Pilot study of combined <scp>FDG</scp>‐<scp>PET</scp> and dynamic contrast‐enhanced <scp>CT</scp> of locally advanced cervical carcinoma before and during concurrent chemoradiotherapy suggests association between changes in tumor blood volume and treatment response

Banks, Thomas; Eyben, Rie von; Hristov, Dimitre; Kidd, Elizabeth A.

doi:10.1002/cam4.1632

Cited by 12 publications

(7 citation statements)

References 27 publications

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“…Fractionated radiation 1.8 Gy × 27 in patients with cervical cancer, increased vascular permeability, and radiomic measures of tumor blood volume, which were associated with treatment response. 57 Based on the evidence that radiation enhances permeability, radiation has been used as a strategy to improve drug delivery. Single doses of radiation increase monoclonal antibody uptake in colorectal carcinoma, melanoma, and hepatoma, attributed primarily to increased vascular permeability.…”

Section: Radiation Dose and Ec Viability And Functionmentioning

confidence: 99%

Effects of radiation on tumor vasculature

Yamazaki

Young

2021

Molecular Carcinogenesis

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Radiation has been utilized as a direct cytotoxic tumorcidal modality, however, the effect of radiation on tumor vasculature influences response to anticancer therapies.Although numerous reports have demonstrated vascular changes in irradiated tumors, the findings and implications are extensive and at times contradictory depending on the radiation dose, timing, and models used. In this review, we focus on the radiation-mediated effects on tumor vasculature with respect to doses used, timing postradiation, vasculogenesis, adhesion molecule expression, permeability, and pericyte coverage, including the latest findings.

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Section: Radiation Dose and Ec Viability And Functionmentioning

confidence: 99%

Effects of radiation on tumor vasculature

Yamazaki

Young

2021

Molecular Carcinogenesis

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“…Interestingly, fractionated low dose radiotherapy, i.e., daily fractions of up to 2 Gy, appears to exert a positive effect on the tumor vasculature and tissue perfusion (9, 23, 24) in multiple tumor models (25–27) as well as in patients (28–33). For example, an increased tumor blood volume during treatment with chemoradiation (27 × 1.8 Gy) was observed in cervical cancer patients (34). Using dynamic contrast-enhanced MRI and contrast-enhanced ultrasonography, we recently also observed increased tumor perfusion following two weeks of fractionated irradiation in a xenograft mouse tumor model.…”

Section: Radiotherapy and The Tumor Vasculaturementioning

confidence: 99%

Combining Radiotherapy With Anti-angiogenic Therapy and Immunotherapy; A Therapeutic Triad for Cancer?

et al. 2019

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Radiotherapy has been used for the treatment of cancer for over a century. Throughout this period, the therapeutic benefit of radiotherapy has continuously progressed due to technical developments and increased insight in the biological mechanisms underlying the cellular responses to irradiation. In order to further improve radiotherapy efficacy, there is a mounting interest in combining radiotherapy with other forms of therapy such as anti-angiogenic therapy or immunotherapy. These strategies provide different opportunities and challenges, especially with regard to dose scheduling and timing. Addressing these issues requires insight in the interaction between the different treatment modalities. In the current review, we describe the basic principles of the effects of radiotherapy on tumor vascularization and tumor immunity and vice versa. We discuss the main strategies to combine these treatment modalities and the hurdles that have to be overcome in order to maximize therapeutic effectivity. Finally, we evaluate the outstanding questions and present future prospects of a therapeutic triad for cancer.

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“…In recent years, clinical computer-aided diagnosis and treatment methods for various common clinical diseases emerged one after another [17], and deep learning technology gradually replaced supervised learning as an effective computer-aided artificial intelligence medical image segmentation scheme relying on its strong model learning ability and highly automatic extraction of target feature information [18], which was widely used in medical image segmentation fields of brain tumors, lung cancer, liver cancer, breast cancer, and gastric cancer, such as ultrasound, CT, and MRI images [19,20]. In this study, an artificial intelligence 3D-CNN algorithm was designed for the lesion image characteristics of cervical cancer patients under multimodal MRI and applied to the multimodal MRI image diagnosis of clinical cervical cancer.…”

Section: Discussionmentioning

confidence: 99%

Multimodal MRI Analysis of Cervical Cancer on the Basis of Artificial Intelligence Algorithm

Wang¹,

Zhang

Wu³

et al. 2021

Contrast Media & Molecular Imaging

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The purpose of this study is to explore the application value of artificial intelligence algorithm in multimodal MRI image diagnosis of cervical cancer. Based on the traditional convolutional neural network (CNN), an artificial intelligence 3D-CNN algorithm is designed according to the characteristics of cervical cancer. 70 patients with cervical cancer were selected as the experimental group, and 10 healthy people were selected as the reference group. The 3D-CNN algorithm was applied to the diagnosis of clinical cervical cancer multimodal MRI images. The value of the algorithm was comprehensively evaluated by the image quality and diagnostic accuracy. The results showed that compared with the traditional CNN algorithm, the convergence rate of the loss curve of the artificial intelligence 3D-CNN algorithm was accelerated, and the segmentation accuracy of whole-area tumors (WT), core tumor areas (CT), and enhanced tumor areas (ET) was significantly improved. In addition, the clarity of the multimodal MRI image and the recognition performance of the lesion were significantly improved. Under the artificial intelligence 3D-CNN algorithm, the Dice values of WT, ET, and CT regions were 0.78, 0.71, and 0.64, respectively. The sensitivity values were 0.92, 0.91, and 0.88, respectively. The specificity values were 0.93, 0.92, and 0.9 l, respectively. The Hausdorff (Haus) distances were 0.93, 0.92, and 0.90, respectively. The data of various indicators were significantly better than those of the traditional CNN algorithm ( P < 0.05). In addition, the diagnostic accuracy of the artificial intelligence 3D-CNN algorithm was 93.11 ± 4.65%, which was also significantly higher than that of the traditional CNN algorithm (82.45 ± 7.54%) ( P < 0.05). In summary, the recognition and segmentation ability of multimodal MRI images based on artificial intelligence 3D-CNN algorithm for cervical cancer lesions were significantly improved, which can significantly enhance the clinical diagnosis rate of cervical cancer.

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Pilot study of combined FDG‐PET and dynamic contrast‐enhanced CT of locally advanced cervical carcinoma before and during concurrent chemoradiotherapy suggests association between changes in tumor blood volume and treatment response

Cited by 12 publications

References 27 publications

Effects of radiation on tumor vasculature

Effects of radiation on tumor vasculature

Combining Radiotherapy With Anti-angiogenic Therapy and Immunotherapy; A Therapeutic Triad for Cancer?

Multimodal MRI Analysis of Cervical Cancer on the Basis of Artificial Intelligence Algorithm

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