A S Cottereau1, M Meignan2, C Nioche3, N Capobianco4, J Clerc5, L Chartier6, L Vercellino7, O Casasnovas8, C Thieblemont9, I Buvat3. 1. Department of Nuclear Medicine, Cochin Hospital, AP-HP, 75014, Paris, France; Université de Paris, Descartes-Paris 5, rue de l'Ecole de Médecine, F-75006, Paris, France; LITO laboratory, UMR 1288 Inserm, Institut Curie, Université Paris Saclay, Orsay, France. Electronic address: annesegolene.cottereau@aphp.fr. 2. Lysa Imaging, Henri Mondor University Hospital, AP-HP, University Paris East, Créteil, France. 3. LITO laboratory, UMR 1288 Inserm, Institut Curie, Université Paris Saclay, Orsay, France. 4. Siemens Healthcare GmbH, Erlangen, Germany; Technical University of Munich, Munich, Germany. 5. Department of Nuclear Medicine, Cochin Hospital, AP-HP, 75014, Paris, France; Université de Paris, Descartes-Paris 5, rue de l'Ecole de Médecine, F-75006, Paris, France. 6. The Lymphoma Academic Research Organisation, Statistics, Centre Hospitalier Lyon Sud, Pierre-Benite, France. 7. Department of Nuclear Medicine, Saint-Louis Hospital, AP-HP, Paris, France. 8. Department of Hematology, University Hospital of Dijon, Dijon, France. 9. Department of Hematology, Saint Louis Hospital, APHP, Paris, France.
Abstract
BACKGROUND: We analysed the prognostic value of a new baseline PET parameter reflecting the spread of the disease, the largest distance between two lesions (Dmax). We tested its complementarity to metabolic tumor volume (MTV) in a large cohort of diffuse large B cell lymphoma (DLBCL) patients from the REMARC trial (NCT01122472). PATIENTS AND METHODS: MTVs were defined using the 41% SUVmax threshold. From the three-dimensional coordinates, the centroid of each lesion was automatically obtained and considered as the lesion location. The distances between all pairs of were calculated. Dmax was obtained for each patient and normalized with the body surface area (SDmax). RESULTS: 290 patients were included from the REMARC trial in patients 60-80 years old; 91% had an advanced stage and 71% IPI≥3. High vs low SDmax significantly impacted PFS (P<0.0001) and OS (P=0.0027). Patients with SDmax>0.32 m-1 (n=82) had a 4y-PFS and OS of 46% and 71%, respectively, against 77% and 87%, respectively, for patients with low SDmax. High SDmax and high MTV were independent prognostic factors of PFS (P=0.0001 and P=0.0010 respectively) and OS (P=0.0028 and P=0.0004 respectively). Combining MTV and SDmax yielded three risk groups with no (n=109), one (n=122) or two (n=59) factors (P<0.0001 for both PFS and OS). The 4-year PFS were 90%, 63%, 41%, respectively, and the 4-year OS were 95%, 79%, 66%, respectively. In addition, patients with at least 2 of the 3 factors including high SDmax, high MTV, ECOG >2 had a higher number of CNS relapse (P=0.017). CONCLUSIONS: SDmax is a simple feature that captures lymphoma dissemination, independent from MTV. These two PET metrics, SDmax and MTV, are complementary to characterise the disease, reflecting the tumor burden and its spread. This score appeared promising for DLBCL baseline risk stratification.
BACKGROUND: We analysed the prognostic value of a new baseline PET parameter reflecting the spread of the disease, the largest distance between two lesions (Dmax). We tested its complementarity to metabolic tumor volume (MTV) in a large cohort of diffuse large B cell lymphoma (DLBCL) patients from the REMARC trial (NCT01122472). PATIENTS AND METHODS: MTVs were defined using the 41% SUVmax threshold. From the three-dimensional coordinates, the centroid of each lesion was automatically obtained and considered as the lesion location. The distances between all pairs of were calculated. Dmax was obtained for each patient and normalized with the body surface area (SDmax). RESULTS: 290 patients were included from the REMARC trial in patients 60-80 years old; 91% had an advanced stage and 71% IPI≥3. High vs low SDmax significantly impacted PFS (P<0.0001) and OS (P=0.0027). Patients with SDmax>0.32 m-1 (n=82) had a 4y-PFS and OS of 46% and 71%, respectively, against 77% and 87%, respectively, for patients with low SDmax. High SDmax and high MTV were independent prognostic factors of PFS (P=0.0001 and P=0.0010 respectively) and OS (P=0.0028 and P=0.0004 respectively). Combining MTV and SDmax yielded three risk groups with no (n=109), one (n=122) or two (n=59) factors (P<0.0001 for both PFS and OS). The 4-year PFS were 90%, 63%, 41%, respectively, and the 4-year OS were 95%, 79%, 66%, respectively. In addition, patients with at least 2 of the 3 factors including high SDmax, high MTV, ECOG >2 had a higher number of CNS relapse (P=0.017). CONCLUSIONS: SDmax is a simple feature that captures lymphoma dissemination, independent from MTV. These two PET metrics, SDmax and MTV, are complementary to characterise the disease, reflecting the tumor burden and its spread. This score appeared promising for DLBCL baseline risk stratification.
Authors: Jakoba J Eertink; Gerben J C Zwezerijnen; Matthijs C F Cysouw; Sanne E Wiegers; Elisabeth A G Pfaehler; Pieternella J Lugtenburg; Bronno van der Holt; Otto S Hoekstra; Henrica C W de Vet; Josée M Zijlstra; Ronald Boellaard Journal: Eur J Nucl Med Mol Imaging Date: 2022-08-04 Impact factor: 10.057
Authors: Laetitia Vercellino; Dorine de Jong; Roberta di Blasi; Salim Kanoun; Ran Reshef; Lawrence H Schwartz; Laurent Dercle Journal: Front Oncol Date: 2021-05-28 Impact factor: 6.244