Radiomics analysis of ultrasonic image predicts sensitive effects of microwave ablation in treatment of patient with benign breast tumors

Li, Guanghui; An, Chao; Yu, Jie; Huang, Qinghua

doi:10.1016/j.bspc.2022.103722

Cited by 19 publications

(4 citation statements)

References 27 publications

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“…TuckER is a knowledge graph completion method based on embedding, proposed by Ivana et al in 2019 [27]. They reconsidered the concept of Tucker tensor decomposition [30] and developed the TuckER model to decompose knowledge embeddings into three parts of tensors: 𝜙 ℎ, 𝑟, 𝑡 = 𝑊 × 𝒉 × 𝒓 × 𝒕 (5) where 𝜙 ℎ, 𝑟, 𝑡 denotes a piece of knowledge indicating there is a relation 𝑟 from the head entity ℎ to the tail entity 𝑡. After being mapped to the tensor space, 𝒉, 𝒓, and 𝒕 represent ℎ, 𝑟, and 𝑡, respectively.…”

Section: Inference Based On Tuckermentioning

confidence: 99%

“…In contrast, US is low-cost, radiation-free, simple-to-operate, and has a higher diagnostic accuracy for breast ultrasound (BUS) imaging, so BUS is widely used in the screening and initial diagnosis of breast tumors in the early stages [4]. In addition, BUS imaging is also commonly used in postoperative follow-up to follow up on the results of breast tumor surgery [5]. Since BUS images are obtained as reconstructed images from ultrasound signals, radiologists need to interpret the image features based on their knowledge and experience in the field to obtain medical imaging reports of the lesion and give diagnostic opinions.…”

Section: Introductionmentioning

confidence: 99%

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Knowledge Tensor-Aided Breast Ultrasound Image Assistant Inference Framework

Xiao

Wang

et al. 2023

Healthcare

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Breast cancer is one of the most prevalent cancers in women nowadays, and medical intervention at an early stage of cancer can significantly improve the prognosis of patients. Breast ultrasound (BUS) is a widely used tool for the early screening of breast cancer in primary care hospitals but it relies heavily on the ability and experience of physicians. Accordingly, we propose a knowledge tensor-based Breast Imaging Reporting and Data System (BI-RADS)-score-assisted generalized inference model, which uses the BI-RADS score of senior physicians as the gold standard to construct a knowledge tensor model to infer the benignity and malignancy of breast tumors and axes the diagnostic results against those of junior physicians to provide an aid for breast ultrasound diagnosis. The experimental results showed that the diagnostic AUC of the knowledge tensor constructed using the BI-RADS characteristics labeled by senior radiologists achieved 0.983 (95% confidential interval (CI) = 0.975–0.992) for benign and malignant breast cancer, while the diagnostic performance of the knowledge tensor constructed using the BI-RADS characteristics labeled by junior radiologists was only 0.849 (95% CI = 0.823–0.876). With the knowledge tensor fusion, the AUC is improved to 0.887 (95% CI = 0.864–0.909). Therefore, our proposed knowledge tensor can effectively help reduce the misclassification of BI-RADS characteristics by senior radiologists and, thus, improve the diagnostic performance of breast-ultrasound-assisted diagnosis.

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Section: Inference Based On Tuckermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Knowledge Tensor-Aided Breast Ultrasound Image Assistant Inference Framework

Xiao

Wang

et al. 2023

Healthcare

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“…Microwave ablation (MWA), known for its broad ablation range, wide indications, and minimal heat deposition effect, has been widely used in the treatment of solid tumors such as liver tumors [1][2][3][4] . In MWA, direct energy deposition in the ablation zone leads to elevated temperatures in surrounding tissues.…”

Section: Introductionmentioning

confidence: 99%

Real-time monitoring of bioelectrical impedance for minimizing tissue carbonization in microwave ablation of porcine liver

Zhang,

Wei,

Qian

et al. 2024

Preprint

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The charring tissue generated by high temperature during microwave ablation can affect the therapeutic effect, such as limiting the volume of the coagulation zone and causing rejection. This paper aimed to prevent tissue carbonization at the same time while delivering an appropriate thermal dose for effective ablations by employing a treatment protocol with real-time monitoring of bioelectrical impedance. Firstly, based on finite element simulation, the current field response under different ablation states. Next, the impedance changes measured by the electrodes were correlated to the physical state of the ablated tissue, and the degree of carbonization was monitored and controlled in real time. Finite element simulations revealed that the dielectric properties of biological tissues changed dynamically during the ablation process. The relative change rule of the electrical impedance magnitude of the ex vivo porcine liver throughout the entire MWA process and the reduction of the central region carbonization were obtained by the MWA experiment. Charring tissue was eliminated without water cooling at 40 W and significantly reduced at 50 W and 60 W. The carbonization during MWA can be reduced according to the relative change pattern of tissue electrical impedance for optimizing microwave thermal ablation efficacy.

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“…Currently, a wide variety of computer-aided diagnosis (CAD) systems have been created to help physicians categorize, segment, and diagnose medical images ( Huang et al, 2021 ; Huang et al, 2022 ; Luo et al, 2022 ), particularly in ultrasound images ( Huang et al, 2020a ; Huang and Ye, 2021 ; Xu et al, 2022b ; Li et al, 2022 ). Some research focuses on migrating research from the traditional imaging field to medical imaging ( Xu et al, 2022a ; Yan et al, 2022 ; Huang et al, 2023 ).…”

Section: Introductionmentioning

confidence: 99%

Long-term liver lesion tracking in contrast-enhanced ultrasound videos via a siamese network with temporal motion attention

et al. 2023

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Propose: Contrast-enhanced ultrasound has shown great promises for diagnosis and monitoring in a wide range of clinical conditions. Meanwhile, to obtain accurate and effective location of lesion in contrast-enhanced ultrasound videos is the basis for subsequent diagnosis and qualitative treatment, which is a challenging task nowadays.Methods: We propose to upgrade a siamese architecture-based neural network for robust and accurate landmark tracking in contrast-enhanced ultrasound videos. Due to few researches on it, the general inherent assumptions of the constant position model and the missing motion model remain unaddressed limitations. In our proposed model, we overcome these limitations by introducing two modules into the original architecture. We use a temporal motion attention based on Lucas Kanade optic flow and Karman filter to model the regular movement and better instruct location prediction. Moreover, we design a pipeline of template update to ensure timely adaptation to feature changes.Results: Eventually, the whole framework was performed on our collected datasets. It has achieved the average mean IoU values of 86.43% on 33 labeled videos with a total of 37,549 frames. In terms of tracking stability, our model has smaller TE of 19.2 pixels and RMSE of 27.6 with the FPS of 8.36 ± 3.23 compared to other classical tracking models.Conclusion: We designed and implemented a pipeline for tracking focal areas in contrast-enhanced ultrasound videos, which takes the siamese network as the backbone and uses optical flow and Kalman filter algorithm to provide position prior information. It turns out that these two additional modules are helpful for the analysis of CEUS videos. We hope that our work can provide an idea for the analysis of CEUS videos.

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Radiomics analysis of ultrasonic image predicts sensitive effects of microwave ablation in treatment of patient with benign breast tumors

Cited by 19 publications

References 27 publications

Knowledge Tensor-Aided Breast Ultrasound Image Assistant Inference Framework

Knowledge Tensor-Aided Breast Ultrasound Image Assistant Inference Framework

Real-time monitoring of bioelectrical impedance for minimizing tissue carbonization in microwave ablation of porcine liver

Long-term liver lesion tracking in contrast-enhanced ultrasound videos via a siamese network with temporal motion attention

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