Authors:

Anwar Padhani

Sandro Iannaccone

Abstract

Whole-Body Diffusion-weighted Magnetic Resonance Imaging (WB-DW-MRI) is an advanced, non-invasive imaging technique that uses the biophysical properties of water molecule movement within tissues to produce images, reflecting tissue cell density and tissue architecture. Emerging as a key tool in cancer patient care, WB-DWI offers clear advantages over traditional imaging methods by providing a comprehensive whole-body assessment without the use of ionizing radiation or contrast agents. It plays a key role in disease detection, lesion characterization, and especially in monitoring treatment response, with particular strength in assessing bone marrow diseases. Ongoing technological improvements, including better hardware and software, are helping its integration into routine clinical practice. At the same time, continued research seeks to refine its capabilities and establish roles in clinical and preventative care.

Introduction

Whole-Body Diffusion-weighted Magnetic Resonance Imaging (WB-DW-MRI) is increasingly recognized as a potent clinical tool for guiding the care of cancer patients (Padhani, Koh, & Collins, Whole-body diffusion-weighted MR imaging in cancer: current status and research directions, 2011). This technique provides functional information from the measurement of the movement of water molecules within biological tissues, a process influenced by factors such as charged cell membranes, intracellular organelles, and macromolecules. Cancerous tissues, typically characterized by disorganized high cellularity, impeded water movement, appear as high-signal-intensity regions on DW images, with water diffusivity quantified as the Apparent Diffusion Coefficient (ADC) (Padhani, Koh, & Collins, Whole-body diffusion-weighted MR imaging in cancer: current status and research directions, 2011) (Koh, et al., 2012) (Yoshida, et al., 2021) (Sjöholm, et al., 2023) (Montoro, et al., 2014). The ability of WB-DWI to map cellular density marked a significant observational breakthrough, providing quantitative figures that correlate directly with the number of cells seen under a microscope and even tumor grade by reflecting tissue organization.

WB-DWI represents a substantial evolution from conventional imaging techniques like computed tomography (CT) and bone scintigraphy. Unlike these modalities, WB-DWI does not involve ionizing radiation, making it particularly advantageous for young patients, pregnant women, or those requiring repeated surveillance (Padhani, Koh, & Collins, Whole-body diffusion-weighted MR imaging in cancer: current status and research directions, 2011) (Montoro, et al., 2014). Furthermore, it avoids the need for injected isotopes or contrast media (Yoshida, et al., 2021) (Summers, et al., 2021). The technology for WB-DWI has matured to a point where it is widely implemented on most modern MR imaging systems, offering reasonably short data-acquisition times for whole-body examinations (Summers, et al., 2021). While already a powerful tool for disease detection and characterization, its exceptional performance in assessing bone marrow for diagnosis and therapy evaluation addresses significant unmet clinical and pharmaceutical needs. The information derived from WB-DWI can be quantified and displayed as parametric maps, enabling the analysis of spatial heterogeneity in tissues and tumors before and during treatment. This comprehensive approach underscores WB-DWI’s emerging leading role in modern oncology.

History

Before the advent of WB-DWI, conventional imaging modalities such as X-rays, CT scans, and bone scintigraphy were the primary tools for oncological assessments of bone disease, but they presented considerable limitations. Plain films, for instance, could not detect lytic lesions in conditions like myeloma until at least 60% of the bone was destroyed. While CT offered cross-sectional views, it still required significant tissue destruction to visualize lesions and had limited soft tissue resolution for bone marrow pathologies that do not disrupt the mineralized matrix (Zhang, et al., 2018). Bone scintigraphy, relying on the interaction between tumor cells and the osteoblasts of the bone matrix, could yield false-negative results even in the presence of extensive cancer if this interaction did not occur, or false-positives for benign processes such as fractures, and its widespread use was challenged by global shortages of isotopes like 99mTc. Whole-body magnetic resonance imaging (WB-MRI) protocols using anatomic sequences with or without exogenous contrast medium (without DW-MRI) need to be tailored for specific tumor types (Schaefer & Schlemmer, 2006). These protocols are time-consuming to acquire, analyse, and report.

The transformation in imaging capabilities began with advancements in MRI scanner technology that allowed for greater cranial-caudal coverage, with multiple coils and table movements for patient repositioning. Concurrently, the deployment of diffusion-weighted imaging (DWI) to extracranial disease proved to be a pivotal breakthrough. Initially applied to brain imaging, particularly in the context of strokes, researchers soon realized the potential of DWI for extracranial applications. The key observation was that diffusion imaging could measure the density of cells by quantifying the movement of water molecules. In tightly packed or disorganized tissues like tumors, water movement is impeded, resulting in a high signal intensity on DW images. Thus, Apparent Diffusion Coefficient (ADC) maps were able to quantify water diffusivity, which inversely correlates with microscopic cellular density and tumor grade.

In 2004, Taro Takahara et al. introduced the concept of Whole-Body Diffusion-weighted Imaging with Background Body Signal Suppression (DWIBS). This technique utilized free breathing, short-tau inversion recovery (STIR) for fat suppression, and high-resolution 3D displays to obtain WB-DWI. Initially, patient table movements were done manually. This innovation, combined with significant improvements in MRI hardware, including modern 1.5-T and 3-T units with echo-planar and parallel imaging capabilities, higher-performance gradients, phased-array multichannel surface coils, and continuous moving table technology, slice-by-slice shimming techniques markedly improved image quality and anatomic coverage, making WB-DWI feasible for wider clinical investigations (Figure 1). The advent of dedicated workstation software also streamlined the viewing and interpretation of whole-body datasets. The driving force behind the accelerated adoption of WB-DWI was not only its technical promise but also compelling clinical needs, which drove the standardization of diffusion imaging approaches (Padhani, et al., 2009) and whole-body MRI applications (Padhani, et al., 2017) (Messiou, et al., 2019). For the most recent developments in WB-DWI, which include the drafting of guidelines for the technique's implementation in various tumor types, the validation of the prognostic role of the criteria, integration with other diagnostic modalities, and the implementation of deep learning and artificial intelligence, please refer to the Timeline section.

Figure 1: Left 2 panels: 2010. Maximum Intensity Projections (MIP; inverted grey scale) of Whole body b800 DWI in the anterior and lateral projections of a 78-year-old man with progressive multiple myeloma. For three stations, the imaging time was about 20 minutes, and so the examination was focused from the skull base to the lower pelvis. Note the slight imaging intensity variation between the stations. Right 2 panels: 2024. MIP of WB b900 DWI in the anterior and lateral projections of a 66-year-old man with a new diagnosis of multiple myeloma. For six imaging stations from the vertex to the distal thighs, the imaging time is 7 minutes using deep learning reconstruction methods. Note the increased body coverage, more even signal intensity between stations, uniform soft tissue signal, and increased image sharpness.

Applications

Whole-Body Diffusion-weighted Imaging (WB-DWI) provides unique functional insights into tissue properties, primarily by assessing the mobility of water molecules. This allows for an "at-a-glance" assessment of both normal tissues and the burden and distribution of disease. It is worth stressing that WB-DWI is just one, but still the key one, of several sequences deployed in the WB-MRI examinations. The way these other sequences are used depends on the application (Table 1). Modern imaging analysis uses displays of multiple functional imaging sequences, maximum intensity projection (MIP) displays, and image fusions (Figure 2) all correlated with morphological CT and PET/CT scans.

Table 1: Different sequences in the WB-MRI examination and their application. The list of sequences and imaging planes is not complete.

Figure 2: 52F. Invasive Lobular Cancer. ER+, PR+, HER2-. Axillary recurrence of disease 6 years post-mastectomy. Left figure: coronal T1-weighted fat fraction, STIR, and b900 MIP (inverted grey scale) images showing the extent of craniocaudal coverage. There is a larger volume of right axillary nodal and chest wall disease, as well as right arm lymphoedema. Pelvic nodal disease on the right and left hydronephrosis. Right figure. Left column: black bone (inverted scale), b900, and fused images with the corresponding ADC map. Right column: T2W, b900, fused and corresponding contrast-enhanced CT scan at the same level.

Detection and Staging

WB-DWI is a powerful tool for initial diagnosis and staging of cancer. It excels in situations where radiation exposure is a concern, such as in children and pregnant women, making it a preferred technique over CT. It also serves as a valuable alternative when contrast-enhanced CT is contraindicated due to conditions like renal failure, poor venous access, or contrast medium allergies. WB-DWI can detect areas of increased cellularity as high-signal-intensity regions, improving the performance of whole-body MR examinations. This is particularly useful for cancers characterized by small-sized neoplastic cells or low FDG uptake on PET scans, including multiple myeloma, neuroendocrine tumors, childhood tumors, melanoma, small cell cancers, prostate cancer, hepatomas, and certain types of low-grade lymphomas (Figure 1).

It is also highly effective at visualizing the dispersed or “finger-like” spread of cancer cells, such as in lobular carcinoma, which can be challenging to detect with other modalities. For prostate cancer, WB-DWI is a promising one-step staging test (with primary tumor staging), demonstrating higher sensitivity for bone metastases than bone scintigraphy and comparable performance to 18F-choline PET/CT. In suspected recurrent colorectal cancer, WB-DWI has shown added value over CT and PET/CT (Taylor, et al., 2019) particularly for diagnosing and staging peritoneal metastases, including small lesions or those from mucinous carcinomas, which may be less FDG-avid (Willemse, et al., 2024). In multiple myeloma (MM), WB-DWI is crucial for diagnosis, staging, and determining which patients with smouldering disease require treatment (myeloma-defining) (Park, et al., 2020). It provides detailed insights into bone marrow involvement patterns and guides bone biopsies in myeloma and other cancers for Next-Generation Genomic Sequencing (Donners, et al., 2022).

Lesion characterization

The strength of WB-DWI in characterization lies in combining the signal intensity of diffusion-weighted information with ADC values, which function as a biomarker of cellularity. High cellularity tissues, including tumors, appear bright on high b-value images, while areas of impeded diffusion appear darker on grayscale ADC maps. An inverse correlation exists between ADC and cell density in many malignant tumors. However, in bone marrow, ADC correlations with cellularity are often non-inverse. The phenomenon is related to the mixed fat-cell population within a fixed bone marrow space. The characterization of tissues is further enhanced by combining DW-MRI information with morphologic images, fat imaging made possible by Dixon images, and black bone sequences, all of which can be done in a time-efficient whole-body basis on modern scanners (Figure 2).

Treatment response assessment

WB-DWI is also a powerful tool for monitoring treatment effectiveness, as changes in cellularity and water content often precede changes visible on conventional imaging (Figure 3a). Combining DW-MRI information with fat and bone images allows the spatial mapping of tumor cell killing and host tissue responses, including inflammation, healing, and repair.

Figure 3: 68F. Metastatic breast cancer with bone, node, and liver disease. Reassessment after three cycles of cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors. Figure 03A (top): The morphological T1-weighted and STIR images are not clear regarding any therapy response, but there is a decrease in the bone marrow signal on the b900 MIP images. Figure 03B (bottom): The bottom row is before treatment, and the top row is after therapy for the dates indicated. The whole skeleton was segmented using thresholding, and a mask was applied to the ADC maps. Corresponding ADC histograms show a good response by an increase in mean ADC from a median of 881 to 1505 (µm^2/s).

Quantitative image analysis is a crucial feature, enabling the assessment of multiple or all lesions in the body as volumes of interest (Figure 3b). Tools like histograms can evaluate the spatial distribution of ADC values within tumors, capturing heterogeneity of responses. The functional diffusion map or ADC parametric response map technique can also measure spatial changes in ADC, enabling radiomic analyses. However, their use may be limited by physiological motion or tumor distortions. For bone marrow response, WB-DWI is effective in monitoring therapy evaluation because of the fixed nature of the skeleton. Successful chemotherapy for primary bone tumors such as osteosarcomas is linked to higher tumor ADCs after treatment. In multiple myeloma, an increase in ADC values during treatment correlates with a good response. While morphological MRI may reveal persistent viable lesions after treatment, combining it with diffusion-weighted imaging enhances diagnostic accuracy for objective response, aligning more closely with clinical benefit.

The Myeloma Response Assessment and Diagnosis System (MY-RADS) criteria, incorporating ADC measurements, predict progression-free and overall survival after autologous stem cell transplantation (Belotti, et al., 2021). In aggressive non-Hodgkin lymphoma (NHL), quantitative WB-DWI after just one cycle of immunochemotherapy is an independent prognostic factor of disease-free survival, with prognostic performance comparable to interim and end-of-treatment 18F-FDG PET/CT (De Paepe, et al., 2021). Early ADC increases have also been observed in liver metastases from colorectal and stomach cancers after chemotherapy. For patients undergoing radiation therapy, increases in tumor ADC often correlate with a better response, with early changes seen in various cancers within days or weeks of treatment. For prostate cancer, WB-DWI is a promising tool to monitor therapeutic response in bone and soft tissues, detecting molecular and cellular changes that precede volume changes. The METastasis Reporting and Data System for Prostate Cancer (MET-RADS-P) guidelines incorporate ADC and DWI signal changes and morphological appearances for assessing the biological state of tissues and treatment response of bone metastases using a response assessment category (RAC) system (Padhani, et al., 2017) (Messiou, et al., 2019). Furthermore, the total tumor diffusion volume and extent of low ADC values are identified as prognostic markers in metastatic castration-resistant prostate cancer (CRPC).

Cancer screening

WB-DWI is valuable for screening individuals at high genetic risk for cancer, such as those with Li-Fraumeni syndrome, where radiation avoidance is paramount. Regular screening with WB-MRI can lead to earlier interventions and improved outcomes for these patients. Recently, we have seen the increasing use of WB-MRI for opportunistic multicancer detection and to promote proactive health management and informed lifestyle choices. The ONCO-RADS classification system provides a standardized framework for acquiring, interpreting, and reporting WB-MRI findings in cancer screening and for opportunistic multicancer detection (Petralia, et al., 2021).

Limitations and perspectives

Despite significant technical advancements with quality improvements and the demonstration of clinical utility, WB-DWI still faces several challenges and offers substantial avenues for future development.

Current limitations

False positives and negatives

WB-DWI, if used alone, can produce false positives due to normal variations in tissue appearance, such as localized areas of hypercellular bone marrow regions that can mimic disease. The T2 shine-through effect, caused by long tissue T2 relaxation times rather than impeded diffusion, can also lead to misinterpretations, necessitating correlation with ADC maps. Conversely, false negatives can occur in specific scenarios, such as when tumor cells are scattered rather than forming discrete masses, when cancer is present in normal hypercellular tissues (such as microscopic disease in lymph nodes), or specific tumor types with high intrinsic ADC values (e.g., mucinous or cystic tumors).

Anatomic blind spots and artifacts

Certain anatomical regions are prone to signal intensity degradation due to incoherent tissue motion or artifacts, impairing lesion detection. These include the mediastinum, pulmonary hila, left hepatic lobe, skull base, and within bowel loops. Complex physiological motion in areas like the thorax and abdomen, and susceptibility artifacts from medical implants or orthopaedic prostheses, can also obscure lesions.

Reproducibility and measurement variables

Documented reproducibility of WB-DWI outside the brain is limited according to organs, and signifi-cant interobserver and intraobserver variability exists for ADC measurements, especially for small structures (Boss, et al., 2024). Significant differences in ADC values can also be observed between scanners, posing challenges for multicentre studies. This variability makes it difficult to define a uni-versally applicable threshold for “real” ADC change.

Clinical relevance of ADC changes

There is a need for clearer documentation on how ADC changes translate into patient benefits, such as improvements in symptoms or survival. The magnitude of early ADC increases in response to therapy can be small, sometimes overlapping between responders and non-responders, which may limit its utility for personalized medicine in some cases. This underlines the need to understand the complex relationships between tumor cell infiltration patterns, cell kill mechanisms, and host re-sponses in different tumor types, particularly with the timing of WB-MRI measurements. This further emphasizes the need for multiparametric assessments of tumor response going beyond ADC measures alone, as incorporated in the RAC systems of the MET-RADS and MY-RADS standards (Padhani, et al., 2017) (Messiou, et al., 2019).

Complexity of analysis

Sophisticated analyses such as image fusions, quantitative analyses like ADC histograms or func-tional diffusion maps, while offering detailed insights, can be complex, and their biological meaning is not always clear, which can hinder their routine clinical adoption. Radiologists and oncologists prefer simple measurements of viable tumor burden in prognostic and response assessment set-tings, and this is being evaluated as a simpler measure in response assessment settings.

Lymph node assessment

A significant limitation lies in differentiating benign from malignant lymph nodes, as normal lymph nodes are already highly cellular and can show high signal intensity, making it difficult to confidently categorize them when there is microscopic disease that does not cause enlargement or architectur-al distortion.

Perspectives for improvement

Standardizations and atlases

Comprehensive documentation of normal WB-DWI appearances across various anatomical regions, including the effects of age, sex, and fat-to-water ratio on bone marrow, is crucial. The development of whole-body diffusion MRI normal atlases is underway to provide population-based descriptions for region- and voxel-based analysis, enhancing precision and aiding in automated tumor segmenta-tion.

Understanding treatment effects on normal tissues

Further research is needed to understand how common and novel treatments, including hematopoi-etic growth factors, affect the signal intensity of normal bone marrow, as these effects can mimic disease.

Refined response criteria

Refinements of establishment response criteria (Padhani, et al., 2017) (Messiou, et al., 2019) includ-ing ADC cutoff values, multiparametric assessment categories like RAC for various tumor types and organs, will be essential for clinical deployment and drug development.

Technological advancements

Acquisition speed

The integration of Artificial Intelligence (AI) is significantly reducing WB-DWI acquisition times by more than 50% without compromising accuracy, allowing for faster scans and extended protocols, such as full head-to-feet coverage (Figure 1).

Image quality

Efforts are ongoing to improve fat suppression at 3T and slice-by-slice shimming to minimize image distortion across the body stations.

Post-processing and AI in analysis

AI is also being developed for the automatic segmentation of tumor volumes and the generation of histograms (ADC, tissue fat, bone mineral) to improve observer variability and analysis times. AI can also help identify regions of differential treatment response within the body, allowing for personal-ized or targeted therapies, such as localized radiotherapy for focal non-responding areas.

New contrast agents

The availability of contrast agents, such as ultrasmall superparamagnetic iron oxide particles, is an-ticipated to improve the sensitivity for detecting microscopic disease in bone marrow and to en-hance lymph node disease detection and characterization.

Integration with other modalities

The advent of hybrid PET/MR imaging systems is encouraging research into the added value of combining WB-DWI with PET information for comprehensive lesion detection, characterization, and therapy response assessment. Studies show that combining WB-DWI with minimal residual disease (MRD) assessment, such as flow cytometry, can significantly improve the prediction of patient out-comes.

Biases

It is important to remember that any technique that has a higher disease detection sensitivity can create dilemmas in treatment initiation and selection. These include stage and risk migration, and lead and length time bias.

Personalized medicine

Prospective clinical trials will be required to evaluate whether higher accuracy imaging can genuine-ly improve clinically relevant endpoints for patients through precise treatment adaptations.

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Other keyplayers: Berthold Kiefer