OBJECTIVES: To determine the diagnostic benefit of volume perfusion computed tomography (VPCT) at end of treatment for response assessment in lymphoma patients. METHODS: Seventy-five patients with different lymphoma subtypes were included: 50/75 patients had residual masses at end of treatment, 26/50 patients underwent VPCT at baseline and at end of treatment, and 24/50 patients only had end-of-treatment VPCTs. We evaluated the size of the main lymphoma mass, its blood flow (BF), blood volume (BV) and k-trans, calculated ratios (baseline and end of treatment) as well as sensitivity/specificity/negative (NPV)/positive predictive values (PPV). For VPCT at end of treatment, a cutoff threshold between responders and non-responders was calculated. RESULTS: For patients undergoing VPCT at baseline and end of treatment, reduction in size, BF, BV and k-trans was significant (P < 0.001). Identification of non-response was reached at: <53% reduction in size (sensitivity/specificity/accuracy/PPV/NPV of 88.89%/62.5%/80.77%/84.21%/71.43%), <15% reduction of BF (sensitivity/specificity/accuracy/PPV/NPV of 100%/37.5%/80.77%/0.26%/100%), or <45% reduction of k-trans (sensitivity/specificity/accuracy/PPV/NPV of 88.89%/75%/84.62%/88.89%/75%). In the subgroup undergoing VPCT at end of treatment, BF >18.51 ml/100 ml indicated non-responsiveness (sensitivity 92.86%, specificity 72.73%, accuracy 84%, PPV 81.25%, NPV 88.89%). CONCLUSIONS: VPCT seems adequate for assessment of lymphoma response at end of treatment. The degree of residual lymphoma perfusion at end of treatment helps to identify patients likely to remain in remission 1 year after completion of therapy. KEY POINTS: • Volume perfusion computed tomography (VPCT) offers measurements for assessing tumour response. • Perfusion parameter changes measured by VPCT correlate with antitumour therapy response. • In lymphoma, baseline and end-of-treatment perfusion parameter ratios can predict response. • Perfusion measurements after treatment identify patients likely to remain in remission.
OBJECTIVES: To determine the diagnostic benefit of volume perfusion computed tomography (VPCT) at end of treatment for response assessment in lymphomapatients. METHODS: Seventy-five patients with different lymphoma subtypes were included: 50/75 patients had residual masses at end of treatment, 26/50 patients underwent VPCT at baseline and at end of treatment, and 24/50 patients only had end-of-treatment VPCTs. We evaluated the size of the main lymphoma mass, its blood flow (BF), blood volume (BV) and k-trans, calculated ratios (baseline and end of treatment) as well as sensitivity/specificity/negative (NPV)/positive predictive values (PPV). For VPCT at end of treatment, a cutoff threshold between responders and non-responders was calculated. RESULTS: For patients undergoing VPCT at baseline and end of treatment, reduction in size, BF, BV and k-trans was significant (P < 0.001). Identification of non-response was reached at: <53% reduction in size (sensitivity/specificity/accuracy/PPV/NPV of 88.89%/62.5%/80.77%/84.21%/71.43%), <15% reduction of BF (sensitivity/specificity/accuracy/PPV/NPV of 100%/37.5%/80.77%/0.26%/100%), or <45% reduction of k-trans (sensitivity/specificity/accuracy/PPV/NPV of 88.89%/75%/84.62%/88.89%/75%). In the subgroup undergoing VPCT at end of treatment, BF >18.51 ml/100 ml indicated non-responsiveness (sensitivity 92.86%, specificity 72.73%, accuracy 84%, PPV 81.25%, NPV 88.89%). CONCLUSIONS: VPCT seems adequate for assessment of lymphoma response at end of treatment. The degree of residual lymphoma perfusion at end of treatment helps to identify patients likely to remain in remission 1 year after completion of therapy. KEY POINTS: • Volume perfusion computed tomography (VPCT) offers measurements for assessing tumour response. • Perfusion parameter changes measured by VPCT correlate with antitumour therapy response. • In lymphoma, baseline and end-of-treatment perfusion parameter ratios can predict response. • Perfusion measurements after treatment identify patients likely to remain in remission.
Authors: Alexander W Sauter; Anne Merkle; Maximilian Schulze; Daniel Spira; Juergen Hetzel; Claus D Claussen; Marius S Horger Journal: Eur J Radiol Date: 2011-07-26 Impact factor: 3.528
Authors: Daniel Spira; Patrick Adam; Catharina Linder; Sven Michael Spira; Jan Pintoffl; Claus Detlef Claussen; Marius Horger Journal: AJR Am J Roentgenol Date: 2012-06 Impact factor: 3.959
Authors: Bruce D Cheson; Beate Pfistner; Malik E Juweid; Randy D Gascoyne; Lena Specht; Sandra J Horning; Bertrand Coiffier; Richard I Fisher; Anton Hagenbeek; Emanuele Zucca; Steven T Rosen; Sigrid Stroobants; T Andrew Lister; Richard T Hoppe; Martin Dreyling; Kensei Tobinai; Julie M Vose; Joseph M Connors; Massimo Federico; Volker Diehl Journal: J Clin Oncol Date: 2007-01-22 Impact factor: 44.544
Authors: Dominik Ketelsen; Marius Horger; Markus Buchgeister; Michael Fenchel; Christoph Thomas; Nadine Boehringer; Maximilian Schulze; Ilias Tsiflikas; Claus D Claussen; Martin Heuschmid Journal: Korean J Radiol Date: 2010-08-27 Impact factor: 3.500
Authors: Adeel Sabir; Rachel Schor-Bardach; Carol J Wilcox; Syed Rahmanuddin; Michael B Atkins; Jonathan B Kruskal; Sabina Signoretti; Vassilios D Raptopoulos; S Nahum Goldberg Journal: AJR Am J Roentgenol Date: 2008-07 Impact factor: 3.959
Authors: Wolfgang M Thaiss; Ulrike Haberland; Sascha Kaufmann; Daniel Spira; Christoph Thomas; Konstantin Nikolaou; Marius Horger; Alexander W Sauter Journal: Eur Radiol Date: 2015-12-17 Impact factor: 5.315
Authors: Roland Syha; Sergios Gatidis; Gerd Grözinger; Ulrich Grosse; Michael Maurer; Lars Zender; Marius Horger; Konstantin Nikolaou; Dominik Ketelsen Journal: Cancer Imaging Date: 2016-09-21 Impact factor: 3.909