scholarly journals Medical Imaging Biomarker Discovery and Integration Towards AI-Based Personalized Radiotherapy

2022 ◽  
Vol 11 ◽  
Yaru Pang ◽  
Hui Wang ◽  
He Li

Intensity-modulated radiation therapy (IMRT) has been used for high-accurate physical dose distribution sculpture and employed to modulate different dose levels into Gross Tumor Volume (GTV), Clinical Target Volume (CTV) and Planning Target Volume (PTV). GTV, CTV and PTV can be prescribed at different dose levels, however, there is an emphasis that their dose distributions need to be uniform, despite the fact that most types of tumour are heterogeneous. With traditional radiomics and artificial intelligence (AI) techniques, we can identify biological target volume from functional images against conventional GTV derived from anatomical imaging. Functional imaging, such as multi parameter MRI and PET can be used to implement dose painting, which allows us to achieve dose escalation by increasing doses in certain areas that are therapy-resistant in the GTV and reducing doses in less aggressive areas. In this review, we firstly discuss several quantitative functional imaging techniques including PET-CT and multi-parameter MRI. Furthermore, theoretical and experimental comparisons for dose painting by contours (DPBC) and dose painting by numbers (DPBN), along with outcome analysis after dose painting are provided. The state-of-the-art AI-based biomarker diagnosis techniques is reviewed. Finally, we conclude major challenges and future directions in AI-based biomarkers to improve cancer diagnosis and radiotherapy treatment.

2021 ◽  
Vol 11 ◽  
Mei Li ◽  
Qin Zhang ◽  
Kaixuan Yang

Advances in radiation technology, such as intensity-modulated radiation therapy (IMRT), have largely enabled a biological dose escalation of the target volume (TV) and reduce the dose to adjacent tissues or organs at risk (OARs). However, the risk of radiation-induced injury increases as more radiation dose utilized during radiation therapy (RT), which predominantly limits further increases in TV dose distribution and reduces the local control rate. Thus, the accurate target delineation is crucial. Recently, technological improvements for precise target delineation have obtained more attention in the field of RT. The addition of functional imaging to RT can provide a more accurate anatomy of the tumor and normal tissues (such as location and size), along with biological information that aids to optimize the therapeutic index (TI) of RT. In this review, we discuss the application of some common MRI-based functional imaging techniques in clinical practice. In addition, we summarize the main challenges and prospects of these imaging technologies, expecting more inspiring developments and more productive research paths in the near future.

2005 ◽  
Vol 44 (S 01) ◽  
pp. S38-S40
Th. Herrmann

Summary:PET/CT imaging is most likely to be of use in radiation oncology with patients who have poorly defined target volume areas, e.g. brain tumours, bronchogenic carcinoma, and cases of miscellaneous geographical miss. Other tumours that call for dose escalated radiotherapy, such as head and neck tumours, bronchogenic carcinoma, and prostate carcinomas may further benefit from an accurate delineation of the metabolically active tumour volume and its differentiation from surrounding healthy tissue, or tumour atelectasis.

Cancers ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 1063
Antonella Castellano ◽  
Michele Bailo ◽  
Francesco Cicone ◽  
Luciano Carideo ◽  
Natale Quartuccio ◽  

The accuracy of target delineation in radiation treatment (RT) planning of cerebral gliomas is crucial to achieve high tumor control, while minimizing treatment-related toxicity. Conventional magnetic resonance imaging (MRI), including contrast-enhanced T1-weighted and fluid-attenuated inversion recovery (FLAIR) sequences, represents the current standard imaging modality for target volume delineation of gliomas. However, conventional sequences have limited capability to discriminate treatment-related changes from viable tumors, owing to the low specificity of increased blood-brain barrier permeability and peritumoral edema. Advanced physiology-based MRI techniques, such as MR spectroscopy, diffusion MRI and perfusion MRI, have been developed for the biological characterization of gliomas and may circumvent these limitations, providing additional metabolic, structural, and hemodynamic information for treatment planning and monitoring. Radionuclide imaging techniques, such as positron emission tomography (PET) with amino acid radiopharmaceuticals, are also increasingly used in the workup of primary brain tumors, and their integration in RT planning is being evaluated in specialized centers. This review focuses on the basic principles and clinical results of advanced MRI and PET imaging techniques that have promise as a complement to RT planning of gliomas.

Medicina ◽  
2020 ◽  
Vol 57 (1) ◽  
pp. 6
Camil Ciprian Mireştean ◽  
Anda Crişan ◽  
Călin Buzea ◽  
Roxana Irina Iancu ◽  
DragoşPetru Teodor Iancu

The combination of immune checkpoint inhibitors and definitive radiotherapy is investigated for the multimodal treatment of cisplatin non-eligible locally advanced head and neck cancers (HNC). In the case of recurrent and metastatic HNC, immunotherapy has shown benefit over the EXTREME protocol, being already considered the standard treatment. One of the biggest challenges of multimodal treatment is to establish the optimal therapy sequence so that the synergistic effect is maximal. Thus, superior results were obtained for the administration of anti-CTLA4 immunotherapy followed by hypofractionated radiotherapy, but the anti-PD-L1 therapy demonstrates the maximum potential of radio-sensitization of the tumor in case of concurrent administration. The synergistic effect of radiotherapy–immunotherapy (RT–IT) has been demonstrated in clinical practice, with an overall response rate of about 18% for HNC. Given the demonstrated potential of radiotherapy to activate the immune system through already known mechanisms, it is necessary to identify biomarkers that direct the “nonresponders” of immunotherapy towards a synergistic RT–IT stimulation strategy. Stimulation of the immune system by irradiation can convert “nonresponder” to “responder”. With the development of modern techniques, re-irradiation is becoming an increasingly common option for patients who have previously been treated with higher doses of radiation. In this context, radiotherapy in combination with immunotherapy, both in the advanced local stage and in recurrent/metastatic of HNC radiotherapy, could evolve from the “first level” of knowledge (i.e., ballistic precision, dose conformity and homogeneity) to “level two” of “biological dose painting” (in which the concept of tumor heterogeneity and radio-resistance supports the need for doses escalation based on biological criteria), and finally to the “third level“ ofthe new concept of “immunological dose painting”. The peculiarity of this concept is that the radiotherapy target volumes and tumoricidal dose can be completely reevaluated, taking into account the immune-modulatory effect of irradiation. In this case, the tumor target volume can include even the tumor microenvironment or a partial volume of the primary tumor or metastasis, not all the gross and microscopic disease. Tumoricidal biologically equivalent dose (BED) may be completely different from the currently estimated values, radiotherapy treating the tumor in this case indirectly by boosting the immune response. Thus, the clinical target volume (CTV) can be replaced with a new immunological-clinical target volume (ICTV) for patients who benefit from the RT–IT association (Image 1).

2021 ◽  
Vol 7 (8) ◽  
pp. 124
Kostas Marias

The role of medical image computing in oncology is growing stronger, not least due to the unprecedented advancement of computational AI techniques, providing a technological bridge between radiology and oncology, which could significantly accelerate the advancement of precision medicine throughout the cancer care continuum. Medical image processing has been an active field of research for more than three decades, focusing initially on traditional image analysis tasks such as registration segmentation, fusion, and contrast optimization. However, with the advancement of model-based medical image processing, the field of imaging biomarker discovery has focused on transforming functional imaging data into meaningful biomarkers that are able to provide insight into a tumor’s pathophysiology. More recently, the advancement of high-performance computing, in conjunction with the availability of large medical imaging datasets, has enabled the deployment of sophisticated machine learning techniques in the context of radiomics and deep learning modeling. This paper reviews and discusses the evolving role of image analysis and processing through the lens of the abovementioned developments, which hold promise for accelerating precision oncology, in the sense of improved diagnosis, prognosis, and treatment planning of cancer.

2010 ◽  
Vol 9 (2) ◽  
pp. 77-85 ◽  
Courtney Buckey ◽  
Gregory Swanson ◽  
Sotirios Stathakis ◽  
Nikos Papanikolaou

AbstractBackground and Purpose: Intensity-modulated radiation therapy (IMRT) is considered by many to be the standard of care in the delivery of external-beam radiotherapy treatments to the prostate. The purpose of this study is to assess the validity of the purported benefits of IMRT.Materials and Methods: Treatment plans were produced for 10 patients using both 3D conformal radiation therapy (3D-CRT) and IMRT, utilising the dose constraints recommended by the Radiation Therapy Oncology Group (RTOG) 0415 protocol. Three IMRT modalities used in this study were linear accelerator based IMRT, helical tomotherapy, and serial tomotherapy. The prescription to the target, 76 Gy, was the same for all plans.Results: In general the 3D-CRT plans satisfied the RTOG criteria for planning target volume (PTV) coverage, and met or bettered the dose criteria for the organs at risk. PTV coverage was more homogeneous for the IMRT plans than the 3D-CRT plans but not significantly improved.Conclusions: Technically, because the IMRT plans required greater effort for the optimisation, longer treatment times and higher monitor units, the use of IMRT for the fulfilment of the protocol’s dosimetric goals was not justified using these constraints.

Molecules ◽  
2021 ◽  
Vol 26 (6) ◽  
pp. 1614
Ken-ichiro Matsumoto ◽  
James B. Mitchell ◽  
Murali C. Krishna

Radiation therapy is one of the main modalities to treat cancer/tumor. The response to radiation therapy, however, can be influenced by physiological and/or pathological conditions in the target tissues, especially by the low partial oxygen pressure and altered redox status in cancer/tumor tissues. Visualizing such cancer/tumor patho-physiological microenvironment would be a useful not only for planning radiotherapy but also to detect cancer/tumor in an earlier stage. Tumor hypoxia could be sensed by positron emission tomography (PET), electron paramagnetic resonance (EPR) oxygen mapping, and in vivo dynamic nuclear polarization (DNP) MRI. Tissue oxygenation could be visualized on a real-time basis by blood oxygen level dependent (BOLD) and/or tissue oxygen level dependent (TOLD) MRI signal. EPR imaging (EPRI) and/or T1-weighted MRI techniques can visualize tissue redox status non-invasively based on paramagnetic and diamagnetic conversions of nitroxyl radical contrast agent. 13C-DNP MRI can visualize glycometabolism of tumor/cancer tissues. Accurate co-registration of those multimodal images could make mechanisms of drug and/or relation of resulted biological effects clear. A multimodal instrument, such as PET-MRI, may have another possibility to link multiple functions. Functional imaging techniques individually developed to date have been converged on the concept of theranostics.

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