Prognosis assessment in metastatic gastrointestinal stromal tumors treated with tyrosine kinase inhibitors based on CT-texture analysis

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Abstract

Purpose: Identification of prognostic CT-textural features in patients with gastrointestinal stromal tumors undergoing tyrosine kinase inhibitor (TKI) therapy.

Methods and materials: We identified 25 GIST patients (mean age, 70.58 ± 9.7 years; range, 41.25–84.08 years; 20 males, 5 females) with a total of 123 scans, each examined with a standardized CT protocol between 1/2014−7/2018. 92 texture features, based on pyradiomics library, were extracted and correlated to response categories; evaluated with help of modified Choi criteria. All patients underwent therapy with imatinib in the first line and different tyrosine kinase inhibitors after disease progression. KIT and PDGFR-mutations were registered in all patients as well as the number of previous treatment regimens, patient’s age as well as gender and the presence of contrast enhancement (vitality) in tumor. The lesion with the largest diameter was chosen and contoured using the spherical VOI tool. Inter-rater testing was performed by a second experienced radiologist. Regression and AUC analysis was performed.

Results: Ten variables could be confirmed to be significantly associated with disease progression. Of them, four textural parameters were significantly positively associated with disease progression and negatively with progression free survival (Glcm Id [grey-level co-occurrence matrix inverse difference], p = 0.012, HR 3.83; 95% CI 1.697–8.611, Glcm Idn [grey-level co-occurrence matrix inverse difference normalized], p = 0.045, HR 2.06, 95% CI 1.015–4.185, Glrlm [grey-level run length matrix] normalized, p = 0.005, HR 3.181; 95% CI 1.418–7.138 and Ngtdm [neighboring grey-tone difference matrix] coarseness, p < 0.001, HR 3.156, 95% CI 1.554–6.411). Single variables were shown to be significantly inferior to the combination of all variables. After 6 months, 90% of patients with 0–1 risk factors (group 1), 64.4% with 2–3 risk variables and 38.1% of patients presenting > 3 structural risk variables showed stable disease. Gclm Id, Gclm Idn and Glrlm non-uniformity were associated with the number of previous treatments, Glrlm non-uniformity also with tumor vitality (enhancement), whereas Gclm Idn and Ngtdm coarseness were associated with the number of tumor mutations.

Conclusion: Some of the CT-textural features correlate with disease progression and the progressive free survival as well as with the number of gene mutations and the number of treatment regimens the patients were exposed to as well as with the tumor enhancement. All these features reflect tumor homogeneity.

Introduction

Gastrointestinal stromal tumors (GIST) are rare mesenchymal non-epithelial tumors arising from the Cajal interstitial cells of the GI-tract [1]. Mutations of the c-KIT are the crucial step for the development of a GIST, but other mutated genes have also been identified (e.g. PDGFR-α) [2]. Based on this knowledge, targeted drugs against these receptors have been developed and by now successfully implemented in the therapeutic armamentarium for GIST [3,4]. Many of the tyrosine kinase inhibitors (TKI) knowingly have also antiangiogenic effects blocking the vascular endothelial growth factor receptors (VEGFR) leading in most responders to a drop in blood supply and consequently to necrosis and cystic transformations of these tumors that are otherwise well vascularized [5]. Based on this knowledge, specific response criteria have been proposed which consider not only size changes induced by therapy but also such reflecting tumor perfusion and attenuation [5]. CT is the mainstay in the diagnostic and response monitoring of GIST to TKI, but other less frequently involved imaging modalities (e.g. MRI, FDG-PET) have also been successfully tested in this clinical setting [[6], [7], [8]]. The main role of imaging is to possibly assess all GIST-manifestations for treatment planning (e.g. surgery vs. systemic treatment) as well as to monitor therapy, predict malignancy risk and prognosis [9,10]. The latter has been already tested using early FDG-PET monitoring, however without success [11].

CT-texture analysis (CTTA) is one part of the radiomics spectrum which delivers quantitative data on tumor heterogeneity by analyzing the distribution and relationship of voxel grey levels in the image [12]. It is based on histogram analysis and comprises different order statistic features that finally all reflect tissue heterogeneity. Contrast enhanced CT (CECT)-data is employed for the diagnostic work-up of GIST and therefore CTTA-results are additionally influenced by the vascular network [13]. For evaluation of well perfused cancerous lesions like the GISTs, focusing on textural changes additionally to visual assessment of drug-related vascular changes (according to CHOI criteria) in the tumor seems plausible.

The aim of this study was to determine the prognostic value of CT-textural features by comparing them with the progressive free survival in our cohort. Moreover, potential associations between textural features, the number of past treatment regimens as well as the tumor mutation status and the tumor vitality (presence of enhancement) were also evaluated.

Section snippets

Subjects

The ethics committee at our institution approved this study. We identified a total of 153 GIST patients at our institution; however, most patients had to be excluded since many provided inadequate (non-standardized) image data (mostly missing thin collimation data). In the end, 25 GIST patients (mean age, 70.58 ± 9.7 years; range, 41.25–84.08 years; 20 males, 5 females) with 123 CT-examinations fulfilled enrollment criteria. Each patient was examined using a standardized CT protocol between

Identification of CTTA-features associated with disease progression

In order to identify relevant textural features associated with disease progression, binary logistic regression analysis was used for all CT-textural features (n = 92).

In a first step ten features could be confirmed to be significantly associated with disease progression (Suppl. Table 2). Interestingly, Glcm (grey-level co-occurrence matrix), Gldm (grey-level dependence matrix) and Glrlm (grey-level run length matrix) group variables represented the most consistent subtypes (80%). Out of these,

Discussion

This study employed CT texture analysis acquired in the portal-venous phase for prediction of response of gastrointestinal stromal tumors to tyrosine kinase inhibitors as well as for their characterization in terms of tissue vitality (presence of enhancement). Further potential associations were drawn with tumor gene mutations, the number of pre-treatments and patient’s age as well as gender.

In our series all patients with progressive disease showed significant higher levels of second order

Conflicts of interest

Kaspar Ekert and Clemens Hinterleitner have no conflicts of interest.

Marius Horger received institutional research support from Siemens Healthineers Germany. He is a scientific advisor of Siemens and has received speaker’s honorarium from Siemens Healthineers Germany.

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