Editorial
Copyright ©The Author(s) 2015. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Jun 14, 2015; 21(22): 6794-6808
Published online Jun 14, 2015. doi: 10.3748/wjg.v21.i22.6794
Prognostication and response assessment in liver and pancreatic tumors: The new imaging
Riccardo De Robertis, Paolo Tinazzi Martini, Emanuele Demozzi, Gino Puntel, Silvia Ortolani, Sara Cingarlini, Andrea Ruzzenente, Alfredo Guglielmi, Giampaolo Tortora, Claudio Bassi, Paolo Pederzoli, Mirko D’Onofrio
Riccardo De Robertis, Emanuele Demozzi, Gino Puntel, Mirko D’Onofrio, Department of Radiology, Verona Comprehensive Cancer Network, G.B. Rossi Hospital, University of Verona, 37134 Verona, Italy
Paolo Tinazzi Martini, Department of Radiology, Casa di Cura Pederzoli, 37019 Peschiera del Garda, Italy
Silvia Ortolani, Sara Cingarlini, Giampaolo Tortora, Department of Oncology, Verona Comprehensive Cancer Network, G.B. Rossi Hospital, University of Verona, 37134 Verona, Italy
Andrea Ruzzenente, Alfredo Guglielmi, Department of Hepato-Biliary Surgery, Verona Comprehensive Cancer Network, G.B. Rossi Hospital, University of Verona, 37134 Verona, Italy
Claudio Bassi, Department of Pancreatic Surgery, Verona Comprehensive Cancer Network, G.B. Rossi Hospital, University of Verona, 37134 Verona, Italy
Paolo Pederzoli, Department of Pancreatic Surgery, Casa di Cura Pederzoli, 37019 Peschiera del Garda, Italy
Author contributions: All authors contributed equally to this work; Tinazzi Martini P, Ruzzenente A, Guglielmi A, Cingarlini S, Tortora G, Bassi C, Pederzoli P and D’Onofrio M designed the research; Demozzi E, Puntel G and Ortolani S performed the research and analyzed the data; and De Robertis R, Demozzi E and Puntel G wrote the paper.
Conflict-of-interest: The authors declare no potential conflict of interest.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Riccardo De Robertis, MD, Department of Radiology, Verona Comprehensive Cancer Network, G.B. Rossi Hospital, University of Verona, Piazzale L.A. Scuro 10, 37134 Verona, Italy. riccardo.derobertis@hotmail.it
Telephone: +39-45-8124301 Fax: +39-45-8027490
Received: January 28, 2015
Peer-review started: January 28, 2015
First decision: March 10, 2015
Revised: March 25, 2015
Accepted: May 2, 2015
Article in press: May 4, 2015
Published online: June 14, 2015

Abstract

Diffusion-weighted imaging (DWI), dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and perfusion computed tomography (CT) are technical improvements of morphologic imaging that can evaluate functional properties of hepato-bilio-pancreatic tumors during conventional MRI or CT examinations. Nevertheless, the term “functional imaging” is commonly used to describe molecular imaging techniques, as positron emission tomography (PET) CT/MRI, which still represent the most widely used methods for the evaluation of functional properties of solid neoplasms; unlike PET or single photon emission computed tomography, functional imaging techniques applied to conventional MRI/CT examinations do not require the administration of radiolabeled drugs or specific equipments. Moreover, DWI and DCE-MRI can be performed during the same session, thus providing a comprehensive “one-step” morphological and functional evaluation of hepato-bilio-pancreatic tumors. Literature data reveal that functional imaging techniques could be proposed for the evaluation of these tumors before treatment, given that they may improve staging and predict prognosis or clinical outcome. Microscopic changes within neoplastic tissues induced by treatments can be detected and quantified with functional imaging, therefore these techniques could be used also for post-treatment assessment, even at an early stage. The aim of this editorial is to describe possible applications of new functional imaging techniques apart from molecular imaging to hepatic and pancreatic tumors through a review of up-to-date literature data, with a particular emphasis on pathological correlations, prognostic stratification and post-treatment monitoring.

Key Words: Diffusion magnetic resonance imaging, Perfusion imaging, Hepatocellular carcinoma, Liver neoplasms, Pancreatic neoplasms

Core tip: Diffusion-weighted imaging and perfusion imaging could add functional information to the morphological evaluation of hepatic and pancreatic tumors. Diffusion-weighted imaging findings seem to be correlated with pathological features and could predict the clinical outcome of hepatocellular carcinomas and pancreatic tumors, especially neuroendocrine neoplasms. Apparent diffusion coefficient quantification and perfusion techniques can be of value for the evaluation of response to ablative treatments, loco-regional therapies and anti-angiogenic therapies, even at an early stage.



INTRODUCTION

Functional imaging techniques include different methods that can detect or measure changes in metabolism, blood flow, and chemical composition. This group included both molecular imaging methods, as positron emission tomography (PET)-computed tomography (CT)/magnetic resonance imaging (MRI) or single photon emission computed tomography (SPECT), and radiological techniques, as diffusion-weighted imaging (DWI), dynamic contrast-enhanced MRI (DCE-MRI) and perfusion CT (pCT). Functional imaging techniques are technical improvements of conventional morphological techniques that can provide both qualitative and quantitative information on hepato-bilio-pancreatic tumors[1-3], being therefore similar to molecular imaging techniques. Functional techniques can be performed during conventional imaging evaluations as CT or MRI, therefore they describe both morphological and functional features of solid tumors; moreover, they do not need radiolabeled agents as fluorodeoxyglucose (18F-FDG) or specific equipments.

DWI evaluate the random diffusion of water molecules: biological tissues with high cellular density or altered cellular membranes will present diffusion restriction, which is depicted as signal hyperintensity areas on high b-value DW images and hypointensity on the apparent diffusion coefficient (ADC) maps; ADC measurement can also quantify water molecules’ diffusion. As dedifferentiation or therapies may induce microscopic changes in neoplastic tissues that could modify water molecules’ diffusion, DWI can distinguish between different degrees of malignancy and can be also proposed for post-treatment monitoring. Moreover, DWI can be performed in a single session with DCE-MRI, thus providing a comprehensive “one-step” morphological and functional evaluation of hepato-bilio-pancreatic tumors.

Perfusion imaging techniques evaluate changes in signal intensity (DCE-MRI) or density (pCT) after contrast medium injection, being therefore able to assess microvascularization through the evaluation of the dynamics of contrast medium distribution from vessels to the neoplastic tissue. Perfusion parameters are therefore theoretically good candidates for the evaluation of microscopic vascular differences between lesions with different pathological grade and for the assessment of treatment response, especially after chemoembolization or during treatments with anti-angiogenic drugs.

This editorial analyzes up-to-date literature data regarding the application of functional imaging techniques, apart from molecular imaging, to hepatic and pancreatic tumors, with particular emphasis on correlations to pathological features, prognostic stratification and therapeutic response assessment.

FUNCTIONAL IMAGING TECHNIQUES: TECHNICAL BASES

In 1965 Stejskal and Tanner[4] developed a modified T2-weighted MR sequence for the detection of water molecules’ diffusion. DWI enables the visualization of Brownian random motions of water molecules in the extracellular, intracellular, and intravascular spaces[5]. DWI provides information on tissue cellularity and integrity of cell membranes, since the degree of restriction to water diffusion in biological tissues is inversely correlated to these features[6-9]. Restricted diffusion is present in tissues with narrowed extracellular spaces as a consequence of a high cellular density, which increases the number of hydrophobic cellular membranes, whereas in cystic or necrotic lesions water diffusion is relatively ‘‘free’’[10]. The b value is a technical parameter that regulates the sensitivity of this sequence to water molecules’ diffusion. Generally, both low and high b values are used for DWI examination; nevertheless, the choice of the b value may vary from institution to institution. The intravoxel incoherent motion (IVIM) model is an advanced DWI technique developed by Le Bihan[11,12] that enables a separate quantitative assessment of all the microscopic translational motions that contribute to DWI signal. In biological tissues, these motions are represented by the molecular diffusion of water, expressed by diffusion (D) and pseudodiffusion (D*), and the perfusion effect caused by blood circulation in the capillary network (perfusion fraction - f). IVIM, therefore, can evaluate perfusion features without the need of contrast medium injection. Multiple b values must be used for IVIM evaluation.

DCE-MRI was developed to assess myocardial and pulmonary blood flow. This technique requires the intravenous injection of a gadolinium-based contrast agent, followed by rapid serial signal intensity measurements while the contrast agent enters tumor arterioles, passes through capillary beds and washes out of the tumor. Technical improvements have shortened the acquisition time and have led to the development of three-dimensional sequences, which replaced single-section examinations: as a consequence, DCE-MRI can be applied to abdominal imaging. The contrast kinetics features assessed by DCE-MRI reflect tissue perfusion, the concentration-time curve in the arterial input vessel, the capillary surface area, the permeability and the volume of the extracellular extravascular space. As a consequence, several metrics can be derived from DCE-MRI evaluation: the volume transfer constant (Ktrans), the fractional volume of the extravascular-extracellular space (ve), the rate constant (Kep, where Kep = Ktrans/ve), the fractional volume of the plasma space (vp), the area under the contrast agent concentration-time curve (AUC)[13]. In 1999, a consensus opinion agreed to standardize the terminology of DCE-MRI studies[13] and selected AUC60 and Ktrans as the preferred end points in clinical trials involving anti-angiogenic drugs[13,14]. Nevertheless, DCE-MRI end points can be tailored to the specific drug involved in the trial.

Perfusion CT has the same physical bases of DCE-MRI, as it is based on the evaluation of temporal changes in tissue density following intravenous administration of iodine contrast medium. By rapid sequential acquisitions during contrast medium passage, pCT allows the quantification of tissues’ vascularity. Perfusion can be quantified using mathematical modeling techniques (mainly the compartmental and the deconvolution analysis) that use data derived both from the tissue and the vascular system[15-17]. The analytical methods and the acquisition protocols vary from institution to institution and between commercial vendors, leading to poor standardization. Many different metrics can be directly or indirectly derived from pCT studies: blood flow (BF), representing the flow rate through vasculature; blood volume (BV), representing the volume of flowing blood; mean transit time (MTT), representing the average time taken to travel from arteries to veins; perfusion, representing the flow rate through vasculature; permeability surface (PS), representing the total flux from plasma to interstitial space; peak enhancement image (PEI), representing the maximum enhancement in a tissue region of interest; and time to peak (TTP), defined as the time from the arrival of the contrast medium in major arterial vessels to the peak enhancement). Other than poor standardization, another important drawback of pCT is the high radiation dose, even though technical improvements have recently led to the development of low-dose pCT examination protocols[18].

CORRELATION WITH PATHOLOGICAL FINDINGS AND PROGNOSTIC STRATIFICATION
Primary liver tumors

The prognosis and management of hepatocellular carcinoma (HCC) depend on size, degree of dedifferentiation, presence of vascular invasion and intrahepatic metastases[19]. As advanced and poorly differentiated HCCs have a significantly worse prognosis than well and moderately differentiated lesions after surgical resection[20], preoperative staging and prognostic prediction play an important role, eventually suggesting wider surgical clearance margins and closer post-treatment surveillance.

As the pathological grade of HCC depends on cellular and structural atypia[21], increasing cellular density, nuclear-to-cytoplasmic ratio, and architectural complexity accompanying dedifferentiation may cause water diffusion restriction. DWI features can be assessed both with a visual (qualitative) and a quantitative analysis through ADC measurement. An et al[22] reported a linear correlation towards higher grades in HCCs showing diffusion restriction: the combination of absence of diffusion restriction (defined as no hyperintensity on high b-value DW images) and no arterial enhancement at conventional contrast-enhanced MRI in predicting well differentiated HCCs had a 100% positive predictive value. The multistep nature of HCC dedifferentiation probably necessitates a quantitative approach rather than a simple visual analysis. Details on the main published studies regarding ADC measurement and correlations with the pathological grade of HCCs are reported in Table 1. Overall, literature data show that HCC dedifferentiation tends to be associated with a decrease of the ADC value, despite differences between studies[23-29]. Apart from the direct correlation with the pathological grade, Nakanishi et al[29] found that ADC quantification might have a clinical prognostic value, being significantly lower in patients with early recurrence after surgery than in those without early recurrence. One important aspect dealing with ADC measurement is the choice of the region of interest (ROI), given that a “whole-tumor” ROI can be irrespective of lesion heterogeneity: as previously mentioned, necrotic areas have a relatively free diffusion and should be avoided during ROI placement because they may falsely increase the ADC value; ADC measurement should be therefore performed only on solid areas showing diffusion restriction.

Table 1 Data derived from the main published studies that have tested correlations between apparent diffusion coefficient values and pathological grade of hepatocellular carcinomas.
StudyNumber of patientsb values(s/mm2)mean ADC value(× 10-3 mm2/s)
Nasu et al[23]990, 5001.45 (WD); 1.46 (MD); 1.36 (PD)
Piana et al[24]990, 5001.29 (WD); 1.22 (MD); 1.21 (PD)
Saito et al[25]32100, 8001.25 (WD); 1.12 (MD); 1.13 (PD)
Muhi et al[26]73500, 8000.91 (WD); 0.71 (MD); 0.68 (PD)
Nishie et al[27]800, 500, 10001.21 (WD); 1.14 (MD); 0.76 (PD)
Heo et al[28]270, 10001.20 (WD); 1.10 (MD); 0.90 (PD)
Nakanishi et al[29]440, 50, 10001.29 (MD); 1.07 (PD)

Studies regarding IVIM imaging reported interesting results. Woo et al[30] found that the D value (diffusion) quantification had significantly higher AUC than ADC measurement for the differentiation between high-grade and low-grade HCCs. Moreover, the percentage of arterial enhancement depicted at conventional contrast-enhanced MRI, which is directly linked to the degree of dedifferentiation of HCCs, was correlated with IVIM-derived f value (perfusion fraction).

As previously mentioned, the prognosis of patients with HCC depends also on other pathological features: DWI has been tested for the detection of malignant features of HCC, as vascular involvement or intrahepatic metastases. It has been reported that ADC measurement has a high sensitivity and specificity (reaching up to 93.5% and 78.6%, respectively) for the prediction of microvascular involvement[31,32]. Portal vein involvement precludes most curative options[33], but its diagnosis may be hampered by the presence of a non-neoplastic thrombus in a cirrhotic liver. Few and controversial papers have been published regarding the ability of DWI in distinguishing malignant from non-malignant thrombi: Catalano et al[34] reported that most neoplastic thrombi were isointense to the primary tumor on DWI, whereas all bland thrombi were hypointense; it must be noted that blood degradation products present variable T2 signal prolongation and water diffusivity, therefore false-positives may be encountered at DWI[35]. Satellite nodules are important determinants of patients’ prognosis and influence the therapeutic approach. The high accuracy of DWI in detecting small HCCs, even smaller than 1 cm, may be assumed to be applicable to intrahepatic HCC metastases[36].

Arterial blood supply tends to increase during hepatocarcinogenesis. Perfusion imaging techniques would be ideal for the prediction of the pathological grade and clinical behavior of HCCs, but literature data at this regard are relatively poor. One single study[37] reported a significant negative correlation between the standardized uptake value (SUV) derived from 18F-FDG PET/CT and Ktrans in advanced HCCs. Some more studies have been conducted with pCT: while Ippolito et al[38] did not report any significant correlation between pCT-derived parameters and pathological grade, Sahani et al[39] found that well-differentiated HCCs had significantly higher perfusion values than less differentiated lesions. Yang et al[40] reported that pCT could quantitatively assess the blood supply and particularly its distribution during hepatocarcinogenesis, with statistically significant correlations between BF, hepatic arterial perfusion (HAP) and microvascular density (MVD).

Few experiences, mainly focused to a qualitative visual assessment of DW images, have been reported regarding cholangiocarcinoma (CCC). Cui et al[41] found an inverse correlation between the pathological grade and ADC values; Park et al[42] reported that the addition of DWI to conventional sequences might improve the pre-operative assessment of hilar CCC, increasing the sensitivity for the evaluation of tumor extent along the bile ducts and liver invasion, thus improving T stage, a parameter that is directly related to prognosis.

Pancreatic tumors

Although the prognosis of patients with pancreatic ductal adenocarcinomas (PDACs) is related to the pathological grade, treatment choice mainly relies on clinical stage. Surgical resection is the only curative treatment for this neoplasm, therefore the pre-operative prediction of the pathological grade may have a smaller importance for PDAC management as compared to other pancreatic tumors.

Some studies have tried to correlate DWI findings with the pathological grade, but results are controversial[43-45]. Details on the most relevant published studies are reported in Table 2. Overall, low-grade PDACs tend to present low ADC values[43-45], but it still not clear which histological feature mainly contributes to diffusion restriction. Wang et al[43] and Muraoka et al[46] reported that tumors with limited glandular formation and dense fibrosis (i.e., paucicellular tumors) had lower ADC values as compared to well-differentiated lesions characterized by neoplastic tubular structures; moreover, PDACs with dense fibrosis showed significantly lower ADC values than those with loose fibrosis. Fibrosis may be therefore the key factor contributing to diffusion restriction in PDACs, but these findings have not been confirmed by other studies: particularly, Klauss et al[47] reported that the difference between the IVIM-derived D value (diffusion) of moderate and severe fibrosis PDACs was significant, but the cellular complexes surrounded by fibrosis might provide more structural limitations than fibrosis alone. Legrand et al[44] reported that mean ADC values did not significantly differ between tumors having < 50% and those having > 50% of fibrotic stroma, or between tumors containing dense fibrosis and those containing loose fibrosis. Similarly, Rosenkrantz et al[45] reported no associations between ADC values and “adverse” pathological features as poor differentiation. Some authors have proposed a more practical role for functional imaging, testing correlations with clinical features as tumor stage or survival. Hayano et al[48] reported a significant negative correlation between ADC values, size and number of metastatic lymphnodes; PDACs with low ADC values presented also a high tendency to show portal system and extra-pancreatic nerve plexus invasion. The comparison of CT and DWI performed by Fukukura et al[49], instead, reported that only CT findings might be associated with the clinical behavior of PDACs. Some studies focused on the application of DWI to the detection and characterization of liver metastases from PDAC and reported high sensitivity and specificity using DWI alone[50] or DWI plus other sequences[51-53]: imaging features derived from conventional MR sequences should be always taken into account because of the possible presence of DWI false-positives.

Table 2 Data derived from the main published studies that have correlated apparent diffusion coefficient quantification with the pathological grade of pancreatic ductal adenocarcinomas and neuroendocrine tumors.
Studynb values(s/mm2)Histotypemean ADC value(× 10-3 mm2/s)
Wang et al[43]210, 500PDAC2.10 (WD-MD); 1.46 (PD)
Legrand et al[44]22Multiple1PDAC1.43 (WD); 1.94 (MD-PD)
Rosenkrantz et al[45]300, 500PDAC1.78/1.75 (WD-MD); 1.69/1.62 (PD)2
Wang et al[58]180, 50, 500PanNET1.75 (G1); 1.00 (G3)
Jang et al[59]200, 800PanNET1.48 (G1-G2); 1.04 (G3)
Hwang et al[60]44Multiple3PanNET1.31 (G1); 1.08 (G2-G3)

Well-differentiated PDACs have a higher microvascular density as compared to less differentiated tumors[54]; perfusion imaging should therefore theoretically be able to identify well-differentiated PDACs, which have better prognosis than poorly differentiated lesions. It has been reported that pCT-derived PEI and BV values could identify high grade PDACs with 100% specificity and 75% accuracy[55]. Ueno et al[56] reported that DCE-MRI might predict the survival of patients with advanced PDAC: all patients included in this study showed transient decreases in signal intensity [signal ratio (SR): 6.9%-55.7%]; high SR (cut-off 22%) significantly correlated with higher disease stage and presence of nodal metastases; patients with high SR had significantly short overall survival.

Pancreatic neuroendocrine tumors (PanNETs) can be divided into well/moderately differentiated and poorly differentiated lesions and their mitotic rate based on the quantification of the mitotic index (Ki67%) can distinguish three categories: G1, with a Ki67 ≤ 2%, G2 (Ki67 3%-20%), and G3 (Ki67 > 20%)[57]. Several treatment options, ranging from surgery to systemic therapy or loco-regional treatments, have been proposed for PanNETs according to their grade of differentiation. The histological grade plays therefore a key role in the clinical management of PanNETs; many studies have been conducted regarding the application of functional imaging techniques to PanNETs, apart from nuclear imaging techniques. Details regarding ADC measurements correlations with the grade of differentiation are reported in Table 2. Overall, it seems that ADC values are correlated with the Ki67 labeling index: G3 PanNETs tend to present lower mean ADC values compared to well-differentiated PanNETs[58-60]. As for PDACs, staging plays a fundamental for treatment planning and prognostication of PanNETs. In most cases, liver metastases from PanNETs are hypervascular; nevertheless, in some cases they can be iso- or hypovascular and therefore difficult to detect and correctly characterize using conventional imaging techniques. Moreover, heterogeneity of liver metastases has been reported[61]. DWI is a good functional technique for the detection of PanNET liver metastases, with 71% sensitivity and 85%-100% specificity, equal or even higher than T2-weighted and contrast-enhanced images[62,63]. In a study that evaluated the role of DWI in the differentiation of hemangiomas from other hypervascular liver lesions, the mean ADC value of NETs metastases was found to be 1.43 × 10-3± 0.39 × 10-3 mm2/s[64], slightly higher than that reported by Schmid-Tannwald (1.23 × 10-3± 0.31 × 10-3 mm2/s)[65]. Nevertheless, MR features derived from conventional sequences should be always taken into account, due to a wide overlap in ADC values among different liver lesions. DWI can also obtain images from the entire body in one single acquisition (whole-body diffusion-weighted imaging - WBDWI). Cossetti et al[66] reported two cases of NETs with distant metastases (bone and mediastinal lymphnodes) discovered by WBDWI and confirmed by Octreoscan. Etchebehere et al[67] compared WBDWI with 68Ga-DOTATATE PET-CT and 99mTc-HYNIC-Octreotide SPECT-CT: WBDWI had a similar accuracy when compared to molecular imaging techniques for lung and liver lesions, while showed a higher false-negative rate for bone lesions. Schraml et al[68] reported that PET-CT and WBDWI had comparable overall detection rates for NETs metastases but significantly differed in organ-based detection rates with superiority of PET-CT for lymph node and pulmonary lesions and of WBDWI for liver and bone metastases.

Experimental applications of pCT to PanNETs reported interesting results. Rodallec et al[69] and D’Assignies et al[70] reported that pCT features were correlated with MVD; moreover, BF values of benign PanNETs were higher than those of uncertain behavior tumors and carcinomas, and significant correlations were reported between BF, MTT and proliferation index, microscopic vascular neoplastic involvement and presence of nodal or liver metastases. Regarding staging, Ng et al[71] reported that BF and hepatic arterial fraction were significantly higher in liver metastases from PanNETs than in healthy liver, thus reflecting an increased arterial blood supply to metastatic lesions; opposite relationships were found for MTT and PS. Guyennon et al[72] reported that pCT could provide additional information in respect to conventional CT; particularly, despite both hypervascular and hypovascular metastases presented higher hepatic arterial perfusion index as compared to the background liver, mean BF and BV values were higher in hyperdense metastases compared with hypodense lesions. All liver metastases showed higher BF, BV, PS and hepatic arterial perfusion index as compared to the background liver.

Functional parameters derived from pCT may therefore be useful for the characterization of suspect PanNET liver metastases when they present atypical morphological features, as hypovascularity.

Well- and poorly-differentiated PanNETs present different DCE-MRI features. Bali et al[73] reported that a signal intensity - time curve similar to that of the aorta was typical of well-differentiated PanNETs, while a curve characterized by a slow enhancement was present in non well-differentiated PanNETs, but also in PDACs. Moreover, a positive correlation was observed between the MVD and the distribution factor, which reflects the volume fraction of the tissue that is accessible to the contrast agent (i.e., the plasma and the extravascular extracellular space). Kim et al[74] found a significant difference in the perfusion characteristics of well-differentiated PanNETs and neuroendocrine carcinomas: Ktrans values, representing tissue blood flow, were significantly lower in G3 tumors. Interestingly, the mean Ktrans of neuroendocrine carcinomas was higher than that of PDACs, thus reflecting the true histological features of PanNETs: even if poorly differentiated, they present higher MVD as compared to PDACs.

DCE-MRI has been tested for PanNETs staging. Koh et al[75] found three different patterns of contrast enhancement for neuroendocrine hepatic metastases, with specific perfusional parameters. DCE-MRI is therefore potentially able to categorize metastases on the basis of their vascular characteristics, with prognostic and therapeutic consequences. Armbruster et al[76] reported that arterial flow fraction and intracellular uptake fraction have a high diagnostic accuracy for the distinction between NET liver metastases and normal hepatic tissue. DCE-MRI parameters are also partially correlated to SUVs derived from 18F-FDG- and 68Ga-DOTA-Tyr(3)-octreotate (68Ga-DOTATATE-) PET/CT[77].

RESPONSE TO TREATMENTS
Primary liver tumors

Loco-regional therapies as percutaneous or intra-operative ablation techniques [radiofrequency ablation (RFA), microwaves, irreversible electroporation or transarterial chemoembolization (TACE) and radioembolization (TARE)], have significantly contributed to the control of unresectable localized HCCs[78]. As these therapies may be repeated and interchangeably applied, early assessment of treatment response is crucial. Response Evaluation Criteria In Solid Tumors (RECIST) criteria are not applicable to HCC, as both loco-regional treatments and systemic therapy generally result in tumor necrosis rather than shrinkage. The European Association for the Study of Liver Diseases has proposed to assess response to loco-regional treatments by assessing the decrease in viable tumor volume, seen as a decrease in contrast-enhancing areas at conventional contrast-enhanced CT/MRI[79]. However, the differentiation of viable tissue from treatment-induced changes as inflammation or granulation tissue can be difficult, as these non-tumoral changes can present contrast enhancement[80,81]. DWI and perfusion imaging techniques may have a potential role in the differentiation of viable tumor from treatment-induced necrosis. Viable neoplastic areas present high cellularity with intact cell membranes and show high vascularization; conversely, treatment-induced necrotic and inflammatory changes present a reduced cellular density, an increased membrane permeability and poor vascularization.

Radiofrequency ablation (RFA) induces coagulative necrosis in tumor tissues. Lu et al[82] reported that the ADC values of HCCs successfully treated with RFA showed a predictable evolution and might help radiologists to monitor tumor response, being significantly high starting from 1 mo after RFA. Ippolito et al[83] reported that pCT enabled the assessment of HCC vascularity after RFA, providing quantitative information about the presence of arterial vessels within viable residual neoplastic tissues: in this study, a significant difference in perfusion, arterial perfusion (AP), and hepatic perfusion index (HPI) values was found between treated lesions with residual tumor and those successfully treated. Eccles et al[84] reported statistically significant changes in ADC values of HCCs treated with radiotherapy (RT): in their study, the baseline median ADC of 1.56 × 10-3 mm2/s increased to 1.89 × 10-3 mm2/s at RT week one, to 1.91 × 10-3 mm2/s during week two and to 2.01 × 10-3 mm2/s one month following treatment; early increases of ADC values were correlated with sustained tumor response. Kim et al[85] reported that ADC values and DCE-MRI parameters acquired before concurrent chemoradiotherapy correlated with progression-free survival (PFS) and were valuable in the prediction of the clinical outcome. The best cutoff values for response prediction of ADC, Ktrans, Kep, and extravascular extracellular volume fraction (ve) were 1.008 × 10-3 mm2/s, 0.108 /min, 0.570 min-1, and 0.298%, respectively.

Many studies have been conducted on the application of functional imaging techniques for HCCs treated with TACE and TARE; the most significant results are reported in Table 3. Overall, ADC values tend to increase after TACE, even at an early evaluation[86-89]. DWI can reliably assess the efficacy of trans-arterial treatments: Yuan et al[90] reported differences in the mean ADC values of the necrotic and vital tumor tissues after TACE (2.22 × 10-3± 0.31 × 10-3 mm2/s and 1.42 × 10-3± 0.25 × 10-3 mm2/s, respectively); a significant linear correlation was identified between the ADC value of the entire area of the treated mass and the extent of tumor necrosis (r = 0.58; P < 0.001). Mannelli et al[91] did not report differences between conventional MRI sequences and DWI for the assessment of post-TACE necrosis, although enhancement decrease on MRI subtraction images was more significantly correlated with pathological findings than ADC increase. Although quantitative analysis of diffusion restriction appears to be of value in assessing response to TACE, visual analysis seems to be less accurate: Goshima et al[92] reported that DW images were significantly less sensitive than contrast-enhanced images in detecting residual/recurrent tumor after TACE, and Yu et al[93] reported that the addition of DW images to contrast-enhanced images reduced specificity and diagnostic accuracy in detecting perilesional recurrence. Probably, the presence of treatment-induced granulation tissue is the cause of DWI false positives.

Table 3 Data derived from the main published studies that have evaluated apparent diffusion coefficient values before and after trans-arterial treatments of primary and metastatic liver tumors.
Studynb values (s/mm2)ADC before treatment(× 10-3 mm2/s)ADC after treatment(× 10-3 mm2/s)HistotypeTreatment
Kamel et al[86]380, 5001.511.70HCCTACE
Sahin et al[87]740, 50, 400, 8001.101.27HCCTACE
Kamel et al[88]240, 50, 7501.862.13HCCTACE
Chen et al[89]200, 5001.562.09HCCTACE
Yuan et al[90]410, 5002.221.42HCCTACE
Deng et al[98]60, 5001.302.23HCCTARE
Kamel et al[99]130, 5001.651.95HCCTARE
Rhee et al[100]200, 5001.641.82HCCTARE
Mannelli et al[102]360, 50, 5001.641.92HCCTACE
Kubota et al[103]250, 5001.2711.3571/1.2222HCCTACE
Liapi et al[120]260, 5001.511.79Metastases (PanNET)TACE
Li et al[121]260, 7501.311.59Metastases (PanNET)TACE

Regarding pCT, Yang et al[94] reported a significant decrease of the HAP, total liver perfusion (TLP), and hepatic arterial perfusion index (HAPI) values 4 wk after TACE.

Braren et al[95] reported strong correlation between the extravascular extracellular volume fraction assessed with DCE-MRI and the percentage of residual tumor after TACE. Taouli et al[96] reported that untreated HCCs had higher arterial fraction and lower portal/venous hepatic blood flow values than chemoembolized HCCs.

Trans-arterial yttrium-90 (90Y) radioembolization (TARE) aims to deliver a high radiation dose to HCCs[97]. Although a small study reported a 60% increase in the mean ADC value after TARE[98], other studies reported less conspicuous ADC increases (approximately 10%-20%)[99]. Rhee et al[100] reported that 1-mo response to TARE assessed with DWI significantly preceded size changes: the mean baseline ADC value (1.64 × 10-3± 0.30 × 10-3 mm2/s) increased to 1.81 × 10-3± 0.37 × 10-3 mm2/s at 1 mo (P < 0.05), and to 1.82 × 10-3± 0.23 × 10-3 mm2/s at 3 mo (P < 0.05), while the mean tumor size did not significantly modify at 1 or 3 mo. Functional imaging techniques may be helpful for response prediction to trans-arterial treatments. Park et al[101] reported that IVIM imaging could predict lipiodol uptake: the D* (pseudodiffusion) value was significantly higher in a “lipiodol-good uptake” HCC group than in a “lipiodol-poor uptake” group. Mannelli et al[102] reported that ADC quantification could predict response to TACE: HCCs with poor/incomplete response (< 50% necrosis) had significantly lower pre- and post-TACE ADC values than lesions with good/complete response. Kubota et al[103] reported that the percent ADC value modification after therapy was significantly higher in non-relapsed HCCs (85.2% ± 12.4%) as compared to lesions with disease relapse (8.0% ± 56.7%, P < 0.001). Konstantinidis et al[104] reported that DCE-MRI could predict treatment outcome after hepatic arterial infusion (HAI) of floxuridine and dexamethasone (with or without bevacizumab) in advanced intra-hepatic CCCs: AUC90 and AUC180 were significantly higher in ≥ 3-year survivors than < 3-year survivors.

The advent of anti-angiogenic therapies, including sorafenib and bevacizumab, greatly expanded treatment options for HCCs. As anti-angiogenic drugs frequently do not induce tumor shrinkage but acts on tumor vascularization, functional imaging techniques may be suitable for the evaluation of patients treated with these agents. Details regarding the most relevant studies on treatment assessment by means of functional radiological techniques are reported in Table 4.

Table 4 Data derived from the main published studies that have correlated functional radiological techniques with response to systemic therapies of hepatic and pancreatic tumors.
StudynTechniqueImaging biomarkerHistotypeTreatment
Lewin et al[107]12IVIMf increaseHCCsorafenib
Vouche et al[108]15DWIADC increaseHCC90Y TARE ± sorafenib
Hsu et al[109]31DCE-MRIKtrans decreaseHCCsorafenib+metronomic tegafur/uracil
Yopp et al[111]17DCE-MRIAUC90/AUC180/Ktrans decreaseHCCbevacizumab
Jiang et al[112]23pCTBF/BV/PS decreaseHCCbevacizumab + cytotoxic agents
MTT increase
Kim et al[113]10DCE-MRI/DWIKtrans/Kep decreaseHCCsunitinib
ADC increase
Sahani et al[114]23DCE-MRI/DWIKtrans/Kep decreaseHCCsunitinib
ADC increase
Kim et al[123]35pCTBF decreaseCRC metastasesXELOX, FOLFOX, FOLFIRI
Schlemmer et al[124]24pCTPerfusion decreasePanNET metastasesTyrosine-kinase inhibitors
Anzidei et al[125]18pCT, DWICP decreaseCRC metastasesOxaliplatinum, capecitabine, bevacizumab
ADC increase
De Bruyne et al[127]19DCE-MRIAUC decreaseCRC metastasesBevacizumab
Vriens et al[129]23DCE-MRIKtrans decreaseCRC metastasesCytotoxic therapy
Coenegrachts et al[130]10DCE-MRIKep increaseCRC metastasesBevacizumab + FOLFIRI
Deckers et al[126]20DWIADC decreaseCRC metastasesChemotherapy
Niwa et al[133]63DWIADC decreasePDACGemcitabine
Cuneo et al[134]12DWIADC increasePDACChemoradiation
Yao et al[135]39pCTBF decreasePanNETBevacizumab ± everolimus
Miyazaki et al[132]20DCE-MRIDistribution volume increasePanNET metastases90Y-octretotide

Sorafenib, an oral multikinase inhibitor that suppresses tumor cell proliferation and angiogenesis, is so far the only drug that has shown overall survival benefit in patients with advanced HCC[105] and represents the standard systemic therapy for patients with advanced (unresectable and/or metastatic) HCCs with well-preserved liver function and for intermediate-stage HCCs with disease progression after local treatments[106]. As sorafenib inhibits neovascularization and decreases tumor vascularity, perfusion parameters should decrease in responding patients. Nevertheless, literature data are controversial. Lewin et al[107] reported a significant f (perfusion fraction) increase in responders at 2 wk and at 2 mo of sorafenib therapy, whereas a decrease was noted in non-responders at the same time intervals. Vouche et al[108] reported that ADC values did not change 1 and 3 mo after 90Y TARE or 90Y TARE plus sorafenib treatments. These results may be explained by the pleiotropic anti-angiogenic actions of sorafenib, which destroys tumor vessels and improves the integrity of basement membranes of the remaining microvessels, thus leading to less “water leakage” from the perfusion pool. Modifications during sorafenib treatment can be assessed also using perfusion-imaging techniques. Hsu et al[109] found good correlations between Ktrans values and survival in patients who received sorafenib plus metronomic tegafur/uracil therapy: baseline Ktrans was higher in patients with RECIST partial response (PR) or stable disease (SD) than in those with progressive disease (PD). Frampas et al[110] reported a non-significant decrease in all pCT-derived values between RECIST non-progressors and progressors treated with sorafenib.

Although not routinely used in clinical practice, other anti-angiogenic therapies are on study for HCCs, including bevacizumab (a monoclonal antibody directed against vascular endothelial growth factor - VEGF) and sunitinib (an oral multikinase inhibitor with VEGF-receptor as one of its targets). Yopp et al[111] reported a significant decrease of AUC90, AUC180, and Ktrans in HCCs treated with bevacizumab; time to progression inversely correlated with AUC90 and AUC180 changes (P < 0.05 and P < 0.001). In one study focused on locally advanced HCCs receiving bevacizumab and cytotoxic therapy, high pretreatment Ktrans identified patients with RECIST response to therapy[112]. Sunitinib seems to induce Ktrans and Kep decrease and ADC increase[113,114]; these modifications can be assessed even at a very early stage (after 2 wk of treatment). Moreover, patients with larger Ktrans and Kep decrease might have a favorable clinical outcome; high baseline Ktrans and large decreases of the extracellular volume fraction were correlated with longer PFS. No significant changes at DCE-MRI have been reported after vandetanib treatment[115,116].

Liver metastases

Lu et al[82] reported that metastatic liver lesions successfully treated by RFA showed a predictable evolution of ADC values, with an up-and-down variation during follow-up. Szurowska et al[117] reported that low pre-treatment ADC values could predict complete response of colorectal adenocarcinoma (CRC) liver metastases treated with RFA. Meijerink et al[118] reported that pCT-derived BF distribution fully paralleled PET/CT images in showing either the absence or presence of local recurrence after RFA: high hepatic arterial perfusion (> 50 mL/min per 100 g) and low portal venous perfusion (< 10 mL/min per 100 g) areas represented viable neoplastic tissue. Marugami et al[119] reported that ADC quantification might be helpful for the early detection of response in CRC liver metastases treated with HAI chemotherapy with 5-fluorouracil: ADC increase was significantly greater in responders than in non-responders.

Chemoembolization induces an increase of ADC values in PanNET liver metastases[120-122]; response to TACE can be assessed even at an early stage, starting from three weeks after treatment[122]. Details on the main published studies regarding functional imaging applications after trans-arterial treatments are reported in Table 3. Functional radiological techniques have been tested for follow-up evaluations during systemic treatment of liver metastases; details are reported in Table 4. Kim et al[123] reported that pCT-derived BF and flow extraction product (FEP) could be used as early response predictors in patients with liver metastases from CRC, being both significantly different between responders and non-responders to XELOX, FOLFOX or FOLFIRI chemotherapy regimens.

Schlemmer et al[124] reported that metastatic NETs with good response to tyrosine kinase inhibitors showed a significant tendency towards lower perfusion values assessed by pCT as compared to poor responders. Anzidei et al[125] reported that both pCT and DWI could detect therapy-induced (oxaliplatinum, capecitabine and bevacizumab) modifications in CRC liver metastases vascularization before significant size changes became evident: capillary permeability was significantly higher in lesions with complete and partial response; moreover, ADC values were significantly higher in partial response lesions than in patients with stable disease. Deckers et al[126] reported that the increase of ADC values in responding liver metastases could occur even within days after the start of chemotherapy; unfortunately, as these changes were of smaller magnitude than the variability of ADC measurement, ADC quantification was not reliable enough to predict final response at such an early time point in individual lesions.

Many studies have been conducted with DCE-MRI, probably as a consequence of the standardization of DCE-MRI-derived endpoints. De Bruyne et al[127] reported that bevacizumab therapy could decrease DCE-MRI-derived AUC in patients with CRC liver metastases. Vriens et al[128] reported a large reduction in DCE-MRI-derived perfusion parameters and glucose metabolic rate at 18F-FDG PET/CT in CRC metastases treated with bevacizumab. The same author[129] reported also that cytotoxic chemotherapy did not alter DCE-MRI-derived properties of tumor vasculature. Coenegrachts et al[130] reported that a decrease of Kep allowed early identification of response after 6 wk of FOLFIRI and bevacizumab treatment. O’Connor et al[131] reported that the variance of CRC liver metastases shrinkage after bevacizumab and FOLFOX-6 treatment was mainly explained by the median values of ve, tumor enhancing fraction (EF), and microvascular uniformity. Miyazaki et al[132] reported that DCE-MRI-derived liver distribution volume and tumor distribution volume were significantly increased in liver metastases with good response to radiolabeled octreotide; low pretreatment values of liver distribution volume and high tumor arterial flow fraction were associated with better response.

Pancreatic tumors

DWI has been tested for treatment response evaluation of pancreatic tumors: therapy seems to increase ADC values. Niwa et al[133] reported ADC differences among patients with advanced pancreatic cancer treated with gemcitabine: in particular, significant differences between patients with progressive disease and those with stable disease were found at 3- and 6-mo follow-up. Tumor progression rate was significantly higher in patients with low ADC values than in those with higher values. Cuneo et al[134] reported a significant correlation between pre-treatment mean ADC values of surgically resected PDACs and the amount of tumor cell destruction after chemoradiation evaluated on surgical specimens, with a Pearson correlation coefficient of 0.94 (P = 0.001): the mean pre-treatment ADC value was 1.61 × 10-3 mm2/s in responding patients (> 90% tumor cell destruction) compared to 1.25 × 10-3 mm2/s in non-responding patients (> 10% viable tumor).

Regarding PanNETs, Yao et al[135] reported that bevacizumab was associated with a 44% decrease in BF in patients with low-to intermediate grade tumors; the addition of everolimus induced a further 29% BF decrease. Everolimus alone was associated with 13% increase in MTT. Pretreatment PS (P = 0.009), post-treatment MTT (P = 0.003), percent reduction in BF (P = 0.03), and percent reduction in BV (P = 0.002) were associated with high percent reduction in tumor diameters. Such perfusion changes occurred early after treatment start and might be used as functional biomarkers of response to bevacizumab or everolimus treatment.

CONCLUSION

Literature data reveal that DWI can provide prognostic stratification of HCCs and PDACs, as DWI findings may reflect “adverse” pathological features associated with poor clinical outcome and prognosis. ADC values are generally low in poorly differentiated lesions, although different results have been reported regarding the direct correlation of ADC values and the pathological grade. Perfusion imaging techniques can theoretically depict microvascular changes related to dedifferentiation of HCCs and PDACs, but poor and controversial results have been reported.

Overall, it seems that functional radiological techniques find their most important applications in PanNETs: both DWI and perfusion imaging methods provide indirect information on their clinical behavior and improve their staging.

Functional imaging techniques can predict treatment outcome and assess response of primary and metastatic hepatic tumors to loco-regional therapies, particularly TACE: ADC increase seems to be associated with good clinical outcome.

Perfusion imaging can be of value in the post-treatment assessment of patients treated with tyrosine kinases inhibitors: DCE-MRI and pCT can distinguish responders from non-responders using DCE-imaging.

Functional radiological techniques are therefore reliable and useful to evaluate patients with hepatic and pancreatic tumors; these “new imaging” techniques could be therefore considered and -whenever possible- adopted as a part of CT/MRI examination protocols.

Footnotes

P- Reviewer: Ji Y, Lim SM, Sun XJ S- Editor: Qi Y L- Editor: A E- Editor: Ma S

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