2
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The Infratentorial Localization of Brain Metastases May Correlate with Specific Clinical Characteristics and Portend Worse Outcomes Based on Voxel-Wise Mapping

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Simple Summary

          Brain metastases (BMs) are cancerous lesions that originated from cancers outside the brain. Specific types of BMs are found distributing in specific brain areas. The infratentorial regions are frequently affected, causing severe neurological symptoms. Thus, it is necessary to investigate what types of tumors tend to form infratentorial BMs and whether these lesions are more fatal. By analyzing substantial brain imaging data of BMs, we found the vulnerability of infratentorial regions to most types of BMs, and found the infratentorial localization of BMs was significantly associated with young age, male sex, lung neuroendocrine and squamous cell carcinomas, more active cell division of the tumors, and patients with poorer outcomes. Additionally, infratentorial involvement might predict worse outcomes for patients who received surgery. Our findings underlined the distinctive role of infratentorial localization of BMs and its potential relationship with specific clinical characteristics, which may assist diagnosis, treatment choice, and prognostic prediction of BMs.

          Abstract

          The infratentorial regions are vulnerable to develop brain metastases (BMs). However, the associations between the infratentorial localization of BMs and clinical characteristics remained unclear. We retrospectively studied 1102 patients with 4365 BM lesions. Voxel-wise mapping of MRI was applied to construct the tumor frequency heatmaps after normalization and segmentation. The analysis of differential involvement (ADIFFI) was further used to obtain statistically significant clusters. Kaplan-Meier method and Cox regression were used to analyze the prognosis. The parietal, insular and left occipital lobes, and cerebellum were vulnerable to BMs with high relative metastatic risks. Infratentorial areas were site-specifically affected by the lung, breast, and colorectal cancer BMs, but inversely avoided by melanoma BMs. Significant infratentorial clusters were associated with young age, male sex, lung neuroendocrine and squamous cell carcinomas, high expression of Ki-67 of primaries and BMs, and patients with poorer prognosis. Inferior OS was observed in patients with ≥3 BMs and those who received whole-brain radiotherapy alone. Infratentorial involvement of BMs was an independent risk factor of poor prognosis for patients who received surgery ( p = 0.023, hazard ratio = 1.473, 95% confidence interval = 1.055–2.058). The current study may add valuable clinical recognition of BMs and provide references for BMs diagnosis, treatment evaluation, and prognostic prediction.

          Related collections

          Most cited references44

          • Record: found
          • Abstract: found
          • Article: not found

          Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

          This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer, with a focus on geographic variability across 20 world regions. There will be an estimated 18.1 million new cancer cases (17.0 million excluding nonmelanoma skin cancer) and 9.6 million cancer deaths (9.5 million excluding nonmelanoma skin cancer) in 2018. In both sexes combined, lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths), closely followed by female breast cancer (11.6%), prostate cancer (7.1%), and colorectal cancer (6.1%) for incidence and colorectal cancer (9.2%), stomach cancer (8.2%), and liver cancer (8.2%) for mortality. Lung cancer is the most frequent cancer and the leading cause of cancer death among males, followed by prostate and colorectal cancer (for incidence) and liver and stomach cancer (for mortality). Among females, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death, followed by colorectal and lung cancer (for incidence), and vice versa (for mortality); cervical cancer ranks fourth for both incidence and mortality. The most frequently diagnosed cancer and the leading cause of cancer death, however, substantially vary across countries and within each country depending on the degree of economic development and associated social and life style factors. It is noteworthy that high-quality cancer registry data, the basis for planning and implementing evidence-based cancer control programs, are not available in most low- and middle-income countries. The Global Initiative for Cancer Registry Development is an international partnership that supports better estimation, as well as the collection and use of local data, to prioritize and evaluate national cancer control efforts. CA: A Cancer Journal for Clinicians 2018;0:1-31. © 2018 American Cancer Society.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            3D Slicer as an image computing platform for the Quantitative Imaging Network.

            Quantitative analysis has tremendous but mostly unrealized potential in healthcare to support objective and accurate interpretation of the clinical imaging. In 2008, the National Cancer Institute began building the Quantitative Imaging Network (QIN) initiative with the goal of advancing quantitative imaging in the context of personalized therapy and evaluation of treatment response. Computerized analysis is an important component contributing to reproducibility and efficiency of the quantitative imaging techniques. The success of quantitative imaging is contingent on robust analysis methods and software tools to bring these methods from bench to bedside. 3D Slicer is a free open-source software application for medical image computing. As a clinical research tool, 3D Slicer is similar to a radiology workstation that supports versatile visualizations but also provides advanced functionality such as automated segmentation and registration for a variety of application domains. Unlike a typical radiology workstation, 3D Slicer is free and is not tied to specific hardware. As a programming platform, 3D Slicer facilitates translation and evaluation of the new quantitative methods by allowing the biomedical researcher to focus on the implementation of the algorithm and providing abstractions for the common tasks of data communication, visualization and user interface development. Compared to other tools that provide aspects of this functionality, 3D Slicer is fully open source and can be readily extended and redistributed. In addition, 3D Slicer is designed to facilitate the development of new functionality in the form of 3D Slicer extensions. In this paper, we present an overview of 3D Slicer as a platform for prototyping, development and evaluation of image analysis tools for clinical research applications. To illustrate the utility of the platform in the scope of QIN, we discuss several use cases of 3D Slicer by the existing QIN teams, and we elaborate on the future directions that can further facilitate development and validation of imaging biomarkers using 3D Slicer. Copyright © 2012 Elsevier Inc. All rights reserved.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              The pathogenesis of cancer metastasis: the 'seed and soil' hypothesis revisited.

              Researchers have been studying metastasis for more than 100 years, and only recently have we gained insight into the mechanisms by which metastatic cells arise from primary tumours and the reasons that certain tumour types tend to metastasize to specific organs. Stephen Paget's 1889 proposal that metastasis depends on cross-talk between selected cancer cells (the 'seeds') and specific organ microenvironments (the 'soil') still holds forth today. It is now known that the potential of a tumour cell to metastasize depends on its interactions with the homeostatic factors that promote tumour-cell growth, survival, angiogenesis, invasion and metastasis. How has this field developed over the past century, and what major breakthroughs are most likely to lead to effective therapeutic approaches?
                Bookmark

                Author and article information

                Journal
                Cancers (Basel)
                Cancers (Basel)
                cancers
                Cancers
                MDPI
                2072-6694
                17 January 2021
                January 2021
                : 13
                : 2
                : 324
                Affiliations
                [1 ]School of Medicine, Zhejiang University, Hangzhou 310058, Zhejiang, China; douzhangqi@ 123456zju.edu.cn (Z.D.); 21818268@ 123456zju.edu.cn (J.W.); hemmings@ 123456zju.edu.cn (H.W.); yuqian950627@ 123456zju.edu.cn (Q.Y.); fengyanzju@ 123456zju.edu.cn (F.Y.); jiangbiao@ 123456zju.edu.cn (B.J.); alexlibz@ 123456126.com (B.L.); zydxjh@ 123456zju.edu.cn (J.X.); 2315084@ 123456zju.edu.cn (C.L.)
                [2 ]Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310009, Zhejiang, China
                [3 ]Department of Radiology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310009, Zhejiang, China
                [4 ]Department of Pathology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310009, Zhejiang, China
                [5 ]School of Life Science, Westlake University, Hangzhou 310024, Zhejiang, China; xieqi@ 123456westlake.edu.cn
                Author notes
                [†]

                These authors contributed equally to this work.

                Article
                cancers-13-00324
                10.3390/cancers13020324
                7831020
                33477374
                32a00aba-f135-48ed-bcc6-007835a6c9e4
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 28 November 2020
                : 15 January 2021
                Categories
                Article

                brain metastases,magnetic resonance imaging,infratentorial localization,prognosis,voxel-wise analysis

                Comments

                Comment on this article