Shumpei Onishi1, Yoshinori Kajiwara2, Takeshi Takayasu3, Manish Kolakshyapati3, Minoru Ishifuro4, Vishwa Jeet Amatya5, Yukio Takeshima5, Kazuhiko Sugiyama6, Kaoru Kurisu3, Fumiyuki Yamasaki7. 1. Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan; Department of Neurosurgery, Higashihiroshima Medical Center, Hiroshima, Japan. 2. Department of Neurosurgery, Matsuyama Red Cross Hospital, Ehime, Japan. 3. Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan. 4. Department of Diagnostic Imaging, Hiroshima University Hospital, Hiroshima, Japan. 5. Department of Pathology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan. 6. Department of Clinical Oncology and Neuro-oncology Program, Hiroshima University Hospital, Hiroshima, Japan. 7. Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan. Electronic address: fyama@hiroshima-u.ac.jp.
Abstract
BACKGROUND: Perfusion computed tomography (PCT) reflects blood flow and capillary condition, which is valuable in assessing brain tumors. We evaluated PCT parameters at the tumor (t) and peritumoral (p) region to differentiate malignant brain tumors. METHODS: We performed PCT in 39 patients with supratentorial malignant brain tumors (22 glioblastomas, 6 lymphomas, 11 metastases). Regions of interests were placed manually at tumor, peritumoral region, and contralateral normal-appearing white matter. Cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time (MTT), and permeability surface (PS) were measured. These parameters were divided by those of contralateral normal-appearing white matter to normalize at tumor (relative [r]CBVt, rCBFt, rMTTt, rPSt) and peritumoral regions (rCBVp, rCBFp, rMTTp, rPSp). The parameters were evaluated with Mann-Whitney U test and receiver operating characteristics analyses. Stepwise analyses also were performed to select useful PCT parameters for differentiating these tumors. RESULTS: The rCBFt and rCBVt of glioblastoma (GBM) were greater than those of primary central nervous system lymphoma (PCNSL) (P = 0.0005, 0.0002) and brain metastasis (METS) (P = 0.0044, 0.0028). The rMTTp of METS was greater than that of GBM and PCNSL (P = 0.0001, 0.0007). The combination of rCBVt and rPSt could differentiate GBM from other tumors with sensitivity and specificity of 81.8% and 94.1%. The combination of rCBFp and rMTTp could differentiate METS from other tumors with sensitivity and specificity of 90.9% and 82.1%. CONCLUSIONS: Our study introduces and supports the usefulness of PCT parameters for differentiation among GBM, PCNSL, and METS. rCBVt and rPSt may be the best predictors of GBM. rCBFp and rMTTp may be the best predictors of METS.
BACKGROUND: Perfusion computed tomography (PCT) reflects blood flow and capillary condition, which is valuable in assessing brain tumors. We evaluated PCT parameters at the tumor (t) and peritumoral (p) region to differentiate malignant brain tumors. METHODS: We performed PCT in 39 patients with supratentorial malignant brain tumors (22 glioblastomas, 6 lymphomas, 11 metastases). Regions of interests were placed manually at tumor, peritumoral region, and contralateral normal-appearing white matter. Cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time (MTT), and permeability surface (PS) were measured. These parameters were divided by those of contralateral normal-appearing white matter to normalize at tumor (relative [r]CBVt, rCBFt, rMTTt, rPSt) and peritumoral regions (rCBVp, rCBFp, rMTTp, rPSp). The parameters were evaluated with Mann-Whitney U test and receiver operating characteristics analyses. Stepwise analyses also were performed to select useful PCT parameters for differentiating these tumors. RESULTS: The rCBFt and rCBVt of glioblastoma (GBM) were greater than those of primary central nervous system lymphoma (PCNSL) (P = 0.0005, 0.0002) and brain metastasis (METS) (P = 0.0044, 0.0028). The rMTTp of METS was greater than that of GBM and PCNSL (P = 0.0001, 0.0007). The combination of rCBVt and rPSt could differentiate GBM from other tumors with sensitivity and specificity of 81.8% and 94.1%. The combination of rCBFp and rMTTp could differentiate METS from other tumors with sensitivity and specificity of 90.9% and 82.1%. CONCLUSIONS: Our study introduces and supports the usefulness of PCT parameters for differentiation among GBM, PCNSL, and METS. rCBVt and rPSt may be the best predictors of GBM. rCBFp and rMTTp may be the best predictors of METS.
Authors: Lelio Guida; Vittorio Stumpo; Jacopo Bellomo; Christiaan Hendrik Bas van Niftrik; Martina Sebök; Moncef Berhouma; Andrea Bink; Michael Weller; Zsolt Kulcsar; Luca Regli; Jorn Fierstra Journal: Cancers (Basel) Date: 2022-03-10 Impact factor: 6.639