{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T05:30:43Z","timestamp":1773034243072,"version":"3.50.1"},"reference-count":18,"publisher":"Oxford University Press (OUP)","issue":"1152","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,12,1]]},"abstract":"<jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>Radiotherapy treatment planning relies upon density information provided by CT for accurate dose calculations. Hounsfield units (HUs) are converted to electron\/physical density via an energy dependant calibration curve. Multiple curves are required to make full use of the available accelerating potentials (kVp). The curves are bi-linear with a discontinuity occurring at soft-tissue densities. The commercial algorithm, DirectDensityTM (Siemens Healthcare GmbH), constructs a single calibration curve covering all available kVp. This enables the optimisation of the CT image quality, e.g. in terms of contrast, or the reduction of the imaging dose, whilst rendering the radiotherapy treatment dose calculation robust to the energy used to acquire the CT image. We report our investigations on the clinical utilisation of the DirectDensityTM algorithm for radiotherapy treatments, by using all accelerating potentials, i.e. from 70 kVp up to 140 kVp, available at our CT treatment simulator, in contrast to previous studies that were limited to accelerating potentials spanning a subset of the available kVp.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>The DirectDensityTM (DD) reconstruction algorithm available on a SOMATOM go.Open Pro CT scanner (Siemens Healthineers) was evaluated using the RayStation v. 9 treatment planning system (RaySearch Laboratories, Stockholm, Sweden) and a CIRS Model 002LFC IMRT Thorax Phantom (SunNuclear, Melbourne, FL), which was imaged at all available kVp with clinical protocols corresponding to various anatomical sites. The DD images were compared to those with the standard reconstruction algorithm acquired only at 120 kVp, as per our routine clinical practice. The effect of increasing kVp on HU is investigated for relevant tissue substitutes. In addition, a dosimetric comparison is performed for a VMAT plan technique with 6\u2009MV X-rays using retrospective patient CT data sets representing four anatomical sites (pelvis, thorax, brain and \u201chead and neck\u201d) with five patients for each site. The original dose distributions were calculated on images acquired at 120 kVp using the standard clinical iterative reconstruction (Qr40) and compared with dose distributions recalculated on images reconstructed with the new DD (Sm40) algorithm.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>The maximum difference for radiotherapy doses calculated using images of the phantom reconstructed with Qr40 (120 kVp) or DD (all available kVp) was 0.73%. The patient plans on the anatomically representative sites studied here showed a mean PTV dose difference of \u22120.2% (s.d. 0.7) for D99%, \u22120.4% (s.d. 0.4%) for D50% and \u22120.3% (s.d. 0.4%) for D2%. Incidentally, we found a previously unreported decrease in HU, mostly notable for bone type inserts (~34\u2009HU (cortical bone)), at 110 kVp for the DD reconstructed images. The effect was not noted for the standard Qr40 reconstructions.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>DD has a minimal dosimetric impact in the dose calculations for radiotherapy treatments and could be implemented with existing clinical workflows. Attention should be paid to the HU values for images acquired at 110 kVp (DD algorithm), which warrants further investigation.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Advances in knowledge<\/jats:title>\n                  <jats:p>This is the first paper where DD was evaluated at all available kVp, leading to the incidental discovery of abnormal HU values at 110 kVp for this algorithm.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1259\/bjr.20230004","type":"journal-article","created":{"date-parts":[[2023,9,26]],"date-time":"2023-09-26T15:06:55Z","timestamp":1695740815000},"source":"Crossref","is-referenced-by-count":3,"title":["An evaluation of an energy independent CT reconstruction algorithm for use in radiotherapy treatment planning"],"prefix":"10.1093","volume":"96","author":[{"given":"Rachael","family":"Tulip","sequence":"first","affiliation":[{"name":"Northern Centre for Cancer Care \u2013 North Cumbria, Newcastle upon Tyne Hospitals NHS Foundation Trust , Newcastle upon Tyne, United Kingdom"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Spyros","family":"Manolopoulos","sequence":"additional","affiliation":[{"name":"Northern Centre for Cancer Care \u2013 North Cumbria, Newcastle upon Tyne Hospitals NHS Foundation Trust , Newcastle upon Tyne, United Kingdom"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Neil","family":"Richmond","sequence":"additional","affiliation":[{"name":"Northern Centre for Cancer Care, Newcastle upon Tyne Hospitals NHS Foundation Trust , Newcastle upon Tyne, United Kingdom"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christopher","family":"Walker","sequence":"additional","affiliation":[{"name":"Northern Centre for Cancer Care, Newcastle upon Tyne Hospitals NHS Foundation Trust , Newcastle upon Tyne, United Kingdom"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2023,10,24]]},"reference":[{"key":"2024010408205029400_b1","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/0360-3016(80)90211-4","article-title":"Computed tomography for radiotherapy planning","volume":"6","author":"Battista","year":"1980","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"2024010408205029400_b2","doi-asserted-by":"crossref","first-page":"781","DOI":"10.1259\/bjr.72.860.10624344","article-title":"Relative electron density calibration of CT scanners for Radiotherapy.Treatment planning","volume":"72","author":"Thomas","year":"1999","journal-title":"Br J Radiol"},{"key":"2024010408205029400_b3","doi-asserted-by":"crossref","DOI":"10.1259\/bjr.20160406","article-title":"Can CT scan protocols used for radiotherapy treatment planning be adjusted to optimize image quality and patient dose? 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Radiation Oncology"},{"key":"2024010408205029400_b15","doi-asserted-by":"crossref","first-page":"065014","DOI":"10.1088\/2057-1976\/ab4a27","article-title":"Potentials and limits of a novel CT reconstruction algorithm (Directdensity\u2122) developed for radiotherapy treatment planning","volume":"5","author":"D\u2019Alessio","year":"2019","journal-title":"Biomed Phys Eng Express"},{"key":"2024010408205029400_b16","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1002\/acm2.12824","article-title":"A phantom based evaluation of the dose prediction and effects in treatment plans, when calculating on a direct density CT reconstruction","volume":"21","author":"Flatten","year":"2020","journal-title":"J Appl Clin Med Phys"},{"key":"2024010408205029400_b17","doi-asserted-by":"crossref","first-page":"7845","DOI":"10.3390\/app12157845","article-title":"The role of a Directdensity\u00ae CT reconstruction in a radiotherapy Workflow: A phantom 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