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1000 Titel
  • Differentiation of brain metastases from small and non-small lung cancers using apparent diffusion coefficient (ADC) maps
1000 Autor/in
  1. Mueller, Sebastian Johannes |
  2. Khadhraoui, Eya |
  3. Neef, Nicole E. |
  4. Riedel, Christian Heiner |
  5. Ernst, Marielle |
1000 Erscheinungsjahr 2021
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-04-15
1000 Erschienen in
1000 Quellenangabe
  • 21(1):70
1000 Copyrightjahr
  • 2021
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1186/s12880-021-00602-7 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8048287/ |
1000 Publikationsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Background!#!Brain metastases are particularly common in patients with small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), with NSCLC showing a less  aggressive clinical course and lower chemo- and radio sensitivity compared to SCLC. Early adequate therapy is highly desirable and depends on a reliable classification of tumor type. The apparent diffusion coefficient is a noninvasive neuroimaging marker with the potential to differentiate between major histological subtypes. Here we determine the sensitivity and specificity of the apparent diffusion coefficient to distinguish between NSCLC and SCLC.!##!Methods!#!We enrolled all NSCLC and SCLC patients diagnosed between 2008 and 2019 at the University Medical Center Göttingen. Cranial MR scans were visually inspected for brain metastases and the ratio of the apparent diffusion coefficient (ADC) was calculated by dividing the ADC measured within the solid part of a metastasis by a reference ADC extracted from an equivalent region in unaffected tissue on the contralateral hemisphere.!##!Results!#!Out of 411 enrolled patients, we detected 129 patients (83 NSCLC, 46 SCLC) with sufficiently large brain metastases with histologically classified lung cancer and no hemorrhage. We analyzed 185 brain metastases, 84 of SCLC and 101 of NSCLC. SCLC brain metastases showed an ADC ratio of 0.68 ± 0.12 SD, and NSCLC brain metastases showed an ADC ratio of 1.47 ± 0.31 SD. Receiver operating curve statistics differentiated brain metastases of NSCLC from SCLC with an area under the curve of 0.99 and a 95% CI of 0.98 to 1, p < 0.001. Youden's J cut-point is 0.97 at a sensitivity of 0.989 and a specificity of 0.988.!##!Conclusions!#!In patients with lung cancer and brain metastases with solid tumor parts, ADC ratio enables an ad hoc differentiation of SCLC and NSCLC, easily achieved during routine neuroradiological examination. Non-invasive MR imaging enables an early-individualized management of brain metastases from lung cancer.!##!Trial registration!#!The study was registered in the German Clinical Trials Register (DRKS00023016).
1000 Sacherschließung
lokal Carcinoma, Non-Small-Cell Lung/diagnostic imaging [MeSH]
lokal Aged, 80 and over [MeSH]
lokal Aged [MeSH]
lokal Diffusion Magnetic Resonance Imaging/methods [MeSH]
lokal Carcinoma, Non-Small-Cell Lung/secondary [MeSH]
lokal Diagnosis, Differential [MeSH]
lokal Brain metastases
lokal SCLC
lokal NSCLC
lokal Sensitivity and Specificity [MeSH]
lokal Male [MeSH]
lokal ADC
lokal Research Article
lokal Algorithms [MeSH]
lokal Female [MeSH]
lokal Brain Neoplasms/secondary [MeSH]
lokal Adult [MeSH]
lokal Humans [MeSH]
lokal Retrospective Studies [MeSH]
lokal Middle Aged [MeSH]
lokal Neuroimaging
lokal Diffusion
lokal ROC Curve [MeSH]
lokal Lung Neoplasms/pathology [MeSH]
lokal Small Cell Lung Carcinoma/secondary [MeSH]
lokal Brain Neoplasms/diagnostic imaging [MeSH]
lokal Small Cell Lung Carcinoma/diagnostic imaging [MeSH]
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0003-2147-9797|https://frl.publisso.de/adhoc/uri/S2hhZGhyYW91aSwgRXlh|https://frl.publisso.de/adhoc/uri/TmVlZiwgTmljb2xlIEUu|https://frl.publisso.de/adhoc/uri/UmllZGVsLCBDaHJpc3RpYW4gSGVpbmVy|https://frl.publisso.de/adhoc/uri/RXJuc3QsIE1hcmllbGxl
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1000 Erstellt am 2023-11-15T15:08:38.878+0100
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1000 Zuletzt bearbeitet 2023-11-30T20:37:31.902+0100
1000 Objekt bearb. Thu Nov 30 20:37:31 CET 2023
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