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Article: Diffusion-weighted magnetic resonance imaging of primary cervical cancer in the detection of sub-centimetre metastatic lymph nodes

TitleDiffusion-weighted magnetic resonance imaging of primary cervical cancer in the detection of sub-centimetre metastatic lymph nodes
Authors
KeywordsCervical Cancer
Diffusion-weighted imaging
Intravoxel incoherent motion
Lymph node metastasis
Magnetic resonance imaging
Issue Date2020
PublisherBioMed Central Ltd. The Journal's web site is located at https://cancerimagingjournal.biomedcentral.com/
Citation
Cancer Imaging, 2020, v. 20 n. 1, p. article no. 27 How to Cite?
AbstractBackground: Magnetic resonance imaging (MRI) has limited accuracy in detecting pelvic lymph node (PLN) metastasis. This study aimed to examine the use of intravoxel incoherent motion (IVIM) in classifying pelvic lymph node (PLN) involvement in cervical cancer patients. Methods: Fifty cervical cancer patients with pre-treatment magnetic resonance imaging (MRI) were examined for PLN involvement by one subspecialist and one non-subspecialist radiologist. PLN status was confirmed by positron emission tomography or histology. The tumours were then segmented by both radiologists. Kruskal-Wallis tests were used to test for differences between diffusion tumour volume (DTV), apparent diffusion coefficient (ADC), pure diffusion coefficient (D), and perfusion fraction (f) in patients with no malignant PLN involvement, those with sub-centimetre and size-significant PLN metastases. These parameters were then considered as classifiers for PLN involvement, and were compared with the accuracies of radiologists. Results: Twenty-one patients had PLN involvement of which 10 had sub-centimetre metastatic PLNs. DTV increased (p = 0.013) while ADC (p = 0.015), and f (p = 0.006) decreased as the nodal status progressed from no malignant involvement to sub-centimetre and then size-significant PLN metastases. In determining PLN involvement, a classification model (DTV + f) had similar accuracies (80%) as the non-subspecialist (76%; p = 0.73) and subspecialist (90%; p = 0.31). However, in identifying patients with sub-centimetre PLN metastasis, the model had higher accuracy (90%) than the non-subspecialist (30%; p = 0.01) but had similar accuracy with the subspecialist (90%, p = 1.00). Interobserver variability in tumour delineation did not significantly affect the performance of the classification model. Conclusion: IVIM is useful in determining PLN involvement but the added value decreases with reader experience.
Persistent Identifierhttp://hdl.handle.net/10722/281984
ISSN
2019 Impact Factor: 2.193
2015 SCImago Journal Rankings: 0.670
PubMed Central ID

 

DC FieldValueLanguage
dc.contributor.authorPERUCHO, JAU-
dc.contributor.authorChiu, KWH-
dc.contributor.authorWong, EMF-
dc.contributor.authorTse, KY-
dc.contributor.authorChu, MMY-
dc.contributor.authorChan, LWC-
dc.contributor.authorPang, H-
dc.contributor.authorKhong, P-L-
dc.contributor.authorLee, EYP-
dc.date.accessioned2020-04-19T03:33:45Z-
dc.date.available2020-04-19T03:33:45Z-
dc.date.issued2020-
dc.identifier.citationCancer Imaging, 2020, v. 20 n. 1, p. article no. 27-
dc.identifier.issn1740-5025-
dc.identifier.urihttp://hdl.handle.net/10722/281984-
dc.description.abstractBackground: Magnetic resonance imaging (MRI) has limited accuracy in detecting pelvic lymph node (PLN) metastasis. This study aimed to examine the use of intravoxel incoherent motion (IVIM) in classifying pelvic lymph node (PLN) involvement in cervical cancer patients. Methods: Fifty cervical cancer patients with pre-treatment magnetic resonance imaging (MRI) were examined for PLN involvement by one subspecialist and one non-subspecialist radiologist. PLN status was confirmed by positron emission tomography or histology. The tumours were then segmented by both radiologists. Kruskal-Wallis tests were used to test for differences between diffusion tumour volume (DTV), apparent diffusion coefficient (ADC), pure diffusion coefficient (D), and perfusion fraction (f) in patients with no malignant PLN involvement, those with sub-centimetre and size-significant PLN metastases. These parameters were then considered as classifiers for PLN involvement, and were compared with the accuracies of radiologists. Results: Twenty-one patients had PLN involvement of which 10 had sub-centimetre metastatic PLNs. DTV increased (p = 0.013) while ADC (p = 0.015), and f (p = 0.006) decreased as the nodal status progressed from no malignant involvement to sub-centimetre and then size-significant PLN metastases. In determining PLN involvement, a classification model (DTV + f) had similar accuracies (80%) as the non-subspecialist (76%; p = 0.73) and subspecialist (90%; p = 0.31). However, in identifying patients with sub-centimetre PLN metastasis, the model had higher accuracy (90%) than the non-subspecialist (30%; p = 0.01) but had similar accuracy with the subspecialist (90%, p = 1.00). Interobserver variability in tumour delineation did not significantly affect the performance of the classification model. Conclusion: IVIM is useful in determining PLN involvement but the added value decreases with reader experience.-
dc.languageeng-
dc.publisherBioMed Central Ltd. The Journal's web site is located at https://cancerimagingjournal.biomedcentral.com/-
dc.relation.ispartofCancer Imaging-
dc.rightsCancer Imaging. Copyright © BioMed Central Ltd.-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectCervical Cancer-
dc.subjectDiffusion-weighted imaging-
dc.subjectIntravoxel incoherent motion-
dc.subjectLymph node metastasis-
dc.subjectMagnetic resonance imaging-
dc.titleDiffusion-weighted magnetic resonance imaging of primary cervical cancer in the detection of sub-centimetre metastatic lymph nodes-
dc.typeArticle-
dc.identifier.emailChiu, KWH: kwhchiu@hku.hk-
dc.identifier.emailTse, KY: tseky@hku.hk-
dc.identifier.emailChu, MMY: chumy@hku.hk-
dc.identifier.emailPang, H: herbpang@hku.hk-
dc.identifier.emailKhong, P-L: plkhong@hku.hk-
dc.identifier.emailLee, EYP: eyplee77@hku.hk-
dc.identifier.authorityChiu, KWH=rp02074-
dc.identifier.authorityTse, KY=rp02391-
dc.identifier.authorityPang, H=rp01857-
dc.identifier.authorityKhong, P-L=rp00467-
dc.identifier.authorityLee, EYP=rp01456-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1186/s40644-020-00303-4-
dc.identifier.pmid32252829-
dc.identifier.pmcidPMC7137185-
dc.identifier.scopuseid_2-s2.0-85083022719-
dc.identifier.hkuros309744-
dc.identifier.volume20-
dc.identifier.issue1-
dc.identifier.spagearticle no. 27-
dc.identifier.epagearticle no. 27-
dc.publisher.placeUnited Kingdom-

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