Innovative Approaches of Multimodal Imaging of Cancer Characteristics in Nuclear Medicine

Dear Colleagues,

Multimodal imaging approaches, such as PET/CT and PET/MRI, are well-established, non-invasive methods of clinical cancer diagnosis. The use of other imaging techniques, such as ultrasound or optical imaging, in combination with PET or SPECT can pave the way to create quantitative maps of molecular, hemodynamic, biomechanical, electrophysiological, and structural parameters beyond current clinical standards. The combination of anatomical, functional, and molecular imaging contributes significantly to a better understanding of cancer biology—and to improved patient care—compared to using a technique alone, which is becoming increasingly evident as research advances.

The diversity of cancers themselves, as well as the inhomogeneous characteristics of metastases and intratumoral heterogeneity, pose critical challenges for their diagnosis and therapy. Multimodal imaging, with its combined strengths, can therefore offer significant benefits. However, further research and novel approaches, as well as their translation into clinical practice are still needed in order to fully exploit the added value of multimodal imaging in delivering more impactful diagnosis of malignancies.

This Special Issue focuses on the exploration of innovative multimodal imaging techniques, refined reconstruction methodologies, the representation of tumor heterogeneity, and combined functional image analyses in both clinical and preclinical contexts.

We welcome both original research articles and reviews. Research areas may include (but are not limited to) the following:

• Reconstruction of PET/SPECT images in combination with other imaging approaches;
• Improving Pharmacokinetic analyses by combined imaging techniques;
• Multimodal imaging analyses in metastatic and primary tumor lesions;
• Functional imaging as fMRI combined with PET/SPECT;
• Multimodal imaging probes;
• Preclinical and clinical evaluations;
• Tumor segmentation and maps;
• Multimodal voxel-wise analysis.

We look forward to receiving your contributions.

Dr. Daniel Gündel
Dr. Sophie Stotz
Guest Editors

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