatic bone disease. A region of interest (in red) is drawn encompassing a metastasis in the left ilium. (b) Post-treatment T1-weighted image. Colours displayed within region of interest indicate voxels that show increase (red), decrease (blue) or no change (green) in ADC values relative to threshold determined by pre-treatment standard deviation of ADC values. (c) Scatter plot of ADC values on a voxel-by-voxel basis before and after treatment shows a large percentage of voxels showing increase in ADC values (in red) indicating treatment effects within tumour volume. (Maps generated using Oncotreat software, Siemens Medical system, Erlangen, Germany).

Mentions: More recently, functional diffusion maps, also known as parametric response maps, have been applied to detect early and heterogeneous tumour response to anticancer treatment (Fig. 7). This method of analysis is based on assessing ADC change for each imaging voxel within an ROI, relative to a threshold determined by the distribution of the pre-treatment ADC values (e.g. the 95% confidence limit of ADC distribution)[47,48]. In this way, the percentage of voxels within an ROI that have significantly increased above or decreased below the threshold after therapy can be determined. Studies using parametric response maps have been reported in brain gliomas, bone metastases, breast and head and neck cancers. It has been shown that parametric response maps can detect a significant drug effect even though the mean ADC value of a tumour does not change. Furthermore, it has been shown in patients with cerebral glioblastoma that an early response by parametric response maps was associated with better disease survival[49]. However, data analysis by parametric response maps requires excellent image registration between studies, to allow the same image voxels to be compared across time. This can be extremely challenging in the body, where motion and variations in the scan plane orientation between studies can make precise image registration difficult. Furthermore, tumours may shrink or grow between imaging studies, further confounding accurate registration of the pre- and post-treatment datasets.Figure 7


Diffusion-weighted magnetic resonance imaging for tumour response assessment: why, when and how?

Afaq A, Andreou A, Koh DM - Cancer Imaging (2010)

Parametric response map. A 72-year-old man with metastatic prostate cancer. (a) Pre-treatment T1-weighted image of the pelvis showing extensive metastatic bone disease. A region of interest (in red) is drawn encompassing a metastasis in the left ilium. (b) Post-treatment T1-weighted image. Colours displayed within region of interest indicate voxels that show increase (red), decrease (blue) or no change (green) in ADC values relative to threshold determined by pre-treatment standard deviation of ADC values. (c) Scatter plot of ADC values on a voxel-by-voxel basis before and after treatment shows a large percentage of voxels showing increase in ADC values (in red) indicating treatment effects within tumour volume. (Maps generated using Oncotreat software, Siemens Medical system, Erlangen, Germany).
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2967137&req=5

Figure 7: Parametric response map. A 72-year-old man with metastatic prostate cancer. (a) Pre-treatment T1-weighted image of the pelvis showing extensive metastatic bone disease. A region of interest (in red) is drawn encompassing a metastasis in the left ilium. (b) Post-treatment T1-weighted image. Colours displayed within region of interest indicate voxels that show increase (red), decrease (blue) or no change (green) in ADC values relative to threshold determined by pre-treatment standard deviation of ADC values. (c) Scatter plot of ADC values on a voxel-by-voxel basis before and after treatment shows a large percentage of voxels showing increase in ADC values (in red) indicating treatment effects within tumour volume. (Maps generated using Oncotreat software, Siemens Medical system, Erlangen, Germany).
Mentions: More recently, functional diffusion maps, also known as parametric response maps, have been applied to detect early and heterogeneous tumour response to anticancer treatment (Fig. 7). This method of analysis is based on assessing ADC change for each imaging voxel within an ROI, relative to a threshold determined by the distribution of the pre-treatment ADC values (e.g. the 95% confidence limit of ADC distribution)[47,48]. In this way, the percentage of voxels within an ROI that have significantly increased above or decreased below the threshold after therapy can be determined. Studies using parametric response maps have been reported in brain gliomas, bone metastases, breast and head and neck cancers. It has been shown that parametric response maps can detect a significant drug effect even though the mean ADC value of a tumour does not change. Furthermore, it has been shown in patients with cerebral glioblastoma that an early response by parametric response maps was associated with better disease survival[49]. However, data analysis by parametric response maps requires excellent image registration between studies, to allow the same image voxels to be compared across time. This can be extremely challenging in the body, where motion and variations in the scan plane orientation between studies can make precise image registration difficult. Furthermore, tumours may shrink or grow between imaging studies, further confounding accurate registration of the pre- and post-treatment datasets.Figure 7

Bottom Line: The technique is quick to perform without the need for administration of exogenous contrast medium, and enables the apparent diffusion coefficient (ADC) of tissues to be quantified.Studies have shown that ADC increases in response to a variety of treatments including chemotherapy, radiotherapy, minimally invasive therapies and novel therapeutics.In this article, we review the rationale of applying DWI for tumour assessment, the evidence for ADC measurements in relation to specific treatments and some of the practical considerations for using ADC to evaluate treatment response.

View Article: PubMed Central - PubMed

Affiliation: Royal Marsden Hospital, Downs Road, Sutton, UK.

ABSTRACT
Diffusion-weighted magnetic resonance imaging (DWI) is increasingly being used to assess tumour response to a variety of anticancer treatments. The technique is quick to perform without the need for administration of exogenous contrast medium, and enables the apparent diffusion coefficient (ADC) of tissues to be quantified. Studies have shown that ADC increases in response to a variety of treatments including chemotherapy, radiotherapy, minimally invasive therapies and novel therapeutics. In this article, we review the rationale of applying DWI for tumour assessment, the evidence for ADC measurements in relation to specific treatments and some of the practical considerations for using ADC to evaluate treatment response.

Show MeSH
Related in: MedlinePlus