An innovative non-invasive technique for subcutaneous tumour measurements
In oncological drug development, animal studies continue to play a central role in which the volume of subcutaneous tumours is monitored to assess the efficacy of new drugs. The tumour volume is estimated by taking the volume to be that of a regular spheroid with the same dimensions. However, this m...
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creator | Delgado-SanMartin, Juan Paczkowski, Marcin Hackett, Sean Smith, Andrew Waraich, Wajahat Klatzow, James Zabair, Adeala Chabokdast, Anna Rubio-Navarro, Leonardo Rahi, Amar Wilson, Zena Ehrhardt, Beate |
description | In oncological drug development, animal studies continue to play a central
role in which the volume of subcutaneous tumours is monitored to assess
the efficacy of new drugs. The tumour volume is estimated by taking the
volume to be that of a regular spheroid with the same dimensions. However,
this method is subjective, insufficiently traceable, and is subject to
error in the accuracy of volume estimates as tumours are frequently
irregular. This paper reviews the standard technique for tumour volume
assessment, calliper measurements, by conducting a statistical review of a
large dataset consisting of 2,500 tumour volume measurements from 1,600
mice by multiple operators across 6 mouse strains and 20 tumour models.
Additionally, we explore the impact of six different tumour morphologies
on volume estimation and the detection of treatment effects using a
computational tumour growth model. Finally, we propose an alternative
method to callipers for estimating volume – BioVolumeTM, a 3D scanning
technique. BioVolume simultaneously captures both stereo RGB (Red, Green
and Blue) images from different light sources and infrared thermal images
of the tumour in under a second. It then detects the tumour region
automatically and estimates the tumour volume in under a minute.
Furthermore, images can be processed in parallel within the cloud and so
the time required to process multiple images is similar to that required
for a single image. We present data of a pre-production unit test
consisting of 297 scans from over 120 mice collected by four different
operators. This work demonstrates that it is possible to record tumour
measurements in a rapid minimally invasive, morphology-independent way,
and with less human-bias compared to callipers, whilst also improving data
traceability. Furthermore, the images collected by BioVolume may be
useful, for example, as a source of biomarkers for animal welfare and
secondary drug toxicity / efficacy. |
doi_str_mv | 10.5061/dryad.hqbzkh1bb |
format | Dataset |
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role in which the volume of subcutaneous tumours is monitored to assess
the efficacy of new drugs. The tumour volume is estimated by taking the
volume to be that of a regular spheroid with the same dimensions. However,
this method is subjective, insufficiently traceable, and is subject to
error in the accuracy of volume estimates as tumours are frequently
irregular. This paper reviews the standard technique for tumour volume
assessment, calliper measurements, by conducting a statistical review of a
large dataset consisting of 2,500 tumour volume measurements from 1,600
mice by multiple operators across 6 mouse strains and 20 tumour models.
Additionally, we explore the impact of six different tumour morphologies
on volume estimation and the detection of treatment effects using a
computational tumour growth model. Finally, we propose an alternative
method to callipers for estimating volume – BioVolumeTM, a 3D scanning
technique. BioVolume simultaneously captures both stereo RGB (Red, Green
and Blue) images from different light sources and infrared thermal images
of the tumour in under a second. It then detects the tumour region
automatically and estimates the tumour volume in under a minute.
Furthermore, images can be processed in parallel within the cloud and so
the time required to process multiple images is similar to that required
for a single image. We present data of a pre-production unit test
consisting of 297 scans from over 120 mice collected by four different
operators. This work demonstrates that it is possible to record tumour
measurements in a rapid minimally invasive, morphology-independent way,
and with less human-bias compared to callipers, whilst also improving data
traceability. Furthermore, the images collected by BioVolume may be
useful, for example, as a source of biomarkers for animal welfare and
secondary drug toxicity / efficacy.</description><identifier>DOI: 10.5061/dryad.hqbzkh1bb</identifier><language>eng</language><publisher>Dryad</publisher><subject>Animal performance ; Cancer treatment ; Computed axial tomography ; Magnetic resonance imaging ; Mouse models ; Oncology ; Statistical data</subject><creationdate>2019</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0001-7247-0667</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>782,1896</link.rule.ids><linktorsrc>$$Uhttps://commons.datacite.org/doi.org/10.5061/dryad.hqbzkh1bb$$EView_record_in_DataCite.org$$FView_record_in_$$GDataCite.org$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Delgado-SanMartin, Juan</creatorcontrib><creatorcontrib>Paczkowski, Marcin</creatorcontrib><creatorcontrib>Hackett, Sean</creatorcontrib><creatorcontrib>Smith, Andrew</creatorcontrib><creatorcontrib>Waraich, Wajahat</creatorcontrib><creatorcontrib>Klatzow, James</creatorcontrib><creatorcontrib>Zabair, Adeala</creatorcontrib><creatorcontrib>Chabokdast, Anna</creatorcontrib><creatorcontrib>Rubio-Navarro, Leonardo</creatorcontrib><creatorcontrib>Rahi, Amar</creatorcontrib><creatorcontrib>Wilson, Zena</creatorcontrib><creatorcontrib>Ehrhardt, Beate</creatorcontrib><title>An innovative non-invasive technique for subcutaneous tumour measurements</title><description>In oncological drug development, animal studies continue to play a central
role in which the volume of subcutaneous tumours is monitored to assess
the efficacy of new drugs. The tumour volume is estimated by taking the
volume to be that of a regular spheroid with the same dimensions. However,
this method is subjective, insufficiently traceable, and is subject to
error in the accuracy of volume estimates as tumours are frequently
irregular. This paper reviews the standard technique for tumour volume
assessment, calliper measurements, by conducting a statistical review of a
large dataset consisting of 2,500 tumour volume measurements from 1,600
mice by multiple operators across 6 mouse strains and 20 tumour models.
Additionally, we explore the impact of six different tumour morphologies
on volume estimation and the detection of treatment effects using a
computational tumour growth model. Finally, we propose an alternative
method to callipers for estimating volume – BioVolumeTM, a 3D scanning
technique. BioVolume simultaneously captures both stereo RGB (Red, Green
and Blue) images from different light sources and infrared thermal images
of the tumour in under a second. It then detects the tumour region
automatically and estimates the tumour volume in under a minute.
Furthermore, images can be processed in parallel within the cloud and so
the time required to process multiple images is similar to that required
for a single image. We present data of a pre-production unit test
consisting of 297 scans from over 120 mice collected by four different
operators. This work demonstrates that it is possible to record tumour
measurements in a rapid minimally invasive, morphology-independent way,
and with less human-bias compared to callipers, whilst also improving data
traceability. Furthermore, the images collected by BioVolume may be
useful, for example, as a source of biomarkers for animal welfare and
secondary drug toxicity / efficacy.</description><subject>Animal performance</subject><subject>Cancer treatment</subject><subject>Computed axial tomography</subject><subject>Magnetic resonance imaging</subject><subject>Mouse models</subject><subject>Oncology</subject><subject>Statistical data</subject><fulltext>true</fulltext><rsrctype>dataset</rsrctype><creationdate>2019</creationdate><recordtype>dataset</recordtype><sourceid>PQ8</sourceid><recordid>eNqVzj0LwjAQxvEsDqLOrvkCfQmiu4iiu3u4tCcNmotN7gr100tF3J0e_sMDP6XWpi639c5UbRqhLbveve6dcW6uLnvSnigOwH5ATZEKTwPkKRibjnwvqG8x6SyuEQbCKFmzhChJB4QsCQMS56Wa3eCRcfXdhapOx-vhXLTA0HhG-0w-QBqtqe2EsR-M_WE2_z_eXGNKTg</recordid><startdate>20191014</startdate><enddate>20191014</enddate><creator>Delgado-SanMartin, Juan</creator><creator>Paczkowski, Marcin</creator><creator>Hackett, Sean</creator><creator>Smith, Andrew</creator><creator>Waraich, Wajahat</creator><creator>Klatzow, James</creator><creator>Zabair, Adeala</creator><creator>Chabokdast, Anna</creator><creator>Rubio-Navarro, Leonardo</creator><creator>Rahi, Amar</creator><creator>Wilson, Zena</creator><creator>Ehrhardt, Beate</creator><general>Dryad</general><scope>DYCCY</scope><scope>PQ8</scope><orcidid>https://orcid.org/0000-0001-7247-0667</orcidid></search><sort><creationdate>20191014</creationdate><title>An innovative non-invasive technique for subcutaneous tumour measurements</title><author>Delgado-SanMartin, Juan ; Paczkowski, Marcin ; Hackett, Sean ; Smith, Andrew ; Waraich, Wajahat ; Klatzow, James ; Zabair, Adeala ; Chabokdast, Anna ; Rubio-Navarro, Leonardo ; Rahi, Amar ; Wilson, Zena ; Ehrhardt, Beate</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-datacite_primary_10_5061_dryad_hqbzkh1bb3</frbrgroupid><rsrctype>datasets</rsrctype><prefilter>datasets</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Animal performance</topic><topic>Cancer treatment</topic><topic>Computed axial tomography</topic><topic>Magnetic resonance imaging</topic><topic>Mouse models</topic><topic>Oncology</topic><topic>Statistical data</topic><toplevel>online_resources</toplevel><creatorcontrib>Delgado-SanMartin, Juan</creatorcontrib><creatorcontrib>Paczkowski, Marcin</creatorcontrib><creatorcontrib>Hackett, Sean</creatorcontrib><creatorcontrib>Smith, Andrew</creatorcontrib><creatorcontrib>Waraich, Wajahat</creatorcontrib><creatorcontrib>Klatzow, James</creatorcontrib><creatorcontrib>Zabair, Adeala</creatorcontrib><creatorcontrib>Chabokdast, Anna</creatorcontrib><creatorcontrib>Rubio-Navarro, Leonardo</creatorcontrib><creatorcontrib>Rahi, Amar</creatorcontrib><creatorcontrib>Wilson, Zena</creatorcontrib><creatorcontrib>Ehrhardt, Beate</creatorcontrib><collection>DataCite (Open Access)</collection><collection>DataCite</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Delgado-SanMartin, Juan</au><au>Paczkowski, Marcin</au><au>Hackett, Sean</au><au>Smith, Andrew</au><au>Waraich, Wajahat</au><au>Klatzow, James</au><au>Zabair, Adeala</au><au>Chabokdast, Anna</au><au>Rubio-Navarro, Leonardo</au><au>Rahi, Amar</au><au>Wilson, Zena</au><au>Ehrhardt, Beate</au><format>book</format><genre>unknown</genre><ristype>DATA</ristype><title>An innovative non-invasive technique for subcutaneous tumour measurements</title><date>2019-10-14</date><risdate>2019</risdate><abstract>In oncological drug development, animal studies continue to play a central
role in which the volume of subcutaneous tumours is monitored to assess
the efficacy of new drugs. The tumour volume is estimated by taking the
volume to be that of a regular spheroid with the same dimensions. However,
this method is subjective, insufficiently traceable, and is subject to
error in the accuracy of volume estimates as tumours are frequently
irregular. This paper reviews the standard technique for tumour volume
assessment, calliper measurements, by conducting a statistical review of a
large dataset consisting of 2,500 tumour volume measurements from 1,600
mice by multiple operators across 6 mouse strains and 20 tumour models.
Additionally, we explore the impact of six different tumour morphologies
on volume estimation and the detection of treatment effects using a
computational tumour growth model. Finally, we propose an alternative
method to callipers for estimating volume – BioVolumeTM, a 3D scanning
technique. BioVolume simultaneously captures both stereo RGB (Red, Green
and Blue) images from different light sources and infrared thermal images
of the tumour in under a second. It then detects the tumour region
automatically and estimates the tumour volume in under a minute.
Furthermore, images can be processed in parallel within the cloud and so
the time required to process multiple images is similar to that required
for a single image. We present data of a pre-production unit test
consisting of 297 scans from over 120 mice collected by four different
operators. This work demonstrates that it is possible to record tumour
measurements in a rapid minimally invasive, morphology-independent way,
and with less human-bias compared to callipers, whilst also improving data
traceability. Furthermore, the images collected by BioVolume may be
useful, for example, as a source of biomarkers for animal welfare and
secondary drug toxicity / efficacy.</abstract><pub>Dryad</pub><doi>10.5061/dryad.hqbzkh1bb</doi><orcidid>https://orcid.org/0000-0001-7247-0667</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Animal performance Cancer treatment Computed axial tomography Magnetic resonance imaging Mouse models Oncology Statistical data |
title | An innovative non-invasive technique for subcutaneous tumour measurements |
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