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Università degli Studi di Pisa
Scuola di Specializzazione in Medicina Nucleare
Direttore: Prof. Duccio Volterrani
Dipartimento di Ricerca Traslazionale e delle Nuove Tecnologie in
Medicina e Chirurgia
Tesi di Specializzazione
[
18F]FDG-PET/CT in patients with Radioiodine-Refractory Thyroid
Cancer in therapy with Lenvatinib
Relatore
Prof. Duccio Volterrani
Candidato
Dr.ssa Elisa Tardelli
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Table of Contents
Page
1. Abstract 3
2. Background: the evaluation of tumor response in oncologic imaging 6
3. Patients and Methods 13
4. Statistics 15
5. Results 15
6. Discussion 17
7. Tables and Iconography 23
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ABSTRACT
Background. Monitoring tumor response to oncologic treatment is an integral and increasingly important function of 2-deoxy-2-[fluorine-18]fluoro-D-glucose Positron Emission Tomography [18F]FDG-PET. The possibility to differentiate as early as possible “responders” from “non-responders” patients during oncologic therapies can maximize the effectiveness of patient care. Moreover, oncologic imaging is expected to have a major role not only in the individual patient, but also in clinical trials designed to help select which new therapies should be advanced to progressively larger and more expensive clinical trials. The metabolic response assessed by [18F]FDG-PET/CT as a leading indicator of tumor response may be even more predictive of outcome than morphologic criteria, especially in the case of new cytostatic drugs. Recently, in agreement with the 2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer, AIFA has approved the use of Lenvatinib, a new tyrosine-kinase inhibitor (TKI), for the management of patients with progressive metastatic Radioiodine-Refractory Thyroid Cancer. Tumor response to TKIs in this setting is currently assessed by Response Evaluation Criteria in Solid Tumors (RECIST) and patient symptoms, while the role of [18F]FDG-PET/CT seems under-explored. Aim. To assess the role of [18F]FDG-PET/CT in monitoring tumor response to Lenvatinib in progressive metastatic Radioiodine-Refractory Thyroid Cancer patients and to predict prognosis with respect to different quantitative parameters. Patients and Methods. From December 2014 to September 2016, 33 patients with progressive Radioiodine-Refractory Thyroid Cancer (M/F=17/16; mean age: 65 years 8,7; histologic type: 21 papillary thyroid carcinoma, 8 follicular thyroid carcinoma, 3 poorly differentiated thyroid carcinoma, 1 oxyphilic cells) were enrolled at the Department of Endocrinology of the University of Pisa to be submitted to treatment with Lenvatinib (24 mg/day). All patients underwent a baseline [18F]FDG-PET/CT scan, then repeated after about 1, 2, 6 and 12 months during therapy. All scans were performed with a PET/CT Discovery 710 scanner (GE
4 Healthcare, Milwaukee, USA), including acquisition from the cranial vertex to half thigh, about 60 minutes after the injection of [18F]FDG (3.7 MBq/Kg). Patients fasted for at least 4 hours and finger stick blood glucose levels were <200 mg/dl prior to injection. Metabolic response to therapy was assessed in each site of disease (thyroid bed, lymph node, lung, bone, and other sites) during follow-up by PET Response Criteria in Solid Tumors (PERCIST 1.0), maximal Standardized Uptake Value (SUVmax), and metabolic tumor volume (MTV) and total lesion glycolysis (TLG), as measures of metabolic tumor burden. TLGwb and MTVwb were then determined by adding together the MTV and TLG of each site of disease to provide an index of the overall malignant processes in the entire body. Results. All patients had high metastatic metabolic involvement disease in more than two sites, in particular at the lymph nodes (32/33 patients) and in the lung (27/33 patients). Fifteen out of 33 patients died during follow-up (median of survival 19.9 months), while 18/33 patients are still alive, though with a reduced dose of Lenvatinib because of adverse effects. During the follow-up 21/33 patients presented progression metabolic disease (PMD) by PERCIST, 14/21 after about 1 month since the onset of therapy. The lack of early metabolic response assessed by PERCIST criteria was significantly associated with mortality, although the response by PERCIST at the end of follow-up was obviously found to be more predictive of outcome. In multivariate analysis, SUVmax, MTVwb and TLGwb of the overall malignant processes in the entire body at baseline were not significantly associated with overall survival (OS), although the majority of patients had decrease in total metabolic tumor burden during treatment. The reduction of both TLGwb and MTVwb was statistically significant only between the baseline PET/CT scan and the first control scan. Subsequently, tumor response, in terms of total tumor burden, showed a slight decrease, but remained essentially stable. This was also confirmed with respect to target lesions in thyroid bed, lymph nodes, and in the lungs, whose mean values of SUVmax, TLG and MTV showed an initial statistically significant decrease between the baseline PET/CT scan and the first control scan. Moreover, based on logistic regression there was a significant statistical evidence (likelihood-ratio test p <0.01) that OS depended on the persistence of TLG response (total and target ΔTLG %) at
5 lymph node level after 4.72.9 months (meanSD) of treatment. On the other hand, in bone metastases there was not a statistically significant response to therapy during follow up. Conclusion. Quantitative [18F]FDG-PET/CT can be a useful tool to evaluate tumor response during TKIs therapy in progressive metastatic Radioiodine-Refractory Thyroid Cancer patients.
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BACKGROUND: the evaluation of tumor response in oncologic imaging
Cancer is one the most common cause of death worldwide. Although the ultimate goal of cancer therapy is cure, for many common solid cancers, treatment of disseminated disease is able to improve overall survival (OS), but is often non curative, toxic, and costly. Distinguishing as early as possible between patients who are responding to treatment and those who are not can maximize the effectiveness of patient care. Monitoring tumor response to treatment is thus an integral and increasingly important function of oncologic imaging. Moreover, imaging is expected to play a major role not only in the individual patient, but also in clinical trials designed to help select which new therapies should be advanced from early phase I to phase II or III trials. There has been growing interest in surrogate metrics for OS after investigational cancer treatments, such as tumor response rate, time to tumor progression, and disease-free survival (DFS)1. Various approaches to standardize tumor response on imaging studies have been developed, beginning with the study of Moertel and Hanley based on physical examination in 19762. In this study, the authors quantified for the first time the variability in determinations of tumor size due to measurement errors and recommended that a true tumor response would need to be greater than 50% in order to avoid random responses due to measurement variance. Considering the need for standardization criteria across clinical trials for assessing tumor response to therapy, the World Health Organization (WHO) published the “WHO Handbook for reporting results of cancer treatment” in 19793
. Subsequently, the WHO criteria had been refined and simplified by the Response Evaluation Criteria in Solid Tumors (RECIST), which were initially published in 2000 (RECIST 1.0)4, 5 and updated (RECIST 1.1) in 20096 (Table 1). Another update of RECIST is currently in preparation. The fundamental principles of assessing tumor response, however, have not changed since the initial publication of the WHO criteria. The Response rate typically refers how often a tumor shrinks anatomically during oncologic therapy and has been classified as complete response (CR), partial response (PR), stable disease (SD), and progressive disease (PD) both in the WHO and
7 RECIST criteria. The time to tumor progression and DFS examine when the disease recurs or progresses. Both WHO and RECIST criteria were developed to assess response to cytotoxic chemotherapeutic agents considering changes in size during the course of treatment to be predictive of OS. Reduction in tumor size indicates a better prognosis than does unchanged or increasing tumor size and has been the mainstay for monitoring chemotherapy response in oncology. However, there are some concerns and limitations in this morphologic tumor response assessment7-10. Changes in tumor size after treatment are often, but not invariably, related to OS and notable exceptions have been identified in several studies 1, 11 12-17. Moreover, the response rate must be viewed with some caution with respect to newer cancer therapies that may be more cytostatic than cytocidal. Traditional anatomic size-based criteria can lead to the incorrect evaluation of treatment response for tumor like-gastrointestinal stromal tumor (GIST), hepatocellular carcinoma (HCC), or melanoma when treated with targeted therapies or immunotherapy18-22. Thus, additional measures of tumor response have been introduced, such as tumor attenuation proposed in the Choi Response Criteria for GIST during treatment with Imatinib, a tyrosine-kinase inhibitor (TKI)23, 24, or contrast enhancement patterns to estimate the viable tumor in the modified RECIST (mRECIST) criteria25, 26 for HCC during treatment with Sorafenib, an inhibitor of vascular endothelial growth factor receptor (VEGFR), platelet-derived growth factor receptor (PDGFR), and RAF. Attempts have been made to use the Choi criteria also in the assessment of other solid tumors, such as metastatic renal cell carcinoma treated with Sunitinib, another selective TKI, but more studies are needed for further evaluation27. Similarly to GIST and HCC, in mesotheliomas and pediatric tumors, modifications of RECIST dealing with the peculiarities of these tumors are in place28-31. Moreover, the Response Assessment in Neuro-Oncology (RANO) criteria, which were developed for gliomas treated with anti-angiogenetic agents32, 33, have been recently expanded to include brain metastases, leptomeningeal metastases, spine tumors, pediatric brain tumors, and meningiomas in order to assess reliable response assessment in nervous system tumors34. Conventional response criteria may not allow adequate assessment of tumor response also during immunotherapeutic therapies because
8 tumor shrinkage in eventually responding patients occurs later than for chemotherapy or targeted therapies and in some patients there is even a “pseudo-progression”. The Immune-related Response Criteria (irRC) were developed to overcome this issue in patients with metastatic melanoma receiving Ipilimumab, a human monoclonal antibody that blocks cytotoxic T lymphocyte antigen-4 (CTLA-4). The core novelty of the irRC is the assessment of tumor burden as a continuous variable, which considers target lesions identified at baseline together with new measurable lesions as they may occur during treatment35, 36. All these considerations emphasize the continuous effort by imaging to evolve in the context of genomic cancer characterization and increasing number and types of oncologic therapies available. In this setting, Positron Emission Tomography (PET), mainly with 2-deoxy-2-[fluorine-18]fluoro-D-glucose, [18F]FDG, appears particularly valuable because it could provide biologically relevant information unavailable through anatomic imaging1. Since its introduction in the early nineties as a promising functional imaging technique in the management of neoplastic disorders, [18F]FDG-PET, and subsequently [18F]FDG-PET/CT, have become a cornerstone in treatment efficacy assessment during or after oncologic treatment22. One of the most evident advantages of [18F]FDG-PET is its ability to detect, very early during treatment, both for interim and final assessment, significant changes in glucose metabolism as a surrogate of tumor chemo-sensitivity assessment. This could enable clinicians to detect much earlier the effectiveness of a given antineoplastic treatment, as compared to traditional radiological detection of tumor shrinkage, which usually takes time and occurs much later. Another major advantage of [18F]FDG-PET is its ability to differentiate residual viable neoplastic tissue from treatment-induced necrosis and fibrosis. Moreover, considering the skeleton, [18F]FDG-PET/CT has the potential to detect the response of osseous metastases to therapy with higher sensitivity than CT37. All these advantages are related to the intrinsic power of the metabolic method based on the strong relationship between [18F]FDG uptake and cancer cell number: decline in tumor [18F]FDG uptake results from reduction in viable tumor cell number, while sustained increase in tumor glucose use and volume of tumor cells is seen upon tumor regrowth1. However, a completely negative
9 [18F]FDG-PET scan at the end of therapy does not necessarily correspond to the absence of cancer cells. Indeed, the [18F]FDG-PET/CT scanners currently available are unsuitable to distinguish between no tumor burden versus microscopic burden when the entity of [18F]FDG uptake by the tumor is beyond the detection power of the instrument (0.4-10 mm). Nevertheless, patients whose [18F]FDG-PET scans convert from positive to negative after treatment more commonly have pathological CR and typically better DFS and OS than patients whose scans remain positive. Often, early changes in [18F]FDG uptake are not complete and may be difficult to visualize using qualitative methods. Quantitative [18F]FDG was introduced for the early sequential monitoring of tumor response of breast cancer in 199338. Since then, there has been growing interest in using [18F]FDG-PET to quickly assess whether a tumor is, or is not, responding to therapy. Quantitative non-anatomic imaging approaches can be used as biomarkers of cancer response to predict or assess the efficacy of treatment1. Different approaches to quantify tumor response have been discussed, but the Standardized Uptake Value (SUV) appears to be the most widely applied, generally correlating well with more complex analytic approaches39, 40. SUV is calculated in a region of interest (ROI) as the ratio of [18F]FDG concentration in this area to the injected activity normalized to patient’s body weight (SUVBW), lean body mass (SUVLBM or SUL), or body surface area (SUVBSA). SUL is typically more consistent from patient to patient than SUVBW, as patients with high body mass indices have high normal organ SUVs because [18F]FDG does not significantly accumulate in white fat in the fasting state39-42. SUVmax is obtained from the single pixel with the highest activity in tumor and it is the most used parameter in clinical practice because it is easily measured, operator-independent and should also be most resistant to partial-volume effect in small tumors. However, SUVmax has limitations, including its emphasis on a single pixel within a lesion, which makes it very susceptible to statistical noise. SUVmean is derived from the mean number of counts within an extended ROI in tumor, so that it is much less susceptible to noise, but suffers from poor reproducibility depending on the number of included pixels within the ROI. Therefore, some have advocated a compromise between SUVmax and SUV mean, termed SUVpeak, which is
10 defined as the average of the activity concentration in a spherical 1.0-cm3 volume of interest (VOI) or 1.2-cm diameter ROI, placed in the area of highest tumor [18F]FDG uptake. Although simplicity and ease of use are among the strengths of SUV, this parameter is vulnerable to many sources of unwanted variability43, such as scanner calibration, clock synchronization between machine and injection time, patient’s body weight, fasting blood glucose level, image acquisition time, image reconstruction algorithm, partial volume effect, and ROI definition. Therefore, absolute and rigorous standardization of [18F]FDG-PET protocols is required to achieve reproducible SUVs1, 44-46
. A variety of methods has been used to determine tumor response by changes in SUV during treatment, but the percentage decline in SUVmax (∆SUVmax) has been considered the most reliable indicator of metabolic activity shutdown47-49. However, there is currently no consensus regarding both how to define the ROI used to quantify tumor uptake and which threshold of ∆SUV to use to predict metabolic response during therapy. Another fundamental issue is whether the maximally metabolically active portion of the tumor or the total tumor volume is important in tumor assessment50, 51. Considering that the most critically important parts of tumors are the most biologically aggressive portions, most papers focus on a single or a few tumor foci in ROI selection. However, total lesion volume and its metabolically activity, known as metabolic tumor volume (MTV) and total lesion glycolysis (TLG), are potentially important parameters for studying tumor behavior52-55. MTV is determined as the total number of voxels within a volume of interest, while TLG is defined as the MTV multiplied with SUV mean53. Various relative or absolute thresholds have been suggested to calculate MTV and TLG and various methods for providing the tumor burden are still evolving, ranging from the more complex models of kinetic studies and tumor segmentation approaches to methods based on tumor to background gradient of [18F]FDG uptake 56-58
. Although controversy on the most appropriate approach to measure MTV and TLG remains, the two most commonly used methods include all voxels above 42% of the SUV max (MTV and TLG42%) or all voxels with a SUV over 2.5 (MTV and TLG 2.5)59-61. Considering both MTV and TLG and the fact that [18F]FDG-PET scans are routinely performed from “eyes to thighs”, the
11 metabolic tumor burden of the whole body can subsequently be determined by adding together either the MTV or TLG of the primary tumor (T), nodal metastases (N), and distant metastases (M). The whole body TLG (TLGwb) and MTV (MTVwb) thus serve as an index of the overall malignant processes in the entire body and can contribute to a more accurate risk stratification within each TNM stage62-64. Based on the need for standardization in clinical trials, the European Organization for Research and Treatment of Cancer (EORTC) published the first [18F]FDG-PET/CT criteria for assessing tumor response in 199965. EORTC PET criteria defined 4 response categories by quantifying changes in SUVBSA mean: progression metabolic disease (PMD), stable metabolic disease (SMD), partial metabolic response (PMR) and complete metabolic response (CMR). Subsequently, Positron Emission tomography Response Criteria In Solid Tumor (PERCIST 1.0) were introduced in 2009 to refine and validate quantitative approaches for monitoring PET tumor response in clinical trials and potentially in clinical practice1, 66 (Table 1). With PERCIST, image acquisition methods consistent with the recommendations of the National Cancer Institute and the Netherlands protocol for multicenter trials are recommended to ensure the correct performance of PET and to minimize variability44, 45, 67. The premises of PERCIST criteria are that cancer response is a continuous and time-dependent variable and that the most metabolically active tumor focus corresponds to the most aggressive portion of the tumor. A single target lesion (not necessarily the same lesion) at each time point between the pre- and post-treatment PET/CT studies is selected and analyzed by means of SULpeak to assess tumor response. PERCIST criteria consider a change in [18F]FDG uptake by 30% as a criterion for tumor response and progression. The background data are measured to help verify that the PET study is performed properly from a technical standpoint and to establish the appropriate threshold for SULpeak evaluation of the target lesion at baseline. A minimal level of tumor uptake at baseline is proposed to ensure that a decline in [18F]FDG with therapy could be measured during treatment, to decrease the likelihood that a change is due to chance, and to minimize overestimation of response or progression. When the SULpeak of tumor at baseline is lower than this threshold, the tumor is considered not measurable by PERCIST, except
12 when there is a new lesion or unequivocal progression in the follow-up study. A CMR is defined as [18F]FDG uptake indistinguishable from the surrounding background (SUL less than liver); a PMR as a decrease in SULpeak of greater than or equal to 30% and of at least 0.8 SUL units between the most intense evaluable lesion at baseline and the most intense lesion at follow-up, with no new [18F]FDG-avid lesions, no increase in size greater than 30% in the target lesion, and no SULpeak or identifiable increase in size greater than 30% in a non-target lesion; SMD as increase or decrease in SULpeak by less than 30%; and PMD as an increase in SULpeak of greater than or equal to 30% and an increase of at least 0.8 SUL units in a target lesion or development of at least one new lesion or increase in target lesion size by 30% or unequivocal progression in non-target lesions. In PERCIST, an adjunctive criterion for PMR is a decrease of greater than or equal to 75% of TLG1, 66. It appears that percentage declines in TLG are sometimes greater than declines in SUV and that TLG gives a larger range of changes after treatment than does SUV. This would suggest that larger changes in TLG would be required to have a meaningful response than are required for SUV alone1. A series of studies have shown that EORTC criteria and PERCIST provide a very similar assessment of tumor response, but the use of PERCIST is preferable because PERCIST is a much more specific standard17. Moreover, there is some evidence that PERCIST is a better approach to assess tumor response than RECIST, although this still needs to be proven by systematically clinical trials. Indeed, despite the rapid integration of [18F]FDG-PET/CT into clinical practice in individual patients, there has been a relatively scarce integration of PET into clinical studies. Until now, for drug development and regulatory approval purposes, indices of efficacy of treatment of solid tumors have been based mainly on the assessment of tumor size by RECIST. For example, tumor response to new cancer therapies, such as TKIs, is currently assessed by RECIST and patient symptoms68, 69, while the role of [18F]FDG-PET/CT seems under-explored in such cases. Recently, the phase III SELECT study has demonstrated significant improvements in DFS and in the response rate among patients with Radioiodine-Refractory Thyroid Cancer in therapy with Lenvatinib, a new TKI. The authors considered objective response rate assessment by RECIST 1.1 criteria and did not take into
13 account [18F]FDG-PET/CT for the evaluation of the effectiveness of therapy69. Based on the results of the SELECT study and in accordance with the 2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer, Lenvatinib has been approved for the management of patients with progressive metastatic Radioiodine-Refractory Thyroid Cancer. Currently, there is no data on the role of [18F]FDG PET/CT in monitoring tumor response to Lenvatinib.
The aim of this study is to assess the role of [18F]FDG PET/CT in monitoring treatment efficacy and predicting prognosis with respect to PERCIST criteria and different quantitative parameters (SUVmax, TLG, MTV) in Radioiodine-Refractory Thyroid Cancer patients in therapy with Lenvatinib.
PATIENTS AND METHODS
From December 2014 to September 2016, 33 patients with progressive metastatic Radioiodine-Refractory Thyroid Cancer were enrolled at the Department of Endocrinology of the University of Pisa to be submitted to treatment with Lenvatinib at a daily dose of 24 mg/day. The Radioiodine-Refractory Thyroid Cancer condition included at least one of the following criteria: the malignant/metastatic tissue never concentrates radioiodine (no uptake outside the thyroid bed at first therapeutic WBS), the tumor tissue loses the ability to concentrate radioiodine after previous evidence of radioiodine-avid disease, radioiodine is concentrated in some lesions but not in others, and metastatic disease progresses despite significant concentration of radioiodine. Patients had received no prior therapy with TKI, or had received one prior treatment regimen with TKI. All patients underwent a baseline [18F]FDG-PET/CT scan, then repeated after about 1, 2, 6 and 12 months during therapy with Lenvatinib. All scans were performed with a PET/CT Discovery 710 scanner (GE Healthcare, Waukesha, Wisconsin, USA) about 60 minutes after the injection of [18F]FDG (3.7 MBq/Kg). Low-dose helical CT scan (automatic exposure control with 100 mA max,
14 120 KVp) was obtained for attenuation correction with a 3.75-mm slice thickness and 3.27-mm reconstruction interval. During both PET and CT scan patients could breathe freely. TOF-PET scan was acquired with 02:00 min/bed (02:30 if patient’s BMI was over 29). Acquisition included the cranial vertex to half thigh, requiring 7 to 9 bed positions. Patients fasted for at least 4 hours and finger stick blood glucose levels were <200 mg/dl prior to injection. [18F]FDG-avid lesions were stratified by two different investigators working together considering each site of disease (thyroid bed, lymph node, lung, bone, and other sites) and were analyzed in the baseline study and during follow-up for SUV max, MTV and TLG by using a GE Advantage 4.6 Workstation. SUV max was the single voxel within the VOI with the greatest activity, MTV was defined as the cubic centimeter volume of voxels with SUV>42% of SUV max and TLG was defined as the product of MTV and the SUVmean of voxels within the MTV. TLGwb and MTVwb were then determined by adding together the MTV and TLG of each site of disease to provide a more complete estimation of the true volume and biological aggressiveness of tumor in the entire body. TLGtarget and MTVtarget were also determined as the highest values of TLG and MTV at different disease sites. Moreover, the metabolic tumor response to Lenvatinib was assessed during follow-up by PERCIST 1.0 criteria with the use of GE Advantage 4.6 PET vCAR software. In accordance with PERCIST, for background activity, a 3-cm diameter spherical VOI was placed in the right hepatic lobe. The SUL and the SD of SUL in the spherical VOI were measured. If the liver is diseased (most notably, full of cancer involvement), the mean background SUL and SD could be measured in the blood pool in a cylindrical VOI with a diameter of 1 cm and long axis (parallel to the descending aorta) of 2 cm in the center of descending aorta. For a tumor to be measurable at baseline, the SUL peak must be greater than or equal to 1.5 x mean liver SUL+ 2 SDs or to 2 x mean blood pool SUL+ 2 SDs to have a minimum threshold for evaluation. During follow-up patients were also submitted to CT imaging of the neck, chest, abdomen, pelvis and all other known sites of disease and to hematologic and biochemical laboratory testing with the assay of Thyroglobulin serum values. Moreover, tumor assessment was evaluated by RECIST 1.1 criteria.
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STATISTICS
OS was calculated from the date of baseline PET to death or last date of follow-up. The rates of OS were estimated and plotted by the Kaplan-Meier method and compared with the use of the Log-Rank test in the different categories of tumor response by PERCIST. Analyses were also performed by investigating the association between quantitative parameters of [18F]FDG uptake and OS for each site of disease and the entire body.
RESULTS
Thirty-three patients with Radioiodine-Refractory Thyroid Cancer patients were included in the study. All patients had high metastatic metabolic involvement disease in more than two sites, in particular at the lymph nodes (32/33 patients) and in the lung (27/33 patients). Baseline characteristics of enrolled patients are illustrated in Table 2. Site-specific stratification is shown to present the initial mean values of SUV max, TLG and MTV in the thyroid bed, lymph node, lung, bone and other sites of metastatic disease (liver, spleen, pancreas, adrenal glands, soft tissues and muscles) in Table 3. At the time of data cutoff (April 2017), the duration of PET follow-up was 17.75.6 months (meanSD). Fifteen out of 33 patients died during follow-up, while 18/33 patients are still alive, although with a reduced dose of Lenvatinib because of toxic effects (median of survival 19.9 months). The majority of these deaths were due to disease progression (40% of patients) and general deterioration of physical health (27%). Twenty-six out of 33 patients had a dose reduction of Lenvatinib during treatment (to 20, 14, or 10 mg/die). The most frequent adverse effects leading to dose reduction were asthenia, decreased appetite and hypertension, which occurred respectively in 82%, 63% and 45% of patients. Considering PERCIST 1.0 criteria, 21/33 patients presented PMD during follow-up, 14/21 after about 1 month since the onset of therapy. In Figures 1 different percentages of patients with PMR, SMD, and PMD, both at early evaluation (1.71.9 months, meanSD) and at the end of follow-up (5.63.7 months, meanSD), are shown.
16 None of the enrolled patients showed a CMR. The patients who experienced a lack of metabolic response as assessed by PERCIST criteria during follow-up presented a worse outcome. Indeed, patients with early PMD showed a median OS significantly lower than that with SMD or PMR (Figure 2a), but the most statistically powerful correlation was obviously found between OS and the final report of PMD by PERCIST. In Figure 2b we can see the difference in terms of OS between patients who showed PMD at the end of follow-up and those with SMD or PMR (10.0 vs 19.9 months, P<0.0001). The best tumor response was assessed by PERCIST criteria after 3.34 months (meanSD), also in patients who initially presented PMD, which was found after 2.92.9 months (meanSD).
In multivariate analysis, SUVmax, MTVwb and TLGwb of the overall malignant process in the entire body at baseline were not statistically associated with OS, although the majority of patients presented a decrease in total metabolic tumor burden during treatment. Figure 3 shows the decrease of mean values of TLGwb (3a) and MTVwb (3b) in the course of therapy. The reduction of both TLGwb and MTVwb was found statistically significant only between the baseline PET/CT scan and the first control scan. Subsequently, tumor response, in terms of total tumor burden, showed a slight decrease, but remained essentially stable. This was also confirmed with respect to target lesions (thyroid bed, lymph node, and lung), whose mean values of SUVmax, TLG and MTV showed an initial statistically significant decrease between the baseline PET/CT scan and the first control scan. Reduction of TLG and MTV was found in the course of treatment in thyroid bed, lymph nodes, and lungs. On the other hand, in bone metastases the nadir was reached later during therapy and it was not statistically significant with respect to baseline. Moreover, based on logistic regression there was a significant statistical evidence that OS depended on the persistence of both TLG and MTV response (total and target ΔTLG% and ΔMTV%) at lymph node level after 4.72.9 months (meanSD) of treatment (likelihood-ratio test p <0.01). This association was found to be more evident for total and target ΔTLG% (Figure 4). No correlation was found between the ΔSUVmax
17 values in the different sites of disease during follow-up and OS. No association was also found between ΔSUV max, ΔTLG, ΔMTV and serum thyroglobulin values, although they both showed a decrease during therapy with Lenvatinib. Moreover, variance analysis demonstrated a weak correlation between final reports by PERCIST and final ΔTLG% values (P=0.05) as we can appreciate in Figure 5.
Considering the RECIST 1.1 criteria, PD was found after 7.96.6 months (meanSD) since the onset of therapy, 5 months later than PMD assessed by PERCIST (2.92.9 months, meanSD). Moreover, the final response by RECIST was found to be statistically significant with respect to duration of OS, but the association was lower than that observed with the final response by PERCIST (Figure 6).
DISCUSSION
Recently, Lenvatinib, an oral inhibitor of VEGF-R 1-3, fibroblast growth factor receptors (FGF-R) 1-4, PDGF-Rα, RET, and KIT, has been approved as an optional treatment for patients with progressive metastatic Radioiodine-Refractory Thyroid Cancer70. [18F]FDG PET/CT is a promising useful indicator to assess tumor metabolic response in these patients, but currently its role seems to be under-explored. Considering new anti-cancer therapies, preliminary data suggest that response assessment by [18F]FDG-PET/CT may be better correlated with patients outcome and may be a better predictor of the effectiveness of treatment than morphologic evaluation17. Caldarella et al. illustrated the significant limitations of RECIST assessment for the management of primary Renal Cell Carcinoma (RCC) in therapy with TKIs, emphasizing the role of metabolic changes on [18F]FDG-PET/CT as a useful imaging biomarker to assess tumor response71. The high sensitivity of [18F]FDG-PET had already been demonstrated in detecting early response and in predicting long-term response to Imatinib in patients with metastatic GIST23, 72. In the Radioiodine-Refractory Thyroid Cancer patients enrolled at the Department of Endocrinology of the University of Pisa to be
18 submitted to therapy with Lenvatinib, [18F]FDG-PET/CT demonstrated to be a useful tool to predict prognosis. In our series, the evaluation of tumor response by using PERCIST criteria was predictive of OS (Figure 2). Indeed, the median OS was longer in patients who presented SMD and PMR than in patients with PMD, when considering both early and the last evaluation with [18F]FDG-PET/CT (10.0 vs 19.9 months, P<0.0001). The shorter median OS observed in patients who presented PMD during follow-up indicates that these patients presented more aggressive thyroid cancers and a worse response to Lenvatinib. During follow-up, the percentage of patients who reported PMD remained substantially stable, while the percentage of patients responding to therapy decreased from 24% at the first control to 9% at the final report. Moreover, it is interesting to note that the percentage of patients who presented SMD during therapy increased from 33% to 52% (Figure 1). No patients showed a CMR during follow-up. This is probably due to the fact that all patients presented high progressive [18F]FDG-avid disease with multiple large metastasis and the probability of a CR to treatment was extremely reduced since the onset of therapy. Indeed, it is known that the likelihood of obtaining a CR in thyroid cancer is reduced when [18F]FDG uptake on PET/CT is high in the tumor foci and metastases are large tumors greater than 1-2 cm in size70, 73, 74. Another important aspect to take into account is that, until now the duration of TKIs response is not durable and “escape phenomenon”, after which the tumor, whose growth was controlled for several months, starts to grow again, will arrive soon or later75. Nevertheless, despite the extremely high risk of disease progression, patients who presented SMD or PMR during follow-up had a median of OS significantly longer than those with PMD. Important limitations of our data include the decrease in the number of [18F]FDG-PET/CT controls during treatment among the majority of patients because of death or decay of general conditions. Despite this consideration, these results agree with data in the literature according to which target-therapy agents have been described as likely “cytostatic” than “cytocidal”, and tumor stabilization has been acknowledged as an important endpoint of treatment76-78. Indeed, lack of progression may be associated with good improvement in outcome, even in the absence of major shrinkage of tumors9, 79. In this setting tumor response is low and
19 probably underestimated applying only RECIST criteria, ranging from 10-40% in metastatic RCC during anti-angiogenetic therapies80, 81. In fact, in our series, despite the small group of patients, PERCIST criteria performed slightly better than RECIST in predicting OS.
[18F]FDG-PET/CT assessment by PERCIST seems to be slightly more sensitive than morphological evaluation because tumor metabolic response occurs earlier during treatment than changes in tumor size. In our series, PMD by PERCIST criteria was found earlier than PD by RECIST (2.92.9 months versus 7.96.6 months, meanSD). The possibility to assess early tumor response during treatment is one of the most important advantages of [18F]FDG-PET/CT because it may predict outcome and may save “non-responders” from the toxic effects of oncologic therapies82. Lenvatinib is associated with important toxicities and at present the actual benefit regarding OS69, 74 is not clearly demonstrated. Also in our series, Lenvatinib caused an important decrease in quality of life and it is therefore fundamental to adequately select patients who should be treated. Another aspect to consider in our population is the important involvement of bone disease that may be difficult to evaluate with RECIST criteria because of the sclerotic reaction, that typically persists and can even increase as response of the healing bone83. On the other hand, response monitoring with PERCIST criteria is feasible for bone metastases in the same way as for soft tissue metastases84. Thus, assessment by [18F]FDG-PET/CT may be more predictive of final outcome in such cases.
This study also analyzed different quantitative parameters, such as SUVmax, TLG and MTV in order to improve the accuracy and consistency of oncologic [18F]FDG-PET/CT during treatment with TKIs. No association was found between OS and values of SUVmax at baseline and ∆SUVmax during treatment. Therefore, despite the fact that SUVmax emerges as the predominant parameter for tumor quantification in clinical practice, it seems not to have a very useful role in monitoring the [18F]FDG uptake in this setting. There is currently great interest in studying quantitative [18F]FDG-PET/CT parameters to improve patient care, but probably, considering the heterogeneity of tumors and the different types of therapies available, there is no a parameter clearly better than others to evaluate tumor response. In a recent meta-analysis about surgical NSCLC the
20 authors reported that high value of SUVmax, MTV and TLG were all correlated to a higher risk of recurrence and death and suggested the use of [18F]FDG-PET/CT to select patients that may benefit from aggressive treatments85. In others studies on NSCLC, the authors concluded that MTVwb and TLGwb were significantly better than SUVmax to predict prognosis63, 64. MTV and TLG reflect changes throughout the entire tumor mass and, in theory, should be more accurate methods of detecting global changes of tumor burden than a single pixel value measurement86. Indeed, several studies have shown prognostic value of both MTV and TLG in different solid cancers, such as mesothelioma54, 87 and head and neck cancers88. Nevertheless, the evaluation of tumor burden appears to be a more sensitive parameter to evaluate response than SUVmax in several, but not all cancers89. In our series, no correlation was found between total tumor burden during treatment and OS. Neither the MTVwb nor TLGwb at baseline were associated with duration of OS. Nevertheless, all patients presented decrease in total metabolic tumor burden, in lymph nodes and lungs during treatment, although this reduction was statistically significant only between the baseline PET/CT scan and the first control scan. Subsequently, tumor response showed a slight decrease, but remained essentially stable. These results demonstrate that Lenvatinib has a direct effect on tumor glucose metabolism and causes very rapid changes in [18F]FDG uptake in sensitive cells. An important consideration to be taken is that probably the decrease of tumor burden was not statistically significant during follow-up because of the reduction in the number of PET controls, which is the main limit of this study. Moreover, our study supports the evidence that TKIs appear to be less effective in controlling bone metastatic disease in comparison to disease at other soft tissues70, 75, 90. Indeed, in bone metastases there was not a statistically significant response to therapy and PMD occurred during treatment despite maintained benefit with respect to disease at other metastatic sites.
A statistically significant association was found between OS and the persistence of both TLG and MTV response at lymph node level after 4.72.9 months (meanSD) of treatment (Figure 5). This correlation was more evident for total and target ΔTLG% (likelihood-ratio test p <0.01) than MTV.
21 These results seem to agree with those of Ulaner et al. obtained in newly diagnosed metastatic breast cancer who found that TLG may be a more informative biomarker of OS than SUVmax for patients with lymph node and liver metastases91. TLG provides information on both tumor volume and metabolic activity and may be a more sensitive imaging parameter than MTV. Increasing enthusiasm for its use is evidenced through multiple reports describing its superiority over SUV max as a predictive and prognostic biomarker in multiple tumors of the head and neck92, gynecological organs60, 61, 93, 94, lung95, 96 and esophagus97.
Another important issue to consider for [18F]FDG-PET/CT is the lack of consensus about the optimal percentage reduction in quantitative parameters, such as MTV, TLG and SUV, to predict OS. The challenge is mainly due to the heterogeneity of the tumors. For various types of cancer and different therapies it is unclear what is the best parameter and the best percentage reduction to consider for tumor response52. Optimal threshold to define response on [18F]FDG-PET/CT for response-adapted therapies, will, therefore, likely be drug- and tumor-specific. In our series, we did not find a statistically significant percentage threshold reduction value for none of the parameters considered. Nevertheless, variance analysis demonstrated a weak correlation between final reports by PERCIST and final ΔTLGwb% values, with a mean value of -ΔTLG% greater than 84% for patients with PMR (Figure 6). This result is in accordance with the PERCIST criteria, according to which a criterion for PMR is a decrease ≥75% of TLG1
.
Despite some limitations, this study showed that [18F]FDG-PET/CT should be a useful tool to evaluate tumor response during TKIs therapy in Radioiodine Refractory Thyroid Cancer patients. The metabolic evaluation provides important prognostic information that may be even more predictive of outcome than morphologic criteria. This is of paramount importance also because serum thyroglobulin seems to be not a useful biomarker in these settings. In our series, no statistically significant correlation was found between SUVmax, TLG, MTV and serum thyroglobulin values. Tumor assessment by PERCIST is feasible and allows standardization of the [18F]FDG uptake evaluation, which is fundamental in clinical practice and clinical trials. Although
22 further studies are needed to better understand the utility of [18F]FDG-PET/CT in quantifying tumor metabolic response to TKIs, [18F]FDG-PET/CT should have an important role in order to differentiate “responders” from “non-responders” patients during therapy. Moreover, due to the high toxicity of TKI therapy [18F]FDG-PET/CT could be a useful tool in modulating treatment regimen in order to improve tolerance and at the same time to maintain effectiveness.
23
24
Table 1. Comparison of RECIST 1.1 and PERCIST 1.0 Tuomor Resonse Criteria
Response RECIST 1.16 PERCIST 1.01
Complete Response Disappearance of all target lesion or lymph nodes<10 mm in the short axis
FDG uptake indistinguishable from surrounding background (SUL* less than liver)
Partial Response >30% decrease in the sum of longest diameters of target lesions
Decrease of SUL by ≥30% and at least 0.8 SUL units difference, and no new FDG-avid lesions, and no increase in size >30% of the target lesion, and no increase in SUL or size of non-target lesion
Progressive disease >20% increase in the sum of the longest diameters of target lesions with an absolute increase of ≥5 mm, or new lesion
SUL increase by at least 30% and increase in by at least 0.8 SUL units of the target lesion, or development of at least one new lesion, or increase in target lesion size by 30%, or unequivocal preogression of non-terget lesions
Stable disease None of the above Incresase or decrease of SUL by less than 30%
Note.-*SUL=lean-body mass-normalized standardized uptake
The four response categories for PET are Complete Metabolic Response, Partial Metabolic Response, Progressive Metabolic Disea se and Stable Disease
25 Table 2. n Patients 33 Age (years) <45 ≥45 meanSD 2 31 65 (8.7) Sex M F 17 16 Histological type PTC* FTC** Poorly differentiated Oxyphilic cells 21 8 3 1 TNM*** T Tx T1 T2 T3 T4 N Nx N0 N1a N1b M Mx M0 M1 4 0 2 17 10 1 13 3 16 1 18 14 Stage*** I II III IVa IVb IVc 0 5 1 12 3 12 Thyroglobulin (ng/mL) meanSD 7888.7519661.5
*PTC- Papillary Thyroid Carcinoma
** FTC- Follicular Thyroid Carcinoma
***2015 ATA guidelines70
26 Table 3. Site of disease n MTV(cm3) meanSD TLG (g/mL*cm3) meanSD SUVmax meanSD Thyroid bed 12/33 16,523,4 195222 2420,7 Lymph node 32/33 32,8 38 381 476 21,2515,7 Lung 27/33 13,618 117214 13,813 Bone 21/33 30,232,5 324637 1,910 Others* 22/33 40,598 6132089 1714
* Liver, Soft tissues, Muscles, Spleen, Adrenal glands, Brain, Pancreas, Breast, Pleura
Figure 1. Different percentages of patients with PMR, SMD, and PMD by PERCIST criteria at early evaluation and at
the end of follow-up. At the first control [18F]FDG-PET/CT, 43%, 33% and 24% of patients presented PMD, SMD and PMR, respectively. At the end of follow-up the percentages were respectively of 39%, 52%, and 9%. None of the patients presented CMR.
27
Figure 2a.Kaplan-Meier Estimate of OS with respect to the PERCIST criteria at the first [18F]FDG-PET/CT evaluation. OS of patients with SMD and PMR and of patients with PMD.
Figure 2b. Kaplan-Meier Estimate of OS with respect to the PERCIST criteria at the final [18F]FDG-PET/CT evaluation. OS of patients with SMD and PMR and of patients with PMD.
28
Figure 3a. The graphic depicts the decrease of mean values of MTVwb during follow-up.
Figure 3b. The graphic depicts the decrease of mean values of TLGwb during follow-up.
Figure 4. Logistic regression analysis between OS and ∆TLG% tot and ∆TLG% target at lymph nodes. The persistence
of metabolic response in lymph nodes at 4.72.9 months (meanSD) of treatment was associated with a more favorable outcome (likelihood-ratio test p <0.01).
-20 0 20 40 60 80 100 120 1 2 3 4 5 -500 0 500 1000 1500 1 2 3 4 5 ∆MTVwb Months Months ∆TLGwb ∆TLG tot% ∆TLG target%
29
Figure 5. Correlation between final result by PERCIST and ΔTLGwb% by using analysis of variance (ANOVA)
techniques (P=0.05).
Figure 6. Kaplan-Meier Estimate of OS with respect to the RECIST criteria 1.1 at the final radiological evaluation. OS of patients with SMD and PMR and of patients with PMD.
P<0.005 ∆TLG%
30
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