Literature DB >> 30196522

Cervical lymphadenopathy: can the histogram analysis of apparent diffusion coefficient help to differentiate between lymphoma and squamous cell carcinoma in patients with unknown clinical primary tumor?

Antonello Vidiri1,2, Silvia Minosse3, Francesca Piludu4, Raul Pellini5, Giovanni Cristalli5, Ramy Kayal6, Giorgio Carlino4, Daniela Renzi7, Renato Covello8, Simona Marzi3.   

Abstract

PURPOSE: To retrospectively evaluate the value of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) maps in differentiating between lymphoma and metastatic squamous cell carcinoma (SCC) of unknown clinical primary in neck nodes.
METHODS: A total of 39 patients, 20 affected by lymphoma and 19 affected by metastatic non-nasopharyngeal SCC, were included in this retrospective study. All patients underwent MR imaging with a 1.5 T scanner system, including diffusion-weighted imaging (DWI) with three different b values (b = 0, 500 and 800 s/mm2). The entire tumor volume was manually delineated on the ADC maps, using the T2-weighted images and DWIs with b = 800 s/mm2 as a guide to the lesion location. The Mann-Whitney rank-sum test for independent samples was performed to compare the histogram parameters of patients with lymphoma and SCC.
RESULTS: The SCCs showed significantly higher median ADC (ADCmedian) and mean ADC (ADCmean) values, compared to lymphomas (p < 0.001), while they exhibited lower kurtosis and skewness without reaching significance (p = 0.066 and 0.148, respectively). The ADCmean and ADCmedian had the best discriminative powers for differentiating lymphoma and SCC, with an area under the curve of 87% and 85%, respectively. The optimal cutoff values for ADCmean and ADCmedian as predictors for lymphoma were ≤ 0.83 × 10-3 mm2/s and ≤ 0.73 × 10-3 mm2/s, respectively.
CONCLUSIONS: The whole-lesion ADC histogram analysis of cervical lymphadenopathy may help to discriminate lymphomas from non-nasopharyngeal SCC in patients with unknown clinical primary tumor.

Entities:  

Keywords:  Diffusion-weighted imaging; Head and neck cancer; Neck nodes; Quantitative imaging

Mesh:

Year:  2018        PMID: 30196522     DOI: 10.1007/s11547-018-0940-1

Source DB:  PubMed          Journal:  Radiol Med        ISSN: 0033-8362            Impact factor:   3.469


  4 in total

1.  Differentiation of lymphomatous, metastatic, and non-malignant lymphadenopathy in the neck with quantitative diffusion-weighted imaging: systematic review and meta-analysis.

Authors:  Seyedmehdi Payabvash; Alexandria Brackett; Reza Forghani; Ajay Malhotra
Journal:  Neuroradiology       Date:  2019-06-07       Impact factor: 2.804

2.  Texture analysis of routine T2 weighted fat-saturated images can identify head and neck paragangliomas - A pilot study.

Authors:  Adarsh Ghosh; Soumya Ranjan Malla; Ashu Seith Bhalla; Smita Manchanda; Devasenathipathy Kandasamy; Rakesh Kumar
Journal:  Eur J Radiol Open       Date:  2020-09-13

3.  Parotid gland tumors: comparison of conventional and diffusion-weighted MRI findings with histopathological results.

Authors:  Can Zafer Karaman; Ahmet Tanyeri; Recep Özgür; Veli Süha Öztürk
Journal:  Dentomaxillofac Radiol       Date:  2020-12-11       Impact factor: 2.419

Review 4.  Diagnostic evaluation and ablation treatments assessment in hepatocellular carcinoma.

Authors:  Vincenza Granata; Roberta Grassi; Roberta Fusco; Andrea Belli; Carmen Cutolo; Silvia Pradella; Giulia Grazzini; Michelearcangelo La Porta; Maria Chiara Brunese; Federica De Muzio; Alessandro Ottaiano; Antonio Avallone; Francesco Izzo; Antonella Petrillo
Journal:  Infect Agent Cancer       Date:  2021-07-19       Impact factor: 2.965

  4 in total

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