xml: <clinical_study>
    <!-- This xml conforms to an XML Schema at:
      https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
    <required_header>
      <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
      <link_text>Link to the current ClinicalTrials.gov record.</link_text>
      <url>https://clinicaltrials.gov/ct2/show/NCT05995990</url>
    </required_header>
    <id_info>
      <org_study_id>20ON038</org_study_id>
      <nct_id>NCT05995990</nct_id>
    </id_info>
    <brief_title>Raman Spectroscopy for Liver Tumours Following Liver Surgery</brief_title>
    <official_title>Raman Spectral Imaging for Liver Tumours Following Liver Surgery</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>Nottingham University Hospitals NHS Trust</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
    </sponsors>
    <source>Nottingham University Hospitals NHS Trust</source>
    <oversight_info>
      <has_dmc>No</has_dmc>
      <is_fda_regulated_drug>No</is_fda_regulated_drug>
      <is_fda_regulated_device>No</is_fda_regulated_device>
    </oversight_info>
    <brief_summary>
      <textblock>
        The aim of the proposed research is to develop a quick and reliable method for automated&#xD;
        evaluation of tissue sections for residual tumour in histology specimens following liver&#xD;
        surgery. This advanced technology will enable assessment of liver tumours and resection&#xD;
        margins following liver surgery. The technology is based on Raman spectroscopy (RS) and&#xD;
        multivariate spectral analysis to produce 2-dimensional biochemical images that can reliably&#xD;
        separate the spectral signal of liver tumours from surrounding normal tissue.&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        In this proposal, investigators will investigate the ability of RS to distinguish between&#xD;
        normal versus cancer in tissue blocks following liver surgery. If successful, this technique&#xD;
        can then be investigated for intra-operative assessment efficacy to ensure that the resection&#xD;
        margin of the tumour is clear (free of tumour cells), enabling this powerful procedure to be&#xD;
        applied to all patients undergoing liver surgery for highest standard of care. This device is&#xD;
        an early concept development of an In-Vitro Diagnostic Medical Device.&#xD;
  &#xD;
        In this project investigators will answer the following two questions:&#xD;
  &#xD;
          -  Can Raman spectroscopy discriminate between healthy tissue and colorectal liver&#xD;
             metastases? If yes, with what accuracy?&#xD;
  &#xD;
          -  How fast can a Raman spectroscopy image of a tissue section be built? The success of&#xD;
             this research will lead to a significant improvement in the quality and efficiency of&#xD;
             liver surgery for colorectal liver metastases as it will allow all patients undergoing&#xD;
             surgery to benefit from the best treatment available to ensure resection margins are&#xD;
             clear. Making the best techniques more widely available to all patients who need them&#xD;
             reduces inequality in healthcare.&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Completed</overall_status>
    <start_date type="Actual">November 25, 2020</start_date>
    <completion_date type="Actual">December 31, 2021</completion_date>
    <primary_completion_date type="Actual">December 31, 2021</primary_completion_date>
    <phase>N/A</phase>
    <study_type>Interventional</study_type>
    <has_expanded_access>No</has_expanded_access>
    <study_design_info>
      <allocation>N/A</allocation>
      <intervention_model>Single Group Assignment</intervention_model>
      <primary_purpose>Basic Science</primary_purpose>
      <masking>None (Open Label)</masking>
    </study_design_info>
    <primary_outcome>
      <measure>Raman spectroscopy is able to discriminate between healthy liver tissue and colorectal liver metastases.</measure>
      <time_frame>3 years</time_frame>
      <description>To determine whether Raman spectroscopy can discriminate between healthy liver tissue and liver tumours.</description>
    </primary_outcome>
    <secondary_outcome>
      <measure>Tissue sections can be analysed by Raman spectroscopy more time effectively than normal clinical practice.</measure>
      <time_frame>3 years</time_frame>
      <description>To determine how fast a Raman spectroscopy image of a tissue section can be built.</description>
    </secondary_outcome>
    <number_of_arms>1</number_of_arms>
    <enrollment type="Actual">19</enrollment>
    <condition>Colorectal Cancer Metastatic</condition>
    <arm_group>
      <arm_group_label>Colorectal liver metatases</arm_group_label>
      <arm_group_type>Experimental</arm_group_type>
      <description>Liver tissue containing colorectal liver metastases</description>
    </arm_group>
    <intervention>
      <intervention_type>Device</intervention_type>
      <intervention_name>Raman Spectrometry</intervention_name>
      <description>Laboratory technique of Raman Spectrometry</description>
      <arm_group_label>Colorectal liver metatases</arm_group_label>
    </intervention>
    <eligibility>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  Patients undergoing surgery for liver tumours (colorectal liver metastases).&#xD;
  &#xD;
            -  Able to give informed consent.&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
          • Patients where there is any doubt regarding the diagnosis from pathologist as ascertained&#xD;
          by previous diagnostic biopsy.&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>18 Years</minimum_age>
      <maximum_age>N/A</maximum_age>
      <healthy_volunteers>No</healthy_volunteers>
    </eligibility>
    <overall_official>
      <last_name>Dhanwant Gomez, FRCS</last_name>
      <role>Principal Investigator</role>
      <affiliation>Nottingham University Hospitals NHS Trust</affiliation>
    </overall_official>
    <overall_official>
      <last_name>Ioan Notingher, PhD</last_name>
      <role>Principal Investigator</role>
      <affiliation>University of Nottingham</affiliation>
    </overall_official>
    <location>
      <facility>
        <name>Nottingham University Hospitals NHS Trust, Queens Medical Centre Campus</name>
        <address>
          <city>Nottingham</city>
          <state>Nottinghamshire</state>
          <zip>NG7 2UH</zip>
          <country>United Kingdom</country>
        </address>
      </facility>
    </location>
    <location_countries>
      <country>United Kingdom</country>
    </location_countries>
    <verification_date>August 2023</verification_date>
    <study_first_submitted>July 23, 2021</study_first_submitted>
    <study_first_submitted_qc>August 10, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">August 16, 2023</study_first_posted>
    <last_update_submitted>August 10, 2023</last_update_submitted>
    <last_update_submitted_qc>August 10, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">August 16, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Sponsor</responsible_party_type>
    </responsible_party>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Liver Neoplasms</mesh_term>
    </condition_browse>
    <!-- Results have not yet been posted for this study                                          -->
  </clinical_study>
  
  
text: download date: ClinicalTrials.gov processed this data on September 20, 2023
  link text: Link to the current ClinicalTrials.gov record.
  url: https://clinicaltrials.gov/ct2/show/NCT05995990
  org study id: 20ON038
  nct id: NCT05995990
  lead sponsor: 
  has dmc: No
  is fda regulated drug: No
  is fda regulated device: No
  The aim of the proposed research is to develop a quick and reliable method for automated
        evaluation of tissue sections for residual tumour in histology specimens following liver
        surgery. This advanced technology will enable assessment of liver tumours and resection
        margins following liver surgery. The technology is based on Raman spectroscopy (RS) and
        multivariate spectral analysis to produce 2-dimensional biochemical images that can reliably
        separate the spectral signal of liver tumours from surrounding normal tissue.
  In this proposal, investigators will investigate the ability of RS to distinguish between
        normal versus cancer in tissue blocks following liver surgery. If successful, this technique
        can then be investigated for intra-operative assessment efficacy to ensure that the resection
        margin of the tumour is clear (free of tumour cells), enabling this powerful procedure to be
        applied to all patients undergoing liver surgery for highest standard of care. This device is
        an early concept development of an In-Vitro Diagnostic Medical Device.
  
        In this project investigators will answer the following two questions:
  
          -  Can Raman spectroscopy discriminate between healthy tissue and colorectal liver
             metastases? If yes, with what accuracy?
  
          -  How fast can a Raman spectroscopy image of a tissue section be built? The success of
             this research will lead to a significant improvement in the quality and efficiency of
             liver surgery for colorectal liver metastases as it will allow all patients undergoing
             surgery to benefit from the best treatment available to ensure resection margins are
             clear. Making the best techniques more widely available to all patients who need them
             reduces inequality in healthcare.
  allocation: N/A
  intervention model: Single Group Assignment
  primary purpose: Basic Science
  masking: None (Open Label)
  measure: Raman spectroscopy is able to discriminate between healthy liver tissue and colorectal liver metastases.
  time frame: 3 years
  description: To determine whether Raman spectroscopy can discriminate between healthy liver tissue and liver tumours.
  measure: Tissue sections can be analysed by Raman spectroscopy more time effectively than normal clinical practice.
  time frame: 3 years
  description: To determine how fast a Raman spectroscopy image of a tissue section can be built.
  arm group label: Colorectal liver metatases
  arm group type: Experimental
  description: Liver tissue containing colorectal liver metastases
  intervention type: Device
  intervention name: Raman Spectrometry
  description: Laboratory technique of Raman Spectrometry
  arm group label: Colorectal liver metatases
  criteria: 
  gender: All
  minimum age: 18 Years
  maximum age: N/A
  healthy volunteers: No
  last name: Dhanwant Gomez, FRCS
  role: Principal Investigator
  affiliation: Nottingham University Hospitals NHS Trust
  last name: Ioan Notingher, PhD
  role: Principal Investigator
  affiliation: University of Nottingham
  facility: 
  country: United Kingdom
  responsible party type: Sponsor
  mesh term: Liver Neoplasms