Tumor heterogeneity for differentiation between liver tumors and normal liver tissue in ¹⁸F-FDG PET/CT

Abstract

Aim Malignancies show higher spatial heterogeneity than normal tissue. We investigated, if textural parameters from FDG PET describing the heterogeneity function as tool to differentiate between tumor and normal liver tissue.

Methods FDG PET/CT scans of 80 patients with liver metastases and 80 patients with results negative upper abdominal organs were analyzed. Metastases and normal liver tissue were analyzed drawing up to three VOIs with a diameter of 25 mm in healthy liver tissue of the tumoral affected and results negative liver, whilst up to 3 metastases per patient were delineated. Within these VOIs 30 different textural parameters were calculated as well as SUV. The parameters were compared in terms of intra-patient and inter-patient variability (2-sided t test). ROC analysis was performed to analyze predictive power and cut-off values.

Results 28 textural parameters differentiated healthy and pathological tissue (p < 0.05) with high sensitivity and specificity. SUV showed ability to differentiate but with a lower significance. 15 textural parameters as well as SUV showed a significant variation between healthy tissues out of tumour infested and negative livers. Mean intra- and inter-patient variability of metastases were found comparable or lower for 6 of the textural features than the ones of SUV. They also showed good values of mean intra- and inter-patient variability of VOIs drawn in liver tissue of patients with metastases and of results negative ones.

Conclusion Heterogeneity parameters assessed in FDG PET are promising to classify tissue and differentiate malignant lesions usable for more personalized treatment planning, therapy response evaluation and precise delineation of tumors for target volume determination as part of radiation therapy planning.

Zusammenfassung

Ziel Maligne Erkrankungen zeigen eine höhere räumliche Heterogenität als normales Gewebe. Wir untersuchten, ob Texturparameter der FDG-PET, die die Heterogenität beschreiben, als Werkzeug zur Unterscheidung zwischen Tumor- und normalem Lebergewebe dienen.

Methoden FDG-PET/CT-Scans von 80 Patienten mit Lebermetastasen und 80 Patienten mit negativen Befunden der abdominalen Organe wurden analysiert. Metastasen und normales Lebergewebe wurden analysiert, wobei bis zu 3 VOIs mit einem Durchmesser von 25 mm im gesunden Lebergewebe der vom Tumor betroffenen Leber bzw. von Lebern mit negativem Befund gelegt wurden, während bis zu 3 Metastasen pro Patient abgegrenzt wurden. Innerhalb dieser VOIs wurden 30 verschiedene Texturparameter sowie der SUV berechnet. Die Parameter wurden in Bezug auf die intra- und interindividuelle Variabilität verglichen (2-seitiger t-Test). Eine ROC-Analyse wurde durchgeführt, um die Vorhersagekraft und die Cut-off-Werte zu analysieren.

Ergebnisse 28 Texturparameter unterschieden gesundes und pathologisches Gewebe (p < 0,05) mit hoher Sensitivität und Spezifität. Der SUV zeigte die Fähigkeit zur Differenzierung, jedoch mit einer geringeren Signifikanz. 15 Texturparameter sowie der SUV zeigten eine signifikante Variation zwischen gesundem Gewebe aus tumorbefallener und negativer Leber. Die mittlere intra- und interindividuelle Variabilität der Metastasen war bei 6 der Texturmerkmale vergleichbar bzw. niedriger als beim SUV. Sie zeigten auch gute Werte für die mittlere intra- und interindividuelle Variabilität der VOIs, die im Lebergewebe von Patienten mit Metastasen und mit negativen Befunden gelegt wurden.

Schlussfolgerung Die in der FDG-PET bewerteten Heterogenitätsparameter sind vielversprechend, um Gewebe zu klassifizieren und maligne Läsionen zu differenzieren, die für eine stärker personalisierte Behandlungsplanung, eine Beurteilung des Therapieansprechens und eine präzise Abgrenzung von Tumoren zur Bestimmung des Zielvolumens im Rahmen der Strahlentherapieplanung geeignet sind.

Key words

textural analysis - heterogeneity - tissue classification - liver metastases

Schlüsselwörter

texturale Analyse - Heterogenität - Gewebeklassifikation - Lebermetastasen

Publikationsverlauf

Eingereicht: 17. Juli 2020

Angenommen: 23. September 2020

Artikel online veröffentlicht:
03. November 2020

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