Dynamic contrast-enhanced computed tomography as a potential biomarker in patients with metastatic colorectal cancer treated with regorafenib

Abstract

Background

RECIST 1.1 presents challenges when evaluating treatment response to angiogenesis inhibitors. The objective response rate, when evaluating the treatment effect of regorafenib, using RECIST 1.1, is < 2% and beneficial treatment could erroneously be terminated. Dynamic contrast-enhanced computed tomography (DCE-CT) has potential as a non-invasive functional imaging biomarker, by quantifying the treatment effect of this targeted therapy.

Purpose

To evaluate three-dimensional (3D) tumor dynamic parameters representing tumor microcirculation assessed by DCE-CT during the treatment with regorafenib in a cohort of patients with treatment-refractory metastatic colorectal cancer.

Material and Methods

Thirty-three patients with colorectal metastases (27 liver lesions, three abdominal lesions, and three pulmonary lesions) were treated with regorafenib and evaluated using DCE-CT. A total of 112 DCE-CT scans were analyzed using Advanced Perfusion and Permeability Application and correlated to standard contrast-enhanced computed tomography (CE-CT) evaluated using RECIST 1.1.

Results

A significant decrease in most DCE-CT parameters, a simultaneous decrease in tumor attenuation and an increase in tumor volume were detected during treatment. However, no associations were found between the DCE-CT parameters and PFS or OS using simple COX proportional hazards regression.

Conclusion

In this exploratory study, a significant decrease in most dynamic parameters suggests an overall treatment effect of regorafenib in tumor vasculature. DCE-CT may assist in an objective evaluation of these responses compared to RECIST. The anti-angiogenic changes could not be associated with treatment outcome in terms of PFS and OS, which might be due to the small cohort or a rather limited survival benefit in this pre-medicated treatment-refractory group of patients.

Keywords

CT quantitative dynamic contrast-enhanced computed tomography metastatic colorectal cancer patient outcome angiogenesis inhibitors

Introduction

Regorafenib (Stivarga, Bayer Pharma AG, Berlin, Germany) is an oral multi-kinase inhibitor, affecting several pathways involved in tumor angiogenesis, oncogenesis, and the tumor microenvironment (1). In patients with metastatic colorectal cancer (mCRC) and disease progression despite all current standard therapies, regorafenib has shown a small survival benefit in two randomized phase III trials, with a considerable toxicity profile, and a low objective response rate according to Response Evaluation Criteria in Solid Tumors (RECIST 1.1) (2,3). It is thus of clinical importance to identify patients who benefit from regorafenib as early as possible. So far, several protein markers as well as DNA biomarkers have been examined in hope of finding predictive markers of response (4).

The morphological changes (decreasing tumor attenuation, tumor margins becoming more well-defined, and a paradox volumetric increase) induced by regorafenib in the treatment of mCRC, and the problems arising when using RECIST criteria, have previously been described. These changes simulate disease progression (“pseudo-progression”) when monitoring treatment using a size-based criterion only. If mistaken for progressive disease, beneficial treatment could be terminated erroneously (5 –7). Lim et al. (8) evaluated the characteristic radiological changes induced by regorafenib in standard contrast-enhanced computed tomography (CE-CT), but found no associations with treatment outcome (disease control rate, progression-free survival [PFS], and overall survival [OS]). Kakizawa et al. (9) applied the “morphological criteria,” originally described by Chun et al. (6) in patients with CRC treated with bevacizumab, to patients treated with regorafenib, and found that patients with tumors that exhibiting “morphological change” had longer PFS.

New evaluation methods are warranted, and the assessment of the physiological vascular changes has been proposed as an alternative to the standard morphological response evaluation in these targeted therapies (10 –13). Various dynamic contrast-enhanced imaging modalities (CT, magnetic resonance imaging [MRI], and ultrasonography [US]) allow for non-invasive imaging of tumor vascularization and microcirculation, which could predict clinical benefits and support monitoring during therapy (14 –17).

Several studies have shown that dynamic CE-CT (DCE-CT) can assist in tumor diagnosis in a number of malignancies (18 –21) and may even assess tumor response to therapy (22,23). DCE-CT may provide an alternative evaluation method based on quantitative data and is thus a more standardized and objective evaluation method compared to the standard visual evaluations.

The purpose of this explorative study was to evaluate three-dimensional (3D) tumor dynamic parameters representing tumor microcirculation in mCRC assessed by DCE-CT and, furthermore, to explore the changes in the DCE-CT parameters during treatment with regorafenib and possible associations between DCE-CT parameters and patient outcomes defined as PFS and OS in a cohort of patients with treatment-refractory mCRC.

Material and Methods

Patients and treatment

All patients included in this single-center study (n = 33) were part of a larger multicenter study (n = 100), evaluating “The clinical value of cancer specific mutations in tissue and circulating DNA in the treatment with regorafenib.” Patients for the multicenter study were included from a large geographical area, including the uptake area of several provincial hospitals. Due to geographical reasons, this single-center study only included patients within a limited region.

The main inclusion criteria relevant for this present study were: histologically verified adenocarcinoma of the colon or the rectum; incurable metastatic disease; failure of or intolerance to all approved standard therapies; evaluable (measurable/non-measurable) disease according to RECIST 1.1; performance status 0-1; life expectancy ≥3 months; and sufficient organ function (liver, kidney, and bone marrow). All patients had received bevacizumab as a part of prior therapy.

Patients received a target dose of regorafenib of 160 mg on days 1–21 in a four-week schedule, with appropriate dose modification at the discretion of the treating physician. In accordance with institutional guidelines, the starting dose for all patients was 120 mg with dose escalation to 160 mg within the first two weeks if well tolerated. Treatment was continued until evidence of disease progression (clinical or as per RECIST), deterioration of health in general, or unacceptable toxicity.

The Regional Committee on Health Research Ethics and the National Data Protection Agency had approved both the multicenter study and this study before any patients were included. Inclusion and examinations were performed between September 2014 and March 2016. Informed written consent was obtained from all participants.

Thirty-three colorectal metastases (27 liver lesions, three abdominal lesions [two carcinomatosis and one lymph node], and three pulmonary lesions) in 33 patients were analyzed with DCE-CT performed at baseline and for each of the follow-up evaluations until four months of treatment. Image analysis was performed in a total of 226 scans. Patients were evaluated according to RECIST 1.1 using standard CE-CT.

DCE-CT and CE-CT examinations

DCE-CT and CE-CT were performed at baseline and at one, two, and four months, if progressive disease or termination of treatment due to other causes (predominantly toxicities or deterioration of general health) had not occurred. A flow chart illustrating the number of patients at each time point is shown in Fig. 1.

Fig. 1.

Flow chart illustrating the number of patients at each time point. DCE-CT as well as CE-CT were performed at each follow-up.

Perfusion CT was performed using Philips iCT 256 (Philips Healthcare, Best, The Netherlands) and intravenous administration of 60 mL iodixanol (Visipaque; GE Healthcare, Princeton, NJ, USA) 320 mg I/mL at 6 mL/s. A few patients (n = 2) had experienced previous allergic reactions to iodixanol and 60 mL iohexol (Omnipaque; GE Healthcare, Princeton, NJ, USA) 350 mg I/mL at 6 mL/s were administered instead. Contrast injection and DCE-CT was started simultaneously. Scan time was 120 s using 4-s scan cycles for the liver protocol and 60 s using 2-s scan cycles for the body protocol. The lesion that appeared most likely to be reproducible for delineation at baseline was preferred for the DCE-CT. The lesions chosen for perfusion CT were primarily located in the liver (n = 27), but a few patients did not have liver metastases; in those patients, lesions located in the retroperitoneum/abdomen (n = 3) or lung (n = 3) were chosen instead.

Axial scan mode was preset to 8 cm z-axis coverage. DCE-CT acquired 5-mm axial slices using a fixed voltage of 100 kVp (or 120 kVp if bodyweight > 100 kg) and 100 mAs.

Following DCE-CT acquisition, the patient remained in the supine position for a 10-min interval before a standard CE-CT of the thorax/abdomen and pelvis was performed for evaluation using RECIST 1.1. The CE-CT scan was performed using a bolus tracking technique (threshold of 150 Hounsfield Units [HU]) to compensate for differences in cardiac output. CT was performed for the chest and upper abdomen in the late arterial phase (post-threshold delay of 15 s) and for the abdomen and pelvis in the portal-dominant phase (post-threshold delay of 50 s) of enhancement. The scan was performed using intravenous administration of the contrast agent iodixanol (Visipaque, GE Healthcare, Princeton, NJ, USA) 320 mg I/mL adjusted to body weight using 1.7 mL/kg (total maximum of contrast agent for both scans was 153 mL) and an injection rate of 4 mL/s. CE-CT was acquired using attenuation-based tube current modulation at peak voltage of 120 kVp (or 140 kVp if body weight > 100 kg), 64 × 0.625 mm collimation, 0.5 s tube rotation time, and a pitch of 0.985. Axial slices of 2 mm were reconstructed with an increment of 1 mm.

The median dose-length product was 1533 mGy × cm (approximately 23 mSv) for the DCE-CT and 1733 mGy × cm (approximately 27 mSv) for the CE-CT.

Caution was made to achieve a similar field of view (FOV) in all exams (both DCE-CT and CE-CT) in each patient at all time points and in all patients in general.

Four-dimensional imaging analysis

The four-dimensional (4D) DCE-CT images were analyzed using the prototype software program Advanced Perfusion and Permeability Application (APPA, Philips Healthcare, Haifa, Israel).

When loading the dynamic data, a non-rigid registration was used for motion correction and spatial filtration. The software program then calculated the perfusion parameters and displayed the corresponding perfusion maps.

Volume of interest (VOI) for the quantitative measurements was defined on the morphological images of the DCE-CT set in the arterial peak enhancement (PE) series and on the CE-CT images in the portal-dominant phase. The selected target lesions were delineated using a semi-quantitative 3D sculpt-tool (Multimodality Tumor Tracking, Intellispace version 6.0, Philips Healthcare, Best, The Netherlands), covering the whole tumor volume. Each delineation was carefully undergoing manual correction before loading the perfusion software.

Using an in-house script developed in Matlab (v. R2001b, MathWorks Inc., Natick, MA, USA), all dynamic data, based on the DCE-CT VOI, were extracted corresponding to each perfusion parameter separately as histogram values (mean, median, mode, SD, skewness, and kurtosis). This method was also applied to the CE-CT VOI to extract volume and histogram values of tissue attenuation in HU.

Statistical analysis

The median time to PFS and OS was estimated using the Kaplan–Meier method. OS was defined as the time from start of treatment until death; patients (n = 1) still alive at the end of the follow-up period (31 December 2016) were censored. PFS was defined as the time from starting regorafenib treatment until treatment termination due to progressive disease.

Changes in the median value of each dynamic parameter over time, from baseline to follow-ups, were analyzed using a mixed model for repeated measurements.

Simple Cox proportional hazard regression analysis was performed to identify associations between all dynamic histogram parameters and PFS or OS. No adjustments for multiple testing were carried out since the analyses were considered exploratory.

Analyses were performed using STATA, version 13.1 (STATA Corp, College Station, TX, USA).

The level of significance was set at P < 0.05.

Results

Patient characteristics

Patient characteristics are summarized in Table 1.

Table 1.

Patient characteristics.

Patient characteristics	n = 27
Age (years), median (range)	64.1 (52–74)
Gender (n (%))
Females	13 (48)
Males	14 (52)
Primary tumor (n (%))
Rectum	11 (41)
Colon	16 (59)
Tumor load SOD* (mm)	Median (range)	Increase (%)
Baseline	96 (41–212)
1 month	103 (44–212)	7
2 months	115 (52–214)	20
3 months	143 (66–247)	49
Best response (n (%))
SD	23 (85)
PD	4 (15)
Duration of treatment (months), median (IQR)
	3.3 (1.6–5.3)

*Sum of diameters in mm (according to RECIST 1.1).

The cohort included a total of 33 patients (18 men, 15 women; mean age = 63.7 years; age range = 50–77 years). Median duration of treatment was 3.5 months (interquartile range [IQR] = 1.7–5.3). No patients were lost to follow-up.

The best overall response was stable disease in 28 patients (85%). The remaining five patients (15%) exhibited progressive disease as best response according to RECIST 1.1. Median PFS and OS for the whole group were 3.6 months (95% confidence interval [CI] = 2.1–3.9) and 5.7 months (95% CI = 4.3–7.3), respectively (Fig. 2).

Fig. 2.

Kaplan–Meier progression-free survival and overall survival curves.

In the following, the cohort of 33 patients was stratified into 27 “liver metastases” and six “others” during analysis of the DCE-CT data. The results demonstrated here are based primarily on the “liver metastases,” but data from “others” was also analyzed and is commented on in the end of this section.

Standard CE-CT

The characteristic morphological changes seen during treatment with regorafenib are illustrated in Fig. 3. Changes in the median tumor volume and tumor tissue attenuation over time were analyzed using a mixed model for repeated measurements. Over time, a statistically significant increase in tumor volume (Fig. 4) and a significant decrease in the tumor tissue attenuation values (data not shown) in the portal-dominant phase of enhancement were registered.

Fig. 3.

The characteristic morphological changes seen during treatment with regorafenib. (a) Cavitation of lung metastases. (b) Decreasing attenuation values and increasing volume of a lymph node (arrow). (c) Decreasing attenuation values, increasing volume, and development of well-defined margins in liver metastases.

Fig. 4.

Development in tumor volume (cm³) during treatment with regorafenib. Estimated means, 95% confidence intervals, and P values are depicted. A significant increase is seen between baseline and follow-up at two and four months.

No general associations between PFS or OS and the standard CE-CT histogram parameters of tissue attenuation were identified (data not shown).

DCE-CT

Changes in tumor morphology in the standard CE-CT images and the corresponding perfusion maps (hepatic portal blood volume and arterial perfusion deconvolution) over time are illustrated in Fig. 5. Increasing tumor volume is seen in the morphologic images, while the corresponding perfusion maps indicate decreasing blood volume and arterial perfusion in the lesion. The associated DCE-CT histograms are outlined in Fig. 6. During treatment, the histograms shifted towards lower attenuation values (indicative of tumor necrosis or myxoid degeneration) and displayed a larger area under the curve (increasing volume of the tumor), while they narrowed down (increasing tumor homogeneity).

Fig. 5.

Changes in tumor morphology on enhanced CT images and the corresponding perfusion maps (hepatic portal blood volume and arterial perfusion) at baseline, one, two, and four months of treatment with regorafenib. Increasing tumor volume is seen on the morphological images, while the corresponding perfusion maps demonstrate decreasing blood volume and arterial perfusion in the lesion.

Fig. 6.

The corresponding DCE-CT histograms of “hepatic portal blood volume” and “arterial perfusion” in a patient, at baseline, one, two, and four months of treatment. The histograms are shifting towards lower values (left) representing decreasing values. The histograms display a greater “area under the curve,” corresponding to the increasing volume during treatment, and grow narrower, illustrating increasing tumor homogeneity.

Estimated means and changes in the median dynamic parameters over time derived from the mixed model for repeated measurements are outlined in Table 2. As seen by the analyses of the standard CT histogram parameters, the estimated mean of the median tumor attenuation values at the arterial peak enhancement (PE) decreased significantly during regorafenib treatment. An illustration of the estimated mean values over time, derived from the quantified histogram median values of the “hepatic portal blood volume,” are outlined in Fig. 7. During the treatment, a significant decrease was evident. In general, we observed a significant decrease in most perfusion parameters over time. Changes in the perfusion parameters were most pronounced in the early phase of treatment (follow-up at one and two months compared to baseline) and subsided or withdrew completely over time.

Table 2.

Estimated means and changes in the median dynamic values derived from the mixed model for repeated measurements.

	PE (HU)	Perm (mL/min/100 g)	BV perm (%)	AP_Dec (mL/min/100 g)	AP_Max (mL/min/100 g)	HPI (0–1)	HPBV (%)	HPP_Dec (mL/min/100 g)	HPP_Max (mL/min/100 g)	St.AP_Dec (g/mL)	St.AP_Max (g/mL)	St.HPP_Dec (g/mL)	St.HPP_Max (g/mL)	HPMTT (s)
0. Baseline	67.2	8.3	11.0	44.1	66.2	0.43	20..4	57.8	88.1	4.6	7.0	6.0	9.2	20.0
95% CI	62.2; 72.2	6.3; 10.3	7.0; 14.9	37.3; 50.8	57.3; 75.2	0.39; 0.48	17.8; 23.0	50.2; 65.4	75.2; 100.9	3.8; 5.4	5.9; 8.1	5.3; 6.7	7.8; 10.6	17.9; 22.1
1. Follow-up	61.0	6.7	7.2	41.5	60.5	0.43	17.5	56.6	82.9	4.2	6.1	5.6	8.3	17.7
95% CI	56.0; 66.0	4.7; 8.7	5.0; 9.5	34.7; 48.3	51.5; 69.5	0.38; 0.47	14.9; 20.0	49.0; 64.1	70.0; 95.8	3.6; 4.8	5.3; 6.9	4.9; 6.3	7.1; 9.5	15.7; 19.6
2. Follow-up	56.1	4.6	5.2	40.1	57.1	0.43	15.4	52.8	82.5	3.9	5.6	4.9	7.9	16.1
95% CI	50.9; 61.3	2.5; 6.7	2.7; 7.6	32.9; 47.2	47.6; 66.7	0.38; 0.48	12.7; 18.2	44.8; 60.7	68.9; 96.1	3.2; 4.6	4.5; 6.6	4.2; 5.7	6.6; 9.1	15.0; 17.2
3. Follow-up	53.0	4.9	2.9	35.5	50.9	0.45	13.0	41.3	75.7	3.9	6.0	4.4	8.3	17.0
95% CI	47.1; 58.8	2.4; 7.4	0.3; 5.5	27.4; 43.6	39.9; 61.9	0.40; 0.51	9.8; 16.1	32.3; 50.3	60.4; 91.1	3.1; 4.6	4.7; 7.2	3.6; 5.3	6.6; 10.1	15.3; 18.8
Estimated means and 95% CI corresponding to each time point.
Δ0–1	–6.2	–1.5	–3.7	–2.55	–5.7	–0.006	–2.9	–1.2	–5.2	–0.42	–0.9	–0.4	–0.9	–2.3
95% CI	–10.1; −2.2	–3.4; 0.3	–7.7; 0.3	–8.3; 3.2	–14.0; 2.5	–0.04; 0.03	–5.3; −0.5	–7.5; 5.0	–15.8; 5.5	–1.0; 0.2	–1.7; −0.1	–1.0; 0.2	–1.8; 0.1	–5.0; 0.3
P	0.002	0.110	0.068	0.382	0.175	0.748	0.017	0.703	0.340	0.181	0.033	0.188	0.078	0.081
Δ1–2	–4.9	–2.1	–2.1	–1.5	–3.4	0.004	–2.0	–3.8	–0.4	–0.3	–0.5	–0.6	–0.4	–1.5
95% CI	–9.2; −0.6	–4.2; 0.1	–4.6; 0.4	–7.6; 4.7	–12.3; 5.5	–0.04; 0.04	–4.6; 0.5	–10.6; 2.9	–11.8; 11.1	–0.7; 0.2	–1,3; 0.2	–1.3; −0.01	–1.2; 0.3	–3.5; 0.4
P	0.024	0.038	0.107	0.645	0.458	0.838	0.119	0.265	0.948	0.228	0.135	0.048	0.264	0.120
Δ2–3	–3.1	0.3	–2.3	–4.5	–6.2	0.02	–2.5	–11.4	–6.8	–0.05	0.4	–0.5	0.4	0.9
95% CI	–8.2; 2.0	–2.1; 2.7	–5.0; 0.5	–11.9; 2.9	–16.9; 4.5	–0.02; 0.07	–5.6; 0.6	–19.6; −3.3	–20.5; 7.0	–0.6; 0.5	–0.8; 1.6	–1.3; 0.3	–1.0; 1.9	–0.8; 2.6
P	0.233	0.811	0.102	0.232	0.255	0.336	0.118	0.006	0.336	0.880	0.477	0.211	0.555	0.286
Estimated changes, corresponding 95% CI, and P value between two time points (e.g. Δ0–1 = change between baseline and 1, follow-up evaluation).
Δ0–2	–11.1	–3.7	–5.8	–4.0	–9.1	0.002	–5.0	–5.1	–5.6	–0.7	–1.4	–1.0	–1.3	–3.9
95% CI	–15.3; −6.8	–5.7; −1.6	–9.9; −1.7	–10.2; 2.2	–18.0; −0.2	–0.04; 0.04	–7.6; −2.4	–11.8; 1.7	–17.0; 5.9	–1.4; 0.0	–2.4; −0.4	–1.7; −0.4	–2.3; −0.3	–6.0; −1.8
P	0.000	0.000	0.006	0.203	0.045	0.925	0.000	0.142	0.341	0.051	0.006	0.001	0.012	0.000
Δ0–3	–14.2	–3.4	–8.1	–8.5	–15.3	0.02	–7.4	–16.5	–12.3	–0.7	–1.0	1.5	–0.9	–3.0
95% CI	–19.2; −9.2	–5.7; −1.0	–12.3; −3.9	–15.8; −1.3	–25.8; −4.9	–0.03; 0.07	–10.5; −4.4	–24.4; −8.6	–25.8; 1.2	–1.5; 0.03	–2.25; 0.3	–2.3; −0.8	–2.5; 0.8	–5.5; −0.5
P	0.000	0.005	0.000	0.021	0.004	0.367	0.000	0.000	0.073	0.060	0.120	0.000	0.295	0.020
Estimated changes, corresponding 95% CI, and P value between more time points (e.g. Δ0–2 = change between baseline and 2, follow-up evaluation).

PE, peak enhancement; Perm, permeability surface area; BVperm, blood volume permeability; AP_Dec, arterial perfusion – deconvolution; AP_Max, arterial perfusion – max slope; HPI, hepatic portal index; HPBV, hepatic portal blood volume; HPP_Dec, hepatic portal perfusion – deconvolution; HPP_Max, hepatic portal perfusion – max slope; HPMTT, hepatic portal mean transit time; St.AP_Dec, st. arterial perfusion – deconvolution; St.AP_Max, st. arterial perfusion – max slope; St.HPP_Dec, st. hepatic portal perfusion – deconvolution; St.HPP_Max, st. hepatic portal perfusion – max slope.Significant values in bold.

Fig. 7.

Development of “hepatic portal blood volume” during treatment with regorafenib. Estimated means, 95% confidence intervals, and P values are depicted. A significant decrease is seen between baseline and all the follow-up evaluations.

Six patients did not have liver metastases but were evaluated using lung or abdominal lesions instead. These lesions demonstrated the same trend as liver lesions concerning changes of the dynamic parameters over time (data not shown).

All dynamic histogram parameters were analyzed using a simple Cox proportional hazard regression model. Only a few random associations were statistically significant, which was expected when performing multiple analyses. No consistent associations between PFS or OS and the dynamic histogram parameters were identified (data not shown).

Discussion

Characteristic morphological changes in the liver, lung, and lymph nodes (Fig. 3) during treatment with regorafenib reported in this explorative study have been described previously (9,24,25).

The significant increase in tumor volume demonstrated emphasizes why size-based evaluation by RECIST 1.1 is inadequate in the evaluation of this treatment.

This study demonstrated a statistically significant decrease in most dynamic parameters in liver metastases during the treatment with regorafenib. These vascular changes, concurrent with the characteristic morphological changes, are consistent with the effects of tyrosine kinase inhibitors described in general (10) and are indicative of the treatment effect in the lesions monitored. Similar to our results, Cyran et al. (26) showed a significant effect of regorafenib by suppressing tumor vascularity (plasma flow and volume) monitored by DCE-CT in an experimental model of human colon carcinoma in rats. Significant reductions in most of the dynamic parameters indicate the multifunctional effect of regorafenib as a general response in all of the tumor vasculature. This is also indicated by the histograms illustrating decreasing tumor attenuation and increasing tumor volume, presumably due to necrosis, cystic, or myxoid degeneration (27).

We did not demonstrate any general associations between the DCE-CT dynamic parameters and the clinical endpoints PFS or OS. This is probably due to the relatively small sample size and short treatment effect in this heavily pre-medicated treatment-refractory patient group. Patients benefit very little from the treatment in terms of both PFS and OS and studies involving larger cohorts, preferably including patients with longer follow-up times, are needed.

Using DCE-CT in evaluating tumor response, we suggest a non-invasive way of quantifying the intra-tumoral changes during treatment with regorafenib. The value of RECIST is limited in evaluating tumor response in this targeted therapy. DCE-CT has, however, the potential to provide a sensitive and reliable imaging marker to monitor the treatment effect in these patients. Further studies are warranted to validate and refine these results before implementation into clinical practice.

The limitations of DCE-CT are the limited coverage in the z-axis (8 cm), allowing only one or a few lesions to be monitored, the motion artifacts that hamper DCE-CT analysis, and the radiation dose applied during the examinations. The prototype APPA software has an improved artifact-reducing and motion-correcting algorithm, which eliminates most artifacts. However, this still represents challenges when performing DCE-CT, and further improvements are warranted. In these end-stage patients with treatment-refractory cancer, the radiation dose is of minor concern. Furthermore, this study was prospectively designed to monitor treatment effect in a limited predefined sample size with no placebo group for comparisons. Due to ethical reasons, in this heavily pre-medicated group of end-stage patients with rapidly decreasing performance status and limited survival, it was not possible to include a control group. As a strength, CT is widely available and inexpensive, which makes it possible to integrate into routine CT protocols at almost every practice.

Other imaging techniques also propose new methods for assessing the treatment response as opposed to the standard morphological size-based evaluation. In the treatment evaluation of regorafenib this includes dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and F-18-fluordeoxyglucose positron emission tomography (FDG-PET), both of which have shown potential as non-invasive imaging biomarkers of response (28 –30).

We suggest that future studies in the advanced imaging of patients receiving regorafenib could potentially improve patient selection, early response evaluation, and speed up the clinical testing of drug combinations to overcome the fast development of resistance as seen in this study. These are all barriers to overcome to increase the clinical benefits of treatment with regorafenib in mCRC.

In conclusion, DCE-CT is feasible in mCRC and we demonstrated radiological changes consistent with angiogenetic changes in a prospective clinical cohort of patients treated with regorafenib. DCE-CT should be further explored in larger studies as an early predictor of anti-tumor effect of regorafenib.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: IRA received research grants from the Memorial Foundation of Eva and Henry Fraenkel and the Health Research Fund of Central Denmark Region. Bayer Healthcare supported the imaging part of the study but did not have any involvement in the clinical decisions regarding the treatment. Bayer was given the opportunity to comment on the first draft of this manuscript, but the authors made the final decisions about the content. Philips Healthcare provided the APPA software for the DCE-CT analysis.

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