Precision Neurosurgery: A Path Forward

Gilard, Vianney; Derrey, Stéphane; Marret, Stéphane; Bekri, Soumeya; Tebani, Abdellah

doi:10.3390/jpm11101019

Cited by 3 publications

(2 citation statements)

References 55 publications

(65 reference statements)

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“…Gillies first proposed the concept of using image omics to extract features via high-throughput radiographic images and to establish a database to provide scientific guidance for individual disease diagnosis and treatment (5). Imaging omics is a common non-invasive method used to predict tumor classification and prognosis in clinical practice (6)(7)(8). The application of imaging in clinical medicine has been paid more and more attention.…”

Section: Introductionmentioning

confidence: 99%

Development of the prediction model based on clinical-imaging omics: molecular typing and sentinel lymph node metastasis of breast cancer

Wang

Zhang

et al. 2022

Ann Transl Med

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Background: Imageology uses high-throughput and automatic computing methods to transform medical image data into quantitative data with feature space, and then makes accurate quantitative analysis, extracts features and builds models, which can intuitively observe the overall features of lesions and the surrounding tissues, and provide rich invisible information. At present, the research on the imaging features of dynamic contrast-enhanced (DCE) and diffusion-weighted imaging (DWI) to predict the molecular typing value has achieved results, but the imaging model based on DWI and DCE-magnetic resonance imaging (MRI) is not enough to predict the molecular subtypes, and the prediction value of the prediction model based on the three-dimensional volume of interest of the lesion to the four molecular subtypes of breast cancer has not been fully studied. Methods:The clinical data of 202 breast cancer patients at our hospital from October 2020 to November 2021 were collected. All patients were examined with multimodal MRI before surgery. Base on immunohistochemical recombinant Ki-67 protein (Ki-67), estrogen receptor (ER), human epidermal growth factor receptor-2 (HER-2) and progesterone receptor (PR) results, the tumors were divided into four types According to the results of the sentinel lymph node (SLN) biopsies, the patients were divided into SLN (+) and SLN (−) groups. 3-dimensional (3D) Slicer software was used to outline the region of interest (ROI), and AMni-Kinetics software was used for feature extraction. The imaging characteristics were screened using least absolute shrinkage and selection operator (LASSO)-Logistic regression model using R statistical software, and the receiver operating characteristic (ROC) curve was drawn using "pROC" software package to evaluate the prediction efficiency of the model. Results:The most efficacious model at predicting SLN (+) in breast cancer patients with different molecular subtypes and SLN metastasis was the model based on the imageological characteristics of fat inhibition, and T2-weighted imaging (T2WI), T1-weighted imaging + C (T1WI-C), and DWI combined sequences at the tumor + 2 mm periphery. AUC (sensitivity, specificity) of the validation group were 0.831 (0.856, 0.891), 0.832 (0.660, 0.877), 0.801 (0.772, 0.765), 0.904 (0.769, 0.873), and 0.819 (0.810, 0.500) respectively when the tumor was 2 mm around the tumor. Conclusions:The imaging features extracted from multi-parameter DWI, T1WI+C, and T2WI in breast cancer have certain value at predicting different molecular types and SLNs of breast cancer.^ ORCID: 0000-0001-8656-4461.

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Section: Introductionmentioning

confidence: 99%

Development of the prediction model based on clinical-imaging omics: molecular typing and sentinel lymph node metastasis of breast cancer

Wang

Zhang

et al. 2022

Ann Transl Med

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“…If patient-centered, precision medicine is a collective aim for neurosurgery as a specialty, accurate digital characterization of radiological lesions will be essential. 22 To that end, introducing image segmentation in the early stages of neurosurgical training may instigate further research and learning and improve clinical workflows. Clinically focused image segmentation courses delivered in conjunction with neuroimaging researchers and radiologists could be a simple and pragmatic way to nurture this undervalued skill set among neurosurgeons.…”

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confidence: 99%

Letter: Image Segmentation in Neurosurgery: An Undervalued Skill Set?

2022

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2023 Society for Academic Emergency Medicine Consensus Conference on Precision Emergency Medicine: Development of a policy‐relevant, patient‐centered research agenda

Strehlow,

Gisondi,

Caretta‐Weyer

et al. 2024

Academic Emergency Medicine

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ObjectivesPrecision medicine is data‐driven health care tailored to individual patients based on their unique attributes, including biologic profiles, disease expressions, local environments, and socioeconomic conditions. Emergency medicine (EM) has been peripheral to the precision medicine discourse, lacking both a unified definition of precision medicine and a clear research agenda. We convened a national consensus conference to build a shared mental model and develop a research agenda for precision EM.MethodsWe held a conference to (1) define precision EM, (2) develop an evidence‐based research agenda, and (3) identify educational gaps for current and future EM clinicians. Nine preconference workgroups (biomedical ethics, data science, health professions education, health care delivery and access, informatics, omics, population health, sex and gender, and technology and digital tools), comprising 84 individuals, garnered expert opinion, reviewed relevant literature, engaged with patients, and developed key research questions. During the conference, each workgroup shared how they defined precision EM within their domain, presented relevant conceptual frameworks, and engaged a broad set of stakeholders to refine precision EM research questions using a multistage consensus‐building process.ResultsA total of 217 individuals participated in this initiative, of whom 115 were conference‐day attendees. Consensus‐building activities yielded a definition of precision EM and key research questions that comprised a new 10‐year precision EM research agenda. The consensus process revealed three themes: (1) preeminence of data, (2) interconnectedness of research questions across domains, and (3) promises and pitfalls of advances in health technology and data science/artificial intelligence. The Health Professions Education Workgroup identified educational gaps in precision EM and discussed a training roadmap for the specialty.ConclusionsA research agenda for precision EM, developed with extensive stakeholder input, recognizes the potential and challenges of precision EM. Comprehensive clinician training in this field is essential to advance EM in this domain.

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Precision Neurosurgery: A Path Forward

Cited by 3 publications

References 55 publications

Development of the prediction model based on clinical-imaging omics: molecular typing and sentinel lymph node metastasis of breast cancer

Development of the prediction model based on clinical-imaging omics: molecular typing and sentinel lymph node metastasis of breast cancer

Letter: Image Segmentation in Neurosurgery: An Undervalued Skill Set?

2023 Society for Academic Emergency Medicine Consensus Conference on Precision Emergency Medicine: Development of a policy‐relevant, patient‐centered research agenda

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