The diagnostic performance of perfusion CT in the detection of local tumor recurrence in head and neck cancer.


Journal

Clinical hemorheology and microcirculation
ISSN: 1875-8622
Titre abrégé: Clin Hemorheol Microcirc
Pays: Netherlands
ID NLM: 9709206

Informations de publication

Date de publication:
2020
Historique:
pubmed: 15 9 2020
medline: 15 12 2020
entrez: 14 9 2020
Statut: ppublish

Résumé

Detecting local tumor recurrence from post-treatment changes in head and neck cancer (HNC) remains a challenge. Based on the hypothesis that post-therapeutically altered tissue is bradytroph, lower perfusion values are expected in perfusion CT (PCT) while higher perfusion values are expected in recurrent malignant tissue. This prospective study investigates PCT for post-treatment recurrent HNC detection with a maximum slope algorithm. A total of 80 patients who received PCT of the head and neck for post-therapy follow-up, of which 63 had no tumor recurrence and 17 presented a histopathologically confirmed recurrence were examined. Regions of interest were placed in the location of the initial tumor, in reference ipsilateral nuchal muscle tissue and the corresponding internal carotid artery. Perfusion was calculated using a single-input maximum slope algorithm. With PCT, recurrent HNC can be differentiated from post-treatment tissue (p < 0.05). It further allows delineating recurrent tumor tissue from benign nuchal tissue of reference (p < 0.05). PCT data of patients with and without recurrent HNC are comparable as perfusion values of reference tissues in patients with and without HNC do not differ (p > 0.05). PCT in combination with a commercially available maximum slope algorithm offers radiologists a reliable imaging tool to detect recurrent head and neck cancer within post-therapeutically altered tissue.

Sections du résumé

BACKGROUND
Detecting local tumor recurrence from post-treatment changes in head and neck cancer (HNC) remains a challenge. Based on the hypothesis that post-therapeutically altered tissue is bradytroph, lower perfusion values are expected in perfusion CT (PCT) while higher perfusion values are expected in recurrent malignant tissue.
OBJECTIVES
This prospective study investigates PCT for post-treatment recurrent HNC detection with a maximum slope algorithm.
METHODS
A total of 80 patients who received PCT of the head and neck for post-therapy follow-up, of which 63 had no tumor recurrence and 17 presented a histopathologically confirmed recurrence were examined. Regions of interest were placed in the location of the initial tumor, in reference ipsilateral nuchal muscle tissue and the corresponding internal carotid artery. Perfusion was calculated using a single-input maximum slope algorithm.
RESULTS
With PCT, recurrent HNC can be differentiated from post-treatment tissue (p < 0.05). It further allows delineating recurrent tumor tissue from benign nuchal tissue of reference (p < 0.05). PCT data of patients with and without recurrent HNC are comparable as perfusion values of reference tissues in patients with and without HNC do not differ (p > 0.05).
CONCLUSIONS
PCT in combination with a commercially available maximum slope algorithm offers radiologists a reliable imaging tool to detect recurrent head and neck cancer within post-therapeutically altered tissue.

Identifiants

pubmed: 32925013
pii: CH209209
doi: 10.3233/CH-209209
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

171-177

Auteurs

Daniel Troeltzsch (D)

Department of Oral and Maxillofacial Surgery, Charité -Universitätsmedizin Berlin, Berlin, Germany.

Stefan Markus Niehues (SM)

Department of Radiology Charité - Universitätsmedizin Berlin, Berlin, Germany.

Tabea Fluegge (T)

Department of Oral and Maxillofacial Surgery, Charité -Universitätsmedizin Berlin, Berlin, Germany.

Norbert Neckel (N)

Department of Oral and Maxillofacial Surgery, Charité -Universitätsmedizin Berlin, Berlin, Germany.

Max Heiland (M)

Department of Oral and Maxillofacial Surgery, Charité -Universitätsmedizin Berlin, Berlin, Germany.

Bernd Hamm (B)

Department of Radiology Charité - Universitätsmedizin Berlin, Berlin, Germany.

Seyd Shnayien (S)

Department of Radiology Charité - Universitätsmedizin Berlin, Berlin, Germany.

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Classifications MeSH