Radiol Oncol 2024; 58(2): 196-205. doi: 10.2478/raon-2024-0024 196 research article Utility of clinical and MR imaging parameters for prediction and monitoring of response to capecitabine and temozolomide (CAPTEM) therapy in patients with liver metastases of neuroendocrine tumors Maria Ingenerf1, Christoph Auernhammer2,3, Roberto Lorbeer1, Michael Winkelmann1, Shiwa Mansournia1, Nabeel Mansour1, Nina Hesse1, Kathrin Heinrich4, Jens Ricke1,2, Frank Berger1, Christine Schmid-Tannwald1,2 1 Department of Radiology, University Hospital, LMU Munich, Germany; 2 ENETS Centre of Excellence, Interdisciplinary Center of Neuroendocrine Tumours of the GastroEnteroPancreatic System at the University Hospital of Munich (GEPNET-KUM), University Hospital of Munich, Munich, Germany 3 Department of Internal Medicine 4, University Hospital, LMU Munich, Munich, Germany 4 Department of Medicine III, University Hospital, University of Munich, Munich, Germany Radiol Oncol 2024; 58(2): 196-205. Received 8 December 2023 Accepted 20 February 2024 Correspondence to: Christine Schmid-Tannwald, Ph.D., M.D., Department of Radiology, University Hospital, LMU Munich, Germany; Email: Christine.schmid-tannwald@med.uni-muenchen.de Disclosure: No potential conflicts of interest were disclosed. This is an open access article distributed under the terms of the CC-BY license (https://creativecommons.org/licenses/by/4.0/). Background. This study explores the predictive and monitoring capabilities of clinical and multiparametric MR pa- rameters in assessing capecitabine and temozolomide (CAPTEM) therapy response in patients with neuroendocrine tumors (NET). Patients and methods. This retrospective study (n = 44) assessed CAPTEM therapy response in neuroendocrine liver metastases (NELM) patients. Among 33 monitored patients, as a subgroup of the overall study cohort, pretherapeutic and follow-up MRI data (size, apparent diffusion coefficient [ADC] values, and signal intensities), along with clinical parameters (chromogranin A [CgA] and Ki-67%), were analyzed. Progression-free survival (PFS) served as the refer- ence. Responders were defined as those with PFS ≥ 6 months. Results. Most patients were male (75%) and had G2 tumors (76%) with a pancreatic origin (84%). Median PFS was 5.7 months; Overall Survival (OS) was 25 months. Non-responders (NR) had higher Ki-67 in primary tumors (16.5 vs. 10%, p = 0.01) and increased hepatic burden (20% vs. 5%, p = 0.007). NR showed elevated CgA post-treatment, while respond- ers (R) exhibited a mild decrease. ADC changes differed significantly between groups, with NR having decreased ADCmin (-23%) and liver-adjusted ADCmean/ADCmean liver (-16%), compared to R’s increases of ADCmin (50%) and ADCmean/ADCmean liver (30%). Receiver operating characteristic (ROC) analysis identified the highest area under the curve (AUC) (0.76) for a single parameter for ∆ ADC mean/ liver ADCmean, with a cut-off of < 6.9 (76% sensitivity, 75% specificity). Combining ∆ Size NELM and ∆ ADCmin achieved the best balance (88% sensitivity, 60% specificity) outperforming ∆ Size NELM alone (69% sensitivity, 65% specificity). Kaplan-Meier analysis indicated significantly longer PFS for ∆ ADCmean/ADCmean liver < 6.9 (p = 0.024) and ∆ Size NELM > 0% + ∆ ADCmin < -2.9% (p = 0.021). Conclusions. Survival analysis emphasizes the need for adapted response criteria, involving combined evaluation of CgA, ADC values, and tumor size for monitoring CAPTEM response in hepatic metastasized NETs. Key words: neuroendocrine tumors; liver metastases; CAPTEM therapy; clinical parameters; MR imaging; treatment response Radiol Oncol 2024; 58(2): 196-205. Ingenerf M et al./ Clinical and MR imaging at CAPTEM treatment in neuroendocrine tumors 197 Introduction Neuroendocrine tumors (NETs) encompass a di- verse group of neoplasms originating from neu- roendocrine cells, with a predilection for the gas- trointestinal (GI) tract, pancreas, and pulmonary system.1 Their indolent progression often leads to delayed diagnosis, rendering curative surgical re- section unfeasible. Among the therapeutic options for metastatic or progressive cases, Capecitabine and Temozolomide (CAPTEM) chemotherapy has emerged as an effec- tive and safe systemic regimen, particularly ben- efiting patients with well-differentiated pancreatic NETs.2.3 Response rates range widely from 17% to 70%, and progression-free survival (PFS) spans 4 to 38.5 months.1,4-6 Previous investigations into clinical biomarkers like O6-methylguanine DNA methyltransferase (MGMT) expression, alternative lengthening of telomeres (ALT) activation, and Ki- 67 index have yielded conflicting results.1,7 Thus, the imperative arises for predictive biomarkers to mitigate treatment failures and needless exposure to toxicity.1 As such, there is a growing interest in evaluating imaging parameters for prognostic and monitoring purposes in oncologic therapies. In addition to morphological changes like tumor size, MRI has the capability to display structural and functional data such as diffusion-weighted imaging (DWI). Incorporating both morphological and functional data, multiparametric MRI could offer a more comprehensive insight into subtle shifts in tumor behavior, especially in small grow- ing tumors such as NET. Parameters such as signal intensity (SI) on T1-weighted or T2-weighted imag- es, tumor vascularization, and apparent diffusion coefficient (ADC) derived from DWI are increas- ingly scrutinized for their predictive and monitor- ing potential across various therapy regimens.8-11 Notably, no prior study has assessed the utility of these MRI parameters for monitoring therapy or predicting CAPTEM response in patients with hepatic metastasized NETs. Therefore, this study aims to evaluate clinical, morphological, and func- tional imaging factors for their ability to predict and monitor therapy response in metastatic NET patients undergoing CAPTEM treatment. Patients and methods Patients This retrospective study received approval from the local research ethics committee with decision Number 23-0183 and the requirement for written informed patient consent was waived. We consec- utively enrolled patients with histologically con- firmed, resected or advanced NETs with liver me- tastases, all of whom received CAPTEM therapy and underwent pretherapeutic MRI at our depart- ment. Furthermore, in the sub-analysis focused on therapy monitoring, we incorporated all individu- als from this cohort who underwent subsequent MRI examinations (Figure 1). The timeframe for therapy initiation ranged from April 2013 to June 2022. The decision to commence CAPTEM therapy was reached through consensus in an interdiscipli- nary tumor conference certified for NETs (ENETS Center of Excellence) for each patient. MR imaging All patients were positioned supine in a 1.5 T MR system (Siemens Healthcare, Erlangen, Germany). For signal reception a phased-array coil was uti- lized. Images were acquired in accordance with our standard liver imaging protocol. The follow- ing sequences were employed for evaluation: 1. A single shot T2-weighted sequence (HASTE). 2. T1-weighted 3D GRE sequences with fat sup- pression (VIBE) prior to and at 20, 50, and 120 seconds (dependent on circulation time) post intravenous contrast injection (EOB- Bayer Pharma, Germany; 25 µmol/kg body weight). 3. Diffusion-weighted sequences with b-values of 50 and 800 s/mm². FIGURE 1. Flow-chart of including process of patients. CAP/TEM = capecitabine and temozolomide; DWI = diffusion-weighted imaging Radiol Oncol 2024; 58(2): 196-205. Ingenerf M et al./ Clinical and MR imaging at CAPTEM treatment in neuroendocrine tumors198 4. After a 15-minute delay, a fat-suppressed T1- weighted VIBE 3D GRE sequence identical to the earlier one. All sequences utilized parallel imaging with an acceleration factor of 2. ADC maps were computed from the acquired DWI-MR images, incorporating all b-values. TABLE 1. Patients characteristics Baseline N = 44 Follow-Up N = 33 Age (years) 60.4 (50.5; 70.2) Males 33 (75.0%) Time initial diagnosis – therapy start 685 (199; 1230) Clinical parameter Hepatic tumor burden (%) 10 (5 ;40) CgA (ng/ml) 610 (119; 2093) 647 (261; 2357) Bilirubin (mg/dl) 0.6 (0.4; 0.8) 0.7 (0.6; 0.9) Grading 1 1 (2.4%) 2 32 (76.2%) 3 6 (14.3%) NEC = 4 3 (7.1%) Ki-67 primary tumor (%) 15 (8;20) Localization primary tumor Pancreas 37 (84.1%) Lung 7 (15.9%) MRI parameter NELM Size (mm) 28 (19;36) 24.5 (18;38.5) T1 non-contrast/T1 liver 0.62 (0.53;0.68) 0.68 (0.56;0.75) T2/T2 liver 1.63 (1.16;2.07) 1.66 (1.21;2.17) ADCmin 448.5 (242.5;628.5) 549 (341;848) ADCmean 903 (708.5;1069.5) 969 (764;1250) ADCmin/ADCmin liver 0.80 (0.60;0.93) 0.85 (0.51;1.32) ADCmean/ADCmean liver 0.82 (0.74;0.96) 0.99 (0.65;1.32) % arterial vascularization 42.5 (15;80) 22.5 (5;74.5)** PNET Size (mm) 43 (32;70) 43 (29.5;52) T1 non-contrast /T1 pancreas 0.63 (0.59;0.76) 0.68 (0.61;0.84) T2/T2 pancreas 1.38 (0.85;1.67) 1.08 (0.83;1.34) ADCmin 604.5 (237;648) 628 (499.5;758.5) ADCmean 985 (810;1150) 1042.5 (939;1167) ADCmin/ADCmin pancreas 0.69 (0.41;1.11) 0.73 (0.58;0.85) ADCmean/ADCmean pancreas 1.01 (0.78;1.19) 0.89 (0.72;0.97) % arterial vascularization 15 (10;80) 7 (5;45) Data are given as median (25th and 75th percentile) or number (percentage); *p < 0.05; **p < 0.01; ***p < 0.001 from Wilcoxon signed-rank test; ADC = apparent diffusion coefficient; CgA = chromogranin A; d = days; NEC = neuroendocrine cancer; NELM = neuroendocrine liver metastasis; PNET = pancreatic neuroendocrine tumor Radiol Oncol 2024; 58(2): 196-205. Ingenerf M et al./ Clinical and MR imaging at CAPTEM treatment in neuroendocrine tumors 199 Image analysis Two board-certified radiologists, blinded to the patients’ clinical and follow-up data, reviewed all MRI data in consensus. They randomly identified, on the pretherapeutic MRI, two hepatic metasta- ses per patient that were larger than 1 cm in size, along with the primary tumor if it hadn’t been previously resected. Inclusion criteria for metas- tases encompassed a homogeneous appearance and absence of artifacts within the lesion across all sequences. The image review took place in two separate sessions, both achieving consensus: 1) pretherapeutic MRI, and for the sub-analysis 2) post-therapeutic MRI, with a three-week interval between each session. For quantitative analysis, the size of liver metas- tases and NETs were measured on the hepatobil- iary and arterial phases, respectively. ADCmean and ADCmin values of the tumorous lesions were calculated by manually placing circular regions- of-interest (ROIs) on the slice with the largest tu- mor extent on DWI, excluding structures near the rim to avoid partial volume effects. Signal inten- sity (SI) values on non-contrast T1-weighted and T2-weighted images were recorded by outlining ROIs of the lesions as large as possible. Percentage of arterial enhancement was visually assessed by the two radiologists in consensus. Additionally, ADC mean and ADC min values, as well as T2- weighted and T1-weighted SI values of the nor- mal liver, pancreas, and spleen, were measured by placing circular ROIs in tumor-free tissue areas. Additionally, SI of the normal liver was measured on the hepatobiliary phase. Tumor-to-organ ratios, including tumor-to-spleen (T/S) ratio and tumor- to-liver (T/L) ratio of SI and ADC, were calculated. Standard of reference and response to treatment Clinical and surgical records were compiled by a third radiologist. Histopathological confirmed di- agnoses of NET, along with their respective Ki-67 indices, were obtained for each patient. Tumor grad- ing adhered to the 2017 WHO Tumor Classification Guideline (G1: Ki-67 Index < 3%, G2: Ki-67 Index 3–20%, and G3 neuroendocrine tumor/neuroendo- crine cancer [NET/NEC]: Ki-67 Index > 20%). Given that the primary tumor was resected in 31 out of 44 patients, rendering RECIST 1.1. assessment of treatment response heterogeneous, evaluation of FIGURE 2. A 72-year-old man with liver metastasis of pancreatic NET classified as responder with a PFS of 38 months. The baseline axial contrast-enhanced T1- weighted image (hepatobiliary phase) (A) shows hypointense lesions (arrows) in segment 8 and exophytic in segment 1. The metastases show (B) restricted diffusion (arrows) with high signal on axial DW-MR image b = 800 s/mm2 and dark signal (arrows) on ADC map (C). After initiation of CAPTEM, the metastases (arrows) exhibited a decrease in size (D) On the axial DW-MR image b = 800 s/mm2, the metastasis (arrow) (E) demonstrated less hyperintense signal to liver and predominantly hyperintense signal (circle) on the ADC map (F) indicating less restricted diffusion compared to the pre- interventional image. ADC = apparent diffusion coefficient; CAPTEM = capecitabine and temozolomide; DW-MR = diffusion-weighted magnetic resonance; NET = neuroendocrine tumor; PFS = progression-free survival; PR =partial remission; TARE = transarterial radioembolization A B C D E F Radiol Oncol 2024; 58(2): 196-205. Ingenerf M et al./ Clinical and MR imaging at CAPTEM treatment in neuroendocrine tumors200 treatment response was conducted through PFS. This was measured in months from the initiation of CAPTEM until progression, as determined by the local interdisciplinary tumor board’s compre- hensive assessment of all performed imaging stud- ies (CT, PET/CT, MRI). Responders were defined by TABLE 2. Differences in baseline clinical and imaging tumor parameters between responder and non-responder Non-responder (< 6 months PFS) N = 23 Responder (≥ 6 months PFS) N = 21 p-value Age 57.8 (44.1;71.1) 61.7 (55.8;68.8) 0.953 Males 16 (69.6%) 17 (81.0%) 0.494 Time ID – Therapy start (d) 851 (426;1552) 396 (153;1004) 0.115 Clinical parameter Hepatic tumor burden (%) 5 (5;20) 20 (10;40) 0.007 CgA 592 (116;2031) 616 (156.5;2745) 0.706 Bilirubin 0.6 (0.4;0.8) 0.6 (0.3;0.9) 0.859 Grading 0.234 1 0 (0%) 1 (5%) 2 15 (68.2%) 17 (85%) 3 4 (18.2%) 2 (10%) NEC = 4 3 (13.6%) 0 (0%) Ki-67 primary tumor (%) 16.5 (10;30) 10.0 (5;15) 0.013 Localization primary tumor 0.232 Pancreas 21 (91.3%) 16 (76.2%) Lung 2 (8.7%) 5 (23.8%) MRI parameter NELM Size (mm) 25.5 (17;33.5) 29.8 (21.8;37.5) 0.348 T1 non-contrast/T1 liver 0.60 (0.53;0.68) 0.64 (0.54;0.74) 0.263 T2/T2 liver 1.62 (1.2;2.07) 1.69 (1.12;2.06) 0.903 ADCmin 506 (228;639) 424 (243;606) 0.827 ADCmean 852.5 (674;1059) 911 (790.5;1082.5) 0.495 ADCmin/ADCmin liver 0.80 (0.63;0.93) 0.74 (0.51;1.03) 0.846 ADCmean/ADCmean liver 0.82 (0.68;0.93) 0.86 (0.78;1.02) 0.342 % arterial vascularization 45 (15;85) 36.3 (15;72.5) 0.494 PNET Size (mm) 38 (30;44) 75.5 (65;85.5) 0.024 T1 non-contrast /T1 pancreas 0.60 (0.58;0.71) 0.71 (0.63;0.8) 0.258 T2/T2 pancreas 1.38 (0.84;1.67) 1.38 (1.11;1.5) 0.777 ADCmin 604.5 (237;648) 527 (316.5;698) 1.000 ADCmean 893 (789;1055) 1084 (996.5;1256) 0.157 ADCmin/ADCmin pancreas 0.79 (0.41;1.18) 0.63 (0.44;0.8) 0.480 ADCmean/ADCmean pancreas 1.09 (0.66;1.31) 0.97 (0.96;1.1) 0.888 % arterial vascularization 10 (5;70) 65 (30;85) 0.130 Data are given as median (25th and 75th percentile); p-values are from Wilcoxon rank-sum (Mann-Whitney) test or Fisher’s exact test; ADC = apparent diffusion coefficient; CgA = chromogranin A; NELM = neuroendocrine liver metastasis; PFS = progression-free survival; PNET = pancreatic neuroendocrine tumor Radiol Oncol 2024; 58(2): 196-205. Ingenerf M et al./ Clinical and MR imaging at CAPTEM treatment in neuroendocrine tumors 201 PFS ≥ 6 months, while non-responders (NR) were defined by PFS < 6 months, respectively. Statistical analysis Continuous data were summarized by median with interquartile range (IQR) and categorical data by numbers and percentages. Differences between baseline and follow-up parameters were assessed by Wilcoxon signed-rank test for paired samples. Differences of baseline characteristics and parameter changes until follow-up between non-responder and responder were investigated by Wilcoxon rank-sum test for unpaired samples or Fisher’s exact test. The area under the receiver operating characteristic (ROC) curve (AUC) was estimated according to logistic regression mod- els predicting non-responder by selected imaging and clinical parameters. Two AUC values were compared by chi2-test. Sensitivity, specificity, and the Youden-Index were calculated for median-di- chotomized parameters. Overall survival (OS) and PFS curves with median survival times were cal- culated by Kaplan-Meier analysis and compared by log rank-test between individuals separated by the median for selected parameters. Individuals were censored in case of death, progression or end of study. A p-value < 0.05 was considered to indi- cate statistical significance. All analyses were con- ducted with Stata 16.1 (Stata Corporation, College Station, TX, U.S.A.). Results Patients’ characteristics A total of 44 patients, comprising 86 neuroendo- crine liver metastases (NELM) and 14 primary pan- creatic NETs were included for the evaluation of prognostic factors for PFS. A subset of 33 patients, with corresponding 66 NELM and 12 pNETs, was identified for the sub-analysis of therapy monitor- ing. Baseline MRI scans were obtained 19d (IQR 1; 61) prior to CAPTEM initiation, and the time inter- val between baseline MRI and follow-up MRI was 130 days (IQR 113; 161). Most patients were male (75%), had G2 tumors (76%), and the primary tu- mor originated in the pancreas (84%). Detailed pa- tient characteristics are presented in Table 1. In the baseline cohort, the overall median PFS was 5.7 months (IQR 3.6; 15.0), and median OS was 25.0 months (interquartile range [IQR] 16.3; 45.3). Responder in the baseline group tended to have a slightly longer median OS 35.0 m (IQR 19.4; 53.4) A B C D E F G H FIGURE 3. A 56-year-old man with liver metastasis of pancreatic NET classified as nonresponder with a PFS of 3 months. The baseline axial contrast-enhanced T1- weighted image (hepatobiliary phase) (A) shows a hypointense lesion (arrow) in segment 4A. The metastasis shows a strong artrerial enhancement (B) and restricted diffusion (arrow) with high signal on axial DW-MR image b = 800 s/mm2 (C) and dark signal (arrow) on ADC map (D). After 3 months under CAPTEM, the metastasis (arrow) (E) exhibited an increase in size; however, it shows less arterial enhancement (F). On the axial DW-MR image b = 800 s/mm2, the metastasis (arrow) demonstrated hyperintense signal to liver and increasing hypointense signal on the ADC map indicating increasing restricted diffusion compared to the baseline image ADC, apparent diffusion coefficient. ADC = apparent diffusion coefficient; CAPTEM = capecitabine and temozolomide; DW-MR = diffusion-weighted magnetic resonance; NET = neuroendocrine tumor; PFS = progression-free survival Radiol Oncol 2024; 58(2): 196-205. Ingenerf M et al./ Clinical and MR imaging at CAPTEM treatment in neuroendocrine tumors202 compared to non-responders, with a median OS 21.4 month (IQR 15.0; 38.3). According to RECIST 1.1,21 patients were rated as stable disease (SD), 3 patients were rated as partial response, and 9 pa- tients were graded as progressive disease. When comparing baseline and follow-up pa- rameters, no differences were observed, except for arterial vascularization of NELM, which was sig- nificantly lower at follow-up time. Differences between non-responders (NR) and responders (R) at baseline The comparison of baseline clinical and imaging parameters between the two response groups re- vealed that NR had a significantly higher Ki-67 of the primary tumor (16.5% vs. 10.0%, p = 0.01) with three patients graded as neuroendocrine can- cer (NEC) in the NR group (none in the R group). Responders showed a significantly higher hepatic tumor burden (20% vs. 5%, p = 0.007). There were no differences in imaging parameters of the NELM, while for the pNETs size varied significantly be- tween response groups with greater diameters of the baseline pNET in R compared to NR (76 mm vs. 38 mm, p = 0.02). However, the statistical evalu- ation of pNET was limited by the small number of patients with non-resected pNET in our cohort (14 and 12 respectively). Differences of parameter change between non-responders (NR) and responders (R) After treatment initiation there was a significant difference in the change of chromogranin A (CgA) between response groups, with an increase in NR compared to a mild decrease in R (61% vs. -2%, p < 0.04). Regarding imaging parameters, there were significant differences in the changes of the size of both NELM (20% vs. -8%, p = 0.038) and pNET (2% vs. -55% p < 0.013) between the two response groups. Additionally, changes of ADC in NELM dif- fered significantly between response groups, with a decrease in both ADCmin (-23%) and the liver ad- justed ADCmean / ADCmean liver ratio (-16%) in NR, compared to an increase in R of both ADCmin (50%) and ADCmean / ADCmean liver (30%). Notably there were no differences in changes in arterial vascularization and signal intensity (SI) on T1w and T2w images between response groups. TABLE 3. Differences in change of clinical and imaging tumor parameters between responder and non-responder Change between baseline and follow-up (%) Non-responder (< 6 months PFS) N = 17 Responder (≥ 6 months PFS) N = 16 p-value Clinical parameter CgA 61.2 (-8.3;251.9) -1.5 (-69.3;19) 0.036 Bilirubin 0 (-20;40) 8.3 (-15.3;133.3) 0.312 MRI parameter NELM Size (mm) 20 (-4.7;50) -8.0 (-20.1;2.2) 0.038 T1 non-contrast/T1 liver 5.4 (-3.8;32.6) -6.8 (-13.6;11.2) 0.078 T2/T2 liver 1.6 (-9.2;24.1) -5.7 (-26.2;32.8) 0.589 ADCmin -22.8 (-41.1;40.2) 49.7 (-6.7;146.4) 0.037 ADCmean -3.5 (-18.4;14.1) 11.7 (-3.4;75.4) 0.056 ADCmin/ADCmin liver -32.3 (-46.2;70.8) 47.5 (12.7;251.7) 0.113 ADCmean/ADCmean liver -16.3 (-30.6;6.9) 30.0 (6.9;90.4) 0.011 % arterial vascularization -16.7 (-75;-5.9) -16.7 (-50.0;11.8) 0.298 PNET Size (mm) 2.3 (-5.4;20) -55 (-60;-17.8) 0.013 T1 non-contrast /T1 pancreas 7.4 (-3.8;36.7) -5 (-19.7;1.9) 0.116 T2/T2 pancreas -16.6 (-22;1.2) -36.1 (-40.3;-10.1) 0.229 ADCmin 14.4 (-13.7;260.8) 18.7 (-33.2;48.9) 0.782 ADCmean 8.3 (-4.5;29.3) 4.0 (-26.3;4.6) 0.405 ADCmin/ADCmin pancreas -3.6 (-29;76.6) 53 (-18.4;80.9) 0.518 ADCmean/ADCmean pancreas -23.2 (-35.5;4.5) -5.7 (-14.3;0.2) 0.518 % arterial vascularization -50 (-80;0) -50 (-80;0) 0.851 Data are given as median (25th and 75th percentile); p-values are from Wilcoxon rank-sum (Mann-Whitney) test; ADC = apparent diffusion coefficient; CgA = chromogranin A; NELM = neuroendocrine liver metastasis; PFS = progression-free survival; PNET = pancreatic neuroendocrine tumor Radiol Oncol 2024; 58(2): 196-205. Ingenerf M et al./ Clinical and MR imaging at CAPTEM treatment in neuroendocrine tumors 203 ROC and survival analysis of selected clinical and imaging parameters ROC analysis of the previously selected imaging and clinical parameters revealed AUC values dif- fering from 0.71 (∆ Size NELM and ∆ ADCmin) to 0.76 (∆ ADC mean/ Liver ADCmean) for classifying non-responders vs. responders. The highest AUC for a single parameter was found for ∆ ADC mean/ Liver ADCmean, with a median cut-off of < 6.9 which yielded a sensitivity of 76% and a specificity of 75%. The combination of ∆ Size NELM and ∆ CgA or ∆ ADC mean/ Liver ADCmean could each slightly, though not significantly, improve AUC (0.79 and 0.77 respectively), while the combination of ∆ Size NELM and ∆ ADCmin yielded the best balance for sensitivity and specificity with 88% and 60% compared to 69% and 65% respectively for ∆ Size NELM alone. Subsequent Kaplan-Meier survival analysis, utilizing the respective median cut-off values (Table 4 and Figure 4) for the param- eters, revealed significantly longer PFS times for ∆ ADCmean/ADCmean liver < 6.9 (p = 0.024) and the combination of ∆ Size NELM > 0% + ∆ ADCmin < -2.9% (p = 0.021). Discussion In this study, we explored the utility of clinical, morphological, and functional imaging param- eters in assessing the response and predicting out- comes in metastatic NETs treated with CAPTEM. Our results underscore the significance of mul- tiparametric MRI, in conjunction with established clinical factors, for evaluating therapy response. The median PFS in our baseline cohort was 5.7 months, which is on the lower end of the range of A B C D FIGURE 4. (A) Survival analysis for ∆ size of NELM with a cut-off of ≤ 0% for responder. This cut-off revealed a slightly longer median PFS time of 12.2 vs. 3.6 month (p = 0.062). (B) The median cut-off for ∆ ADCmean/ADCmean liver showed a significantly longer median PFS time of 15.3 compared to 4.1 month (p = 0.024). Both the combination of ∆ size of NELM > 0% and ∆ ADCmin < - 2.9% and the combination of ∆ size of NELM > 0% and ∆ CgA > 12.6% could differentiate patients with a longer median PFS time. Median PFS of the group with ∆ size of NELM > 0% and ∆ ADCmin < -2.9% was 3.6 m compared to 12 months (p = 0.021) in the group not fulfilling these criteria or a maximum of one criterion. Median PFS of the group with ∆ size of NELM > 0% and ∆ CgA > 12.6% was 3.6 m compared to 11.3 months (p = 0.072) in the group not fulfilling these criteria or a maximum of one criterium. ADC = apparent diffusion coefficient; CgA = chromogranin A; NELM = neuroendocrine liver metastasis; PFS = progression-free survival Radiol Oncol 2024; 58(2): 196-205. Ingenerf M et al./ Clinical and MR imaging at CAPTEM treatment in neuroendocrine tumors204 the review by Arrivi et al., which reported a me- dian PFS between 4 to 38.5 months.6 Discrepancies may be attributed to the predominance of GEP- NENs (GEP-NENs) in their study. Our median OS aligned well with Arrivi et al. report, at 25 months, compared to their range of 8 to 108 months. Disease control rate in our cohort was consistent with the literature, at 73% versus 77%.6 Comparison of baseline parameters between non-responders (NR) and responders (R) revealed higher Ki-67 levels (> 15%) in NR, contrasting with some studies suggesting improved response to CAPTEM in tumors with higher Ki-67.6,12 The ap- plicability of Ki-67 as a predictive/prognostic bio- marker for CAPTEM therapy in NETs remains con- troversial. Other authors suggested that there was no correlation between tumor grade, mitotic rate, or Ki-67 and tumor response to CAPTEM as the cytotoxic activity of temozolomide is not limited to mitosis but encompasses the entire cell cycle.7,13 Responders in our cohort exhibited a higher hepatic tumor burden at baseline, potentially in- dicating a better response in advanced disease stages. Follow-up analysis revealed marked CgA increases in non-responders versus mild decreases in responders. CgA is considered the most sensi- tive general marker for the diagnosis of NET14, and has been shown to be associated with survival and treatment response15-18 in follow-up, however opti- mal cut-offs remain controversial.19 Changes in size of metastases and primary tumors differed significantly between response groups, and ROC analysis showed an AUC for ∆size NELM of 0.71 with an optimal cut-off of > 0% to define non-response. Generally, we found that cut-offs for tumor progression (≥20%) or re- sponse (≥30%) according to RECIST 1.1 were barely reached in our cohort (median ∆size NELM for NR = 20%, and for R = -8%). Therefore, it is critical to adapt treatment response criteria to the rather slow evolution of most NETs to ameliorate man- agement of NET patients and design of clinical tri- als with better study end points.19 An effort to enhance therapy response assess- ment included the development of mRECIST cri- teria, initially proposed for hepatocellular carci- noma20 and now also proposed an alternative to RECIST for GEP-NETs.21 Despite well-developed capillary networks in NETs, and previous indica- tions of DCE-CT perfusion parameters predict- ing outcomes in NETs undergoing targeted thera- pies19,22, our study revealed a significant decrease in arterial vascularization in both NELM and pNETs after initiating CAPTEM treatment. However, no- tably, there was no discernible difference between responder and non-responder groups, challenging the utility of mRECIST in this context. Notably, our investigation revealed significant differences in ADCmin changes and the ratio of ADCmean divided by ADCmean of the liver be- tween response groups. ROC analysis demon- strated the highest AUC for ∆ADCmean/Liver ADCmean, with corresponding cut-offs effectively stratifying patients with longer PFS. Combining changes in tumor size (∆size NELM) with CgA or ADCmin showed slight improvements in sen- sitivities compared to size-based evaluation alone. Although no study has specifically analyzed the TABLE 4. ROC analysis of the previously selected imaging and clinical parameters AUC Cut-off(Median) Sensitivity (%) Specificity (%) Youden- Index Ki-67% 0.72 > 15 69 59 0.28 Hepatic tumor burden 0.73 < 10 84 72 0.56 ∆ CgA 0.73 > 12.6 67 64 0.31 ∆Size NELM 0.71 > 0 69 65 0.34 ∆ Size PNET - > -2.7 100 50 0.50 ∆ ADCmin 0.71 < -2.9 65 63 0.28 ∆ ADCmean/ADCmean liver 0.76 < 6.9 76 75 0.51 ∆ Size NELM+ ∆ CgA 0.79 > 0/> 12.6 78 60 0.38 ∆ Size NELM+ ∆ ADCmin 0.70 > 0/< -2.9 88 60 0.48 ∆ Size NELM+ ∆ ADCmean/ ADCmean liver 0.77 > 0/< 6.9 78 58 0.36 All p > 0.05; ADC = apparent diffusion coefficient; AUC = area under the curve; CgA = chromogranin A; NELM = neuroendocrine liver metastasis; PNET = pancreatic neuroendocrine tumor Radiol Oncol 2024; 58(2): 196-205. 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