BPG is committed to discovery and dissemination of knowledge
Cited by in F6Publishing
For: Schob S, Meyer J, Gawlitza M, Frydrychowicz C, Müller W, Preuss M, Bure L, Quäschling U, Hoffmann KT, Surov A. Diffusion-Weighted MRI Reflects Proliferative Activity in Primary CNS Lymphoma. PLoS One 2016;11:e0161386. [PMID: 27571268 DOI: 10.1371/journal.pone.0161386] [Cited by in Crossref: 38] [Cited by in F6Publishing: 40] [Article Influence: 6.3] [Reference Citation Analysis]
Number Citing Articles
1 Surov A, Meyer HJ, Wienke A. Correlation between apparent diffusion coefficient (ADC) and cellularity is different in several tumors: a meta-analysis. Oncotarget. 2017;8:59492-59499. [PMID: 28938652 DOI: 10.18632/oncotarget.17752] [Cited by in Crossref: 129] [Cited by in F6Publishing: 120] [Article Influence: 25.8] [Reference Citation Analysis]
2 Meyer HJ, Leifels L, Schob S, Garnov N, Surov A. Histogram analysis parameters identify multiple associations between DWI and DCE MRI in head and neck squamous cell carcinoma. Magnetic Resonance Imaging 2018;45:72-7. [DOI: 10.1016/j.mri.2017.09.015] [Cited by in Crossref: 15] [Cited by in F6Publishing: 14] [Article Influence: 3.8] [Reference Citation Analysis]
3 Li J, Zhou Y, Wang X, Yu Y, Zhou X, Luan K. Histogram Analysis of Diffusion-Weighted Magnetic Resonance Imaging as a Biomarker to Predict Lymph Node Metastasis in T3 Stage Rectal Carcinoma. Cancer Manag Res 2021;13:2983-93. [PMID: 33833581 DOI: 10.2147/CMAR.S298907] [Reference Citation Analysis]
4 Ravanelli M, Grammatica A, Tononcelli E, Morello R, Leali M, Battocchio S, Agazzi GM, Buglione di Monale E Bastia M, Maroldi R, Nicolai P, Farina D. Correlation between Human Papillomavirus Status and Quantitative MR Imaging Parameters including Diffusion-Weighted Imaging and Texture Features in Oropharyngeal Carcinoma. AJNR Am J Neuroradiol 2018;39:1878-83. [PMID: 30213805 DOI: 10.3174/ajnr.A5792] [Cited by in Crossref: 23] [Cited by in F6Publishing: 12] [Article Influence: 5.8] [Reference Citation Analysis]
5 Surov A, Garnov N. Proving of a Mathematical Model of Cell Calculation Based on Apparent Diffusion Coefficient. Transl Oncol 2017;10:828-30. [PMID: 28863287 DOI: 10.1016/j.tranon.2017.08.001] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 0.8] [Reference Citation Analysis]
6 Wang Y, Bai G, Zhang X, Shan W, Xu L, Chen W. Correlation analysis of apparent diffusion coefficient value and P53 and Ki-67 expression in esophageal squamous cell carcinoma. Magnetic Resonance Imaging 2020;68:183-9. [DOI: 10.1016/j.mri.2020.01.011] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 1.5] [Reference Citation Analysis]
7 Schob S, Beeskow A, Dieckow J, Meyer H, Krause M, Frydrychowicz C, Hirsch F, Surov A. Diffusion profiling of tumor volumes using a histogram approach can predict proliferation and further microarchitectural features in medulloblastoma. Childs Nerv Syst 2018;34:1651-6. [DOI: 10.1007/s00381-018-3846-2] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 1.0] [Reference Citation Analysis]
8 Schob S, Meyer HJ, Dieckow J, Pervinder B, Pazaitis N, Höhn AK, Garnov N, Horvath-Rizea D, Hoffmann KT, Surov A. Histogram Analysis of Diffusion Weighted Imaging at 3T is Useful for Prediction of Lymphatic Metastatic Spread, Proliferative Activity, and Cellularity in Thyroid Cancer. Int J Mol Sci 2017;18:E821. [PMID: 28417929 DOI: 10.3390/ijms18040821] [Cited by in Crossref: 45] [Cited by in F6Publishing: 44] [Article Influence: 9.0] [Reference Citation Analysis]
9 Fiester PJ, Soule E, Natter PE, Haymes D, Rao D. Necrotic Primary Central Nervous System Lymphoma in an Immunocompetent Patient: A Case Report and Literature Review. Cureus 2019;11:e4910. [PMID: 31423387 DOI: 10.7759/cureus.4910] [Reference Citation Analysis]
10 Khan B, Chong I, Ostrom Q, Ahmed S, Dandachi D, Kotrotsou A, Colen R, Morón F. Diffusion-weighted MR imaging histogram analysis in HIV positive and negative patients with primary central nervous system lymphoma as a predictor of outcome and tumor proliferation. Oncotarget 2020;11:4093-103. [PMID: 33227089 DOI: 10.18632/oncotarget.27800] [Reference Citation Analysis]
11 Schob S, Meyer HJ, Pazaitis N, Schramm D, Bremicker K, Exner M, Höhn AK, Garnov N, Surov A. ADC Histogram Analysis of Cervical Cancer Aids Detecting Lymphatic Metastases—a Preliminary Study. Mol Imaging Biol 2017;19:953-62. [DOI: 10.1007/s11307-017-1073-y] [Cited by in Crossref: 41] [Cited by in F6Publishing: 41] [Article Influence: 8.2] [Reference Citation Analysis]
12 Surov A, Meyer HJ, Wienke A. Associations between apparent diffusion coefficient (ADC) and KI 67 in different tumors: a meta-analysis. Part 2: ADCmin. Oncotarget 2018;9:8675-80. [PMID: 29492226 DOI: 10.18632/oncotarget.24006] [Cited by in Crossref: 10] [Cited by in F6Publishing: 11] [Article Influence: 2.5] [Reference Citation Analysis]
13 Bhattacharjee R, Gupta M, Singh T, Sharma S, Khanna G, Parvaze SP, Patir R, Vaishya S, Ahlawat S, Singh A, Gupta RK. Role of intra-tumoral vasculature imaging features on susceptibility weighted imaging in differentiating primary central nervous system lymphoma from glioblastoma: a multiparametric comparison with pathological validation. Neuroradiology. [DOI: 10.1007/s00234-022-02946-5] [Reference Citation Analysis]
14 Gihr G, Horvath-Rizea D, Hekeler E, Ganslandt O, Henkes H, Hoffmann KT, Scherlach C, Schob S. Diffusion weighted imaging in high-grade gliomas: A histogram-based analysis of apparent diffusion coefficient profile. PLoS One 2021;16:e0249878. [PMID: 33857203 DOI: 10.1371/journal.pone.0249878] [Reference Citation Analysis]
15 Meyer HJ, Schob S, Münch B, Frydrychowicz C, Garnov N, Quäschling U, Hoffmann KT, Surov A. Histogram Analysis of T1-Weighted, T2-Weighted, and Postcontrast T1-Weighted Images in Primary CNS Lymphoma: Correlations with Histopathological Findings-a Preliminary Study. Mol Imaging Biol 2018;20:318-23. [PMID: 28865050 DOI: 10.1007/s11307-017-1115-5] [Cited by in Crossref: 11] [Cited by in F6Publishing: 11] [Article Influence: 3.7] [Reference Citation Analysis]
16 Schob S, Münch B, Dieckow J, Quäschling U, Hoffmann KT, Richter C, Garnov N, Frydrychowicz C, Krause M, Meyer HJ, Surov A. Whole Tumor Histogram-profiling of Diffusion-Weighted Magnetic Resonance Images Reflects Tumorbiological Features of Primary Central Nervous System Lymphoma. Transl Oncol 2018;11:504-10. [PMID: 29522972 DOI: 10.1016/j.tranon.2018.02.006] [Cited by in Crossref: 11] [Cited by in F6Publishing: 12] [Article Influence: 2.8] [Reference Citation Analysis]
17 Li S, Zhou Q, Zhang P, Ma S, Xue C, Deng J, Liu X, Zhou J. The relationship between the apparent diffusion coefficient and the Ki-67 proliferation index in intracranial solitary fibrous tumor/hemangiopericytoma. Neurosurg Rev 2021. [PMID: 34761325 DOI: 10.1007/s10143-021-01687-y] [Reference Citation Analysis]
18 Kalisz K, Alessandrino F, Beck R, Smith D, Kikano E, Ramaiya NH, Tirumani SH. An update on Burkitt lymphoma: a review of pathogenesis and multimodality imaging assessment of disease presentation, treatment response, and recurrence. Insights Imaging 2019;10:56. [PMID: 31115699 DOI: 10.1186/s13244-019-0733-7] [Cited by in Crossref: 24] [Cited by in F6Publishing: 21] [Article Influence: 8.0] [Reference Citation Analysis]
19 Nakamura M, Iwasa H, Kojima K. Central Nervous System Involvement in Mantle Cell Lymphoma Presenting Magnetic Resonance Imaging Features of Mild Encephalitis/Encephalopathy with a Reversible Splenial Lesion. Intern Med 2021;60:1597-600. [PMID: 33281168 DOI: 10.2169/internalmedicine.6386-20] [Reference Citation Analysis]
20 He YX, Qu CX, He YY, Shao J, Gao Q. Conventional MR and DW imaging findings of cerebellar primary CNS lymphoma: comparison with high-grade glioma. Sci Rep 2020;10:10007. [PMID: 32561819 DOI: 10.1038/s41598-020-67080-9] [Reference Citation Analysis]
21 Lin Y, Pan YH, Li MK, Zong XD, Pan XM, Tan SY, Guo YW. Clinical presentation of gastric Burkitt lymphoma presenting with paraplegia and acute pancreatitis: A case report. World J Gastroenterol 2021; 27(45): 7844-7854 [PMID: 34963746 DOI: 10.3748/wjg.v27.i45.7844] [Reference Citation Analysis]
22 Schob S, Voigt P, Bure L, Meyer HJ, Wickenhauser C, Behrmann C, Höhn A, Kachel P, Dralle H, Hoffmann KT, Surov A. Diffusion-Weighted Imaging Using a Readout-Segmented, Multishot EPI Sequence at 3 T Distinguishes between Morphologically Differentiated and Undifferentiated Subtypes of Thyroid Carcinoma-A Preliminary Study. Transl Oncol 2016;9:403-10. [PMID: 27661405 DOI: 10.1016/j.tranon.2016.09.001] [Cited by in Crossref: 28] [Cited by in F6Publishing: 27] [Article Influence: 4.7] [Reference Citation Analysis]
23 Fu F, Sun X, Li Y, Liu Y, Shan Y, Ji N, Wang X, Lu J, Sun S. Dynamic contrast-enhanced magnetic resonance imaging biomarkers predict chemotherapeutic responses and survival in primary central-nervous-system lymphoma. Eur Radiol 2021;31:1863-71. [PMID: 32997181 DOI: 10.1007/s00330-020-07296-5] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
24 Sun M, Cheng J, Zhang Y, Bai J, Wang F, Meng Y, Li Z. Application of DWIBS in malignant lymphoma: correlation between ADC values and Ki-67 index. Eur Radiol 2018;28:1701-8. [PMID: 29143105 DOI: 10.1007/s00330-017-5135-y] [Cited by in Crossref: 12] [Cited by in F6Publishing: 9] [Article Influence: 2.4] [Reference Citation Analysis]
25 Calandrelli R, Pilato F, Massimi L, Gessi M, Panfili M, Colosimo C. Characterization of high-grade pineal region lesions: the usefulness of apparent diffusion coefficient volumetric values. Acta Radiol 2021;:284185120986912. [PMID: 33497274 DOI: 10.1177/0284185120986912] [Reference Citation Analysis]
26 Chong I, Ostrom Q, Khan B, Dandachi D, Garg N, Kotrotsou A, Colen R, Morón F. Whole Tumor Histogram Analysis Using DW MRI in Primary Central Nervous System Lymphoma Correlates with Tumor Biomarkers and Outcome. Cancers (Basel) 2019;11:E1506. [PMID: 31597366 DOI: 10.3390/cancers11101506] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 1.3] [Reference Citation Analysis]
27 Surov A, Meyer HJ, Wienke A. Associations between apparent diffusion coefficient (ADC) and KI 67 in different tumors: a meta-analysis. Part 1: ADCmean. Oncotarget 2017;8:75434-44. [PMID: 29088879 DOI: 10.18632/oncotarget.20406] [Cited by in Crossref: 68] [Cited by in F6Publishing: 61] [Article Influence: 13.6] [Reference Citation Analysis]
28 Gihr GA, Horvath-rizea D, Garnov N, Kohlhof-meinecke P, Ganslandt O, Henkes H, Meyer HJ, Hoffmann K, Surov A, Schob S. Diffusion Profiling via a Histogram Approach Distinguishes Low-grade from High-grade Meningiomas, Can Reflect the Respective Proliferative Potential and Progesterone Receptor Status. Mol Imaging Biol 2018;20:632-40. [DOI: 10.1007/s11307-018-1166-2] [Cited by in Crossref: 24] [Cited by in F6Publishing: 26] [Article Influence: 6.0] [Reference Citation Analysis]
29 Bozdağ M, Er A, Ekmekçi S. Association of apparent diffusion coefficient with Ki-67 proliferation index, progesterone-receptor status and various histopathological parameters, and its utility in predicting the high grade in meningiomas. Acta Radiol 2021;62:401-13. [PMID: 32397733 DOI: 10.1177/0284185120922142] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
30 Zhang HW, Lyu GW, He WJ, Lei Y, Lin F, Feng YN, Wang MZ. Differential diagnosis of central lymphoma and high-grade glioma: dynamic contrast-enhanced histogram. Acta Radiol 2020;61:1221-7. [PMID: 31902220 DOI: 10.1177/0284185119896519] [Reference Citation Analysis]
31 Huttinger AL, Wheeler DG, Gnyawali S, Dornbos D 3rd, Layzer JM, Venetos N, Talentino S, Musgrave NJ, Jones C, Bratton C, Joseph ME, Sen C, Sullenger BA, Nimjee SM. Ferric Chloride-induced Canine Carotid Artery Thrombosis: A Large Animal Model of Vascular Injury. J Vis Exp 2018. [PMID: 30247470 DOI: 10.3791/57981] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
32 Meyer HJ, Pazaitis N, Surov A. ADC histogram analysis of muscle lymphoma-correlation with histopathology in a rare entity. Br J Radiol 2018;91:20180291. [PMID: 29927638 DOI: 10.1259/bjr.20180291] [Cited by in Crossref: 13] [Cited by in F6Publishing: 11] [Article Influence: 3.3] [Reference Citation Analysis]
33 Priori A, Magno S, Campiglio L, Lovati E, Tagliabue L. Imaging of sciatic lymphoma. Muscle Nerve 2017;56:E22-3. [PMID: 28543442 DOI: 10.1002/mus.25698] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.4] [Reference Citation Analysis]
34 Lee J, Kim CK, Park SY. Histogram analysis of apparent diffusion coefficients for predicting pelvic lymph node metastasis in patients with uterine cervical cancer. Magn Reson Mater Phy 2020;33:283-92. [DOI: 10.1007/s10334-019-00777-9] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 1.3] [Reference Citation Analysis]
35 He M, Tang Z, Qiang J, Xiao Z, Zhang Z. Differentiation between sinonasal natural killer/T-cell lymphomas and diffuse large B-cell lymphomas by RESOLVE DWI combined with conventional MRI. Magn Reson Imaging 2019;62:10-7. [PMID: 31212002 DOI: 10.1016/j.mri.2019.06.011] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.3] [Reference Citation Analysis]
36 Xing Z, Kang N, Lin Y, Zhou X, Xiao Z, Cao D. Performance of diffusion and perfusion MRI in evaluating primary central nervous system lymphomas of different locations. BMC Med Imaging 2020;20:62. [PMID: 32517711 DOI: 10.1186/s12880-020-00462-7] [Reference Citation Analysis]
37 Meyer HJ, Wienke A, Surov A. Correlations Between Imaging Biomarkers and Proliferation Index Ki-67 in Lymphomas: A Systematic Review and Meta-Analysis. Clin Lymphoma Myeloma Leuk 2019;19:e266-72. [PMID: 31000497 DOI: 10.1016/j.clml.2019.03.005] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 1.3] [Reference Citation Analysis]
38 Wang Y, Bai G, Guo L, Chen W. Associations Between Apparent Diffusion Coefficient Value With Pathological Type, Histologic Grade, and Presence of Lymph Node Metastases of Esophageal Carcinoma. Technol Cancer Res Treat 2019;18:1533033819892254. [PMID: 31782340 DOI: 10.1177/1533033819892254] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
39 Horvath-Rizea D, Surov A, Hoffmann KT, Garnov N, Vörkel C, Kohlhof-Meinecke P, Ganslandt O, Bäzner H, Gihr GA, Kalman M, Henkes E, Henkes H, Schob S. The value of whole lesion ADC histogram profiling to differentiate between morphologically indistinguishable ring enhancing lesions-comparison of glioblastomas and brain abscesses. Oncotarget 2018;9:18148-59. [PMID: 29719596 DOI: 10.18632/oncotarget.24454] [Cited by in Crossref: 11] [Cited by in F6Publishing: 11] [Article Influence: 2.8] [Reference Citation Analysis]
40 Surov A, Hamerla G, Meyer HJ, Winter K, Schob S, Fiedler E. Whole lesion histogram analysis of meningiomas derived from ADC values. Correlation with several cellularity parameters, proliferation index KI 67, nucleic content, and membrane permeability. Magn Reson Imaging 2018;51:158-62. [PMID: 29782920 DOI: 10.1016/j.mri.2018.05.009] [Cited by in Crossref: 24] [Cited by in F6Publishing: 22] [Article Influence: 6.0] [Reference Citation Analysis]
41 Renard D, Guillamo J, Ion I, Thouvenot E. Brainstem lesions: MRI review of standard morphological sequences. Acta Neurol Belg. [DOI: 10.1007/s13760-022-01943-y] [Reference Citation Analysis]
42 Gihr GA, Horvath-Rizea D, Kohlhof-Meinecke P, Ganslandt O, Henkes H, Richter C, Hoffmann KT, Surov A, Schob S. Histogram Profiling of Postcontrast T1-Weighted MRI Gives Valuable Insights into Tumor Biology and Enables Prediction of Growth Kinetics and Prognosis in Meningiomas. Transl Oncol 2018;11:957-61. [PMID: 29909365 DOI: 10.1016/j.tranon.2018.05.009] [Cited by in Crossref: 8] [Cited by in F6Publishing: 8] [Article Influence: 2.0] [Reference Citation Analysis]
43 Gihr GA, Horvath-Rizea D, Hekeler E, Ganslandt O, Henkes H, Hoffmann KT, Scherlach C, Schob S. Histogram Analysis of Diffusion Weighted Imaging in Low-Grade Gliomas: in vivo Characterization of Tumor Architecture and Corresponding Neuropathology. Front Oncol 2020;10:206. [PMID: 32158691 DOI: 10.3389/fonc.2020.00206] [Cited by in Crossref: 8] [Cited by in F6Publishing: 7] [Article Influence: 4.0] [Reference Citation Analysis]