Bruno Vanderlinden

Tumor Texture Analysis in 18F-FDG PET: Relationships Between Texture Parameters, Histogram Indices, Standardized Uptake Values, Metabolic Volumes, and Total Lesion Glycolysis

Texture indices are of growing interest for tumor characterization in 18F-FDG PET. Yet, on the basis of results published in the literature so far, it is unclear which indices should be used, what they represent, and how they relate to conventional indices such as standardized uptake values (SUVs), metabolic volume (MV), and total lesion glycolysis (TLG). We investigated in detail 31 texture indices, 5 first-order statistics (histogram indices) derived from the gray-level histogram of the tumor region, and their relationship with SUV, MV, and TLG in 3 different tumor types. Methods: Three patient groups corresponding to 3 cancer types at baseline were studied independently: patients with metastatic colorectal cancer (72 lesions), non–small cell lung cancer (24 lesions), and breast cancer (54 lesions). Thirty-one texture indices were studied in addition to SUVs, MV, and TLG, and 5 indices extracted from histogram analysis were also investigated. The relationships between indices were studied as well as the robustness of the various texture indices with respect to the parameters involved in the calculation method (sampling schemes and tumor volume of interest). Results: Regardless of the patient group, many indices were highly correlated (Pearson correlation coefficient |r| ≥ 0.80), making it desirable to focus on only a few uncorrelated indices. Three histogram indices were highly correlated with SUVs (|r| ≥ 0.84). Four texture indices were highly correlated with MV, and none was highly correlated with SUVs (|r| ≤ 0.55). The resampling formula used to calculate texture indices had a substantial impact, and resampling using at least 32 discrete values should be used for texture indices calculation. The texture indices change as a function of the segmentation method was higher than that of peak and maximum SUVs but less than mean SUV for 5 texture indices and was larger than that of MV for 14 texture indices and for the 5 histogram indices. All these results were extremely consistent across the 3 tumor types and explained many of the observations reported in the literature so far. Conclusion: None of the histogram indices and only 17 of 31 texture indices were robust with respect to the tumor-segmentation method. An appropriate resampling formula with at least 32 gray levels should be used to avoid introducing a misleading relationship between texture indices and SUV. Some texture indices are highly correlated or strongly correlate with MV whatever the tumor type. Such correlation should be accounted for when interpreting the usefulness of texture indices for tumor characterization, which might call for systematic multivariate analyses.

Comparative assessment of methods for estimating tumor volume and standardized uptake value in (18)F-FDG PET.

In 18F-FDG PET, tumors are often characterized by their metabolically active volume and standardized uptake value (SUV). However, many approaches have been proposed to estimate tumor volume and SUV from 18F-FDG PET images, none of them being widely agreed upon. We assessed the accuracy and robustness of 5 methods for tumor volume estimates and of 10 methods for SUV estimates in a large variety of configurations. Methods: PET acquisitions of an anthropomorphic phantom containing 17 spheres (volumes between 0.43 and 97 mL, sphere-to-surrounding-activity concentration ratios between 2 and 68) were used. Forty-one nonspheric tumors (volumes between 0.6 and 92 mL, SUV of 2, 4, and 8) were also simulated and inserted in a real patient 18F-FDG PET scan. Four threshold-based methods (including one, Tbgd, accounting for background activity) and a model-based method (Fit) described in the literature were used for tumor volume measurements. The mean SUV in the resulting volumes were calculated, without and with partial-volume effect (PVE) correction, as well as the maximum SUV (SUVmax). The parameters involved in the tumor segmentation and SUV estimation methods were optimized using 3 approaches, corresponding to getting the best of each method or testing each method in more realistic situations in which the parameters cannot be perfectly optimized. Results: In the phantom and simulated data, the Tbgd and Fit methods yielded the most accurate volume estimates, with mean errors of 2% ± 11% and −8% ± 21% in the most realistic situations. Considering the simulated data, all SUV not corrected for PVE had a mean bias between −31% and −46%, much larger than the bias observed with SUVmax (−11% ± 23%) or with the PVE-corrected SUV based on Tbgd and Fit (−2% ± 10% and 3% ± 24%). Conclusion: The method used to estimate tumor volume and SUV greatly affects the reliability of the estimates. The Tbgd and Fit methods yielded low errors in volume estimates in a broad range of situations. The PVE-corrected SUV based on Tbgd and Fit were more accurate and reproducible than SUVmax.

Multimodality imaging can predict the metabolic response of unresectable colorectal liver metastases to radioembolization therapy with Yttrium-90 labeled resin microspheres

Selective internal radiotherapy (SIRT) using Yttrium-90 labeled resin microspheres is increasingly used for the radioembolization of unresectable liver metastases of colorectal cancer (CRC). The treatment can be simulated by scintigraphy with Tc(99m)-labeled macroaggregates of albumin (MAA). The aim of the study was to develop a predictive dosimetric model for SIRT and to validate it by correlating results with the metabolic treatment response. The simulation of the dosimetry was performed by mathematically converting all liver voxel MAA-SPECT uptake values to the absolute Y(90) activity. The voxel values were then converted to a simulated absorbed dose (Gy) using simple MIRD formalism. The metabolic response was defined as the change in total lesion glycolysis (TLG) on FDG-PET. A total of 39 metastatic liver lesions were studied in eight evaluable patients. The mean administered Y(90) activity was 1.69 GBq (range: 1.33-2.04 GBq). The median (95% CI) simulated absorbed dose (Gy) was 29 Gy (1–98 Gy) and 66 Gy(32–159 Gy) in the poor (<50% TLG change) and the good responders (TLG change > 50%),respectively [DOSAGE ERROR CORRECTED].Using a simple cut-off value of 1 for the MAA-tumor-to-normal uptake ratio, a significant metabolic response was predicted with a sensitivity of 89% (17/19), a specificity of 65% (13/20), a positive predictive value of 71% (17/24) and a negative predictive value of 87% (13/15). Integrated multimodality imaging allows prediction of metabolic response post radioembolization using Y(90)-resin microspheres, and should be used for patient selection.

Serial FDG–PET/CT for early outcome prediction in patients with metastatic colorectal cancer undergoing chemotherapy

BACKGROUND The study purpose was to assess the predictive value of 2-[fluorine-18]fluoro-2-deoxy-D-glucose (FDG)-positron emission tomography (PET)/computerized tomography (CT) metabolic response after a single course of chemotherapy in patients with metastatic colorectal cancer (mCRC). PATIENTS AND METHODS FDG-PET/CT scans were carried out at baseline and on day 14 in 41 patients with unresectable mCRC treated with a biweekly regimen of chemotherapy. Metabolic nonresponse was defined by <15% decrease in FDG uptake in the dominant proportion of the patients lesions or if a lesion was found metabolically progressive. The PET-based response was correlated with radiological response (primary end point) and patients outcome (secondary end points). RESULTS RECIST response rate in metabolically responding patients was 43% (10 of 23) compared with 0% (0 of 17) in nonresponding patients (P=0.002). The metabolic assessments predictive performance for RECIST response was sensitivity 100% [95% confidence interval (CI) 69% to 100%], specificity 57% (95% CI 37% to 75%), positive predictive value 43% (95% CI 23% to 66%), and negative predictive value 100% (95% CI 80% to 100%). Comparing metabolically responding versus nonresponding patients, the hazard ratio (HR) was 0.28 (95% CI 0.10-0.76) for overall survival and 0.57 (95% CI 0.27-1.21) for progression-free survival. CONCLUSION The metabolic response measured by FDG-PET/CT after a single course of chemotherapy in mCRC is able to identify patients who will not benefit from the treatment.

Heterogeneity of Metabolic Response to Systemic Therapy in Metastatic Breast Cancer Patients

AIM The aim of this retrospective study was to describe the intra-individual heterogeneity of the ¹⁸F-labelled fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) response among lesions in bone-dominant metastatic breast cancer patients treated with systemic therapies. PATIENTS AND METHODS The metabolic response was analysed by comparing PET/CT scans carried out before and during a new treatment phase (n=46) in 25 bone-dominant metastatic breast cancer patients. Patients presented both bone and extra-bone metastases in 48% treatment phases. The metabolic response was analysed according to European Organization for Research and Treatment of Cancer (EORTC) criteria. A heterogeneous response was defined as the coexistence of responding and non-responding lesions within the same patient. RESULTS The lesion-based response analysis showed a heterogeneous metabolic response in 48% of treatment phases. In the subset with both bone and extra-bone metastases (n=20), PET/CT showed discordant responses between bone and extra-bone metastases in 6/20 (30%) treatment phases. Considering all the cases included in the study, the time to progression (TTP) was longer in cases with a metabolic response compared with the cases with a metabolic non-response (P=0.02). In cases with a PET/CT non-response, TTP seemed to be lower in those with a homogeneous non-response compared with those with a heterogeneous metabolic response (P=0.07). CONCLUSION Whole-body FDG-PET allows frequent heterogeneous responses after systemic therapy to be identified in bone-dominant metastatic breast cancer patients.

Detection and Characterization of Tumor Changes in 18F-FDG PET Patient Monitoring Using Parametric Imaging

In PET-based patient monitoring, metabolic tumor changes occurring between PET scans are most often assessed visually or by measuring only a few parameters (tumor volume or uptake), neglecting most of the image content. We propose and evaluate a parametric imaging (PI) method to assess tumor changes at the voxel level. Methods: Seventy-eight pairs of tumor images obtained from baseline and follow-up 18F-FDG PET/CT for 28 patients with metastatic colorectal cancer were considered. For each pair, after CT-based registration of the PET volumes, the 2 PET datasets were subtracted. A biparametric graph of subtracted voxel values versus voxel values in the first PET scan was obtained. A model-based analysis of this graph was used to identify the tumor voxels in which significant changes occurred between the 2 scans and yielded indices characterizing these changes. The Response Evaluation Criteria in Solid Tumors (RECIST) based on the CT images obtained 5–8 wk after the second PET/CT scan were used to classify tumor masses as responding or progressive. On the basis of this classification, we compared the sensitivity and specificity of PI and an approach based on recommendations from the European Organization for Research and Treatment of Cancer (EORTC). Results: For tumor-based classification, the EORTC-based approach had a sensitivity and specificity of 85% and 52%, respectively, for detecting responding lesions, whereas PI had a sensitivity and specificity of 100% and 53%, respectively. None of responding tumors using RECIST was classified as progressive with the PI or EORTC-based criteria. Among the 14 progressive lesions according to RECIST, 12 were identified as progressive with PI whereas EORTC-based criteria classified only 1 as progressive and 13 as stable tumors. Considering the patient-based classification, none of the responders according to RECIST was classified as having progressive disease with the PI and EORTC-based criteria. PI has the advantage of showing a parametric image of the patient response to therapy, indicating potential heterogeneity in tumor response. Conclusion: The PI method has been successfully applied to characterize early metabolic tumor changes in 78 lesions from 18F-FDG PET/CT scans of patients with metastatic colorectal cancer during chemotherapy. The PI findings correlated well with the standard RECIST-based response assessment.

Multicenter Harmonization of 89Zr PET/CT Performance

This study investigated the feasibility of quantitative accuracy and harmonized image quality in 89Zr-PET/CT multicenter studies. Methods: Five PET/CT scanners from 3 vendors were included. 89Zr activity was measured in a central dose calibrator before delivery. Local activity assays were based on volume as well as on the local dose calibrator. Accuracy and image noise were determined from a cross calibration experiment. Image quality was assessed from recovery coefficients derived from different volume-of-interest (VOI) methods (VOIA50%, based on a 3-dimensional isocontour at 50% of the maximum voxel value with local background correction; VOIMax, based on the voxel with the highest uptake; and VOI3Dpeak, based on a spheric VOI of 1.2-cm diameter positioned so as to maximize the enclosed average). PET images were analyzed before and after postreconstruction smoothing, applied to match image noise. Results: PET/CT accuracy and image noise ranged from −3% to 10% and from 13% to 22%, respectively. VOI3Dpeak produced the most reproducible recovery coefficients. After calibration of the local dose calibrator to the central dose calibrator, differences between the local activity assays were within 6%. Conclusion: This study showed that quantitative accuracy and harmonized image quality can be reached in 89Zr PET/CT multicenter studies.

New Imaging Techniques for 90Y Microsphere Radioembolization

Adequate patient selection and treatment planning is crucial for a safe and cost-effective administration of selective internal radiotherapy (SIRT) of malignant liver disease using 90 Y-labelled microspheres. It requires the implementation of multimodality imaging, integrating metabolic, functional and structural characteristics. A multidisciplinary approach is a prerequisite for SIRT, bringing together the knowhow and expertise of radiologists, nuclear medicine physicians, medical physicists, imaging engineers, and radiotherapists. This review discusses the available radiologic (CT/MRI) and nuclear (SPECT/PET) imaging modalities and their specific utility in the different diagnostic phases related to SIRT: wholebody and intrahepatic pre-treatment disease staging, CT and MRI-based angiography, liver-lung shunt assessment, treatment simulation, predictive dosimetry, post-treatment imaging, and SIRT response assessment.

Pretreatment Dosimetry in HCC Radioembolization with 90Y Glass Microspheres Cannot Be Invalidated with a Bare Visual Evaluation of 99mTc-MAA Uptake of Colorectal Metastases Treated with Resin Microspheres

TO THE EDITOR: We read with great interest the paper by Ulrich et al. (1) reporting on the predictive value of 99mTcmacroaggregated albumin (99mTc-MAA) uptake in patients with colorectal liver metastasis scheduled for selective internal radiation therapy (SIRT) with 90Y-loaded resin microspheres. Despite the inclusion of an impressive amount of work (66 patients and 435 lesions), the results are disappointing as they found no association between patientor lesion-based response and the overall degree of 99mTc-MAA perfusion (P 5 0.172). The authors conclude that the response cannot be predicted by the degree of perfusion on 99mTc-MAA scintigraphy. This study raises several important methodologic and general concerns that have to be clarified. In our opinion, conclusions made by the authors cannot be supported by data presented in this paper. From a methodologic point of view, we have 4 major concerns: the insufficient quantification method, lack of dosimetric evaluation, inappropriate radiologic evaluation of response, and inadequate definition of catheter position. First, the main issue about imaging 99mTc-MAA perfusion is that it does not sufficiently evaluate the true degree of implantation in small lesions. Mazzaferro et al. (2), using the same Siemens software as Ulrich et al., needed to apply 120 projections, 8 iterations, and 8 subsets without any gaussian postfiltering to maximize the SPECT spatial resolution (7 mm in full width at half maximum measured in water), keeping a reasonable noise level. Nevertheless, under these circumstances, because of the wellknown partial-volume effect, a 20% underestimation of activity was reported for a 1.8-cm-diameter sphere (3 mL in volume) with a 99mTc contrast ratio of 4:1 between sphere and background. The smaller the lesion, the larger the underestimation. For this reason, Mazzaferro et al. excluded lesions with a diameter smaller than 1.8 cm from their voxel dosimetry analysis. The reconstruction parameter described by Ulrich et al. implies worse spatial resolution than that achieved by Mazzaferro et al., with a consequently more pronounced underestimation of the degree of 99mTc-MAA perfusion even in lesions larger than 1.8 cm, whereas their lesion size was 3.39 6 2.12 cm at baseline. Moreover, they adopted the Chang attenuation correction, which is valid for uniform objects and for which accuracy should be validated in regions of nonuniform attenuation (slices containing liver–lung interfaces). The lesion-based analysis relies on MR imaging/SPECT registration, and no description of the registration process is given. Since liver deformation can occur in 30 d, an image mismatch could occur without an elastic deformation registration method. Second, SIRT is a kind of radiation therapy. As such, efficacy should be discussed in terms of absorbed dose and radiobiologic models, not merely in qualitative terms of degree of 99mTc-MAA implantation, which is imageand operator-dependent. The third methodologic concern relates to the response evaluation. According to our experience, the 6-wk interval is definitely too short to observe an appropriate morphologic response. Metabolic assessment of tumor response using 18F-FDG PET can be applied early (6–8 wk) and would probably have been more accurate as an endpoint for assessing a dose–response relationship. In addition, the Response Evaluation Criteria in Solid Tumors (RECIST) are not at all a validated method for the assessment of treatment response in SIRT. “The most common change in the CT-appearance of the liver after SIRT is decreased attenuation in the affected hepatic areas” (3). In these situations, response evaluation must take into account the vascularization of the lesion, as in the criteria of the European Association for the Study of the Liver (EASL) or in modified RECIST. Fourth, regarding catheter position, identification of the vessel by merely specifying right or left artery is not sufficient. The distance between the tip of the catheter and the origin of the artery should also be carefully reproduced, since a 5to 10-mm difference in catheter position can have a major impact on flow distribution (4). In addition to these 4 methodologic issues, 3 general concerns have to be raised. First, the results of this study contradict previously published results on resin microspheres (SIR-Spheres; Sirtex). Using an appropriate dosimetric approach (5), a preliminary study (8 patients) found a good correlation between the tumor-absorbed dose and the response of metastatic disease to 90Y-resin microspheres. On the other hand, more than one study (Wondergem et al. (4), for instance) found a poor correspondence between 99mTc-MAA and 90Y-resin microsphere biodistributions, suggesting that the degree of 99mTc-MAA perfusion could not predict response. Indeed, 99mTc-MAA particles and 90Y-resin microspheres may not have the same distribution, since the number of injected therapeutic particles is about 300 times higher than the number of 99mTc-MAA particles. Moreover, 99mTcMAA is injected as a bolus, whereas the resin microspheres are given as a series of small injections interleaved with checks with contrast medium. In hepatocellular carcinoma (HCC), the results seem more concordant. Using the partition model applied to planar 99mTc-MAA images, Ho et al. (6) reported a response rate of 37.5% for a tumor dose of more than 225 Gy versus only 10.3% for a tumor dose of 225 Gy or less (P, 0.006). Similarly, Kao et al. (7) reported a good correlation between 99mTc-MAA SPECT/CT dosimetry and response after 90Y-resin microsphere therapy. Second, the fact that in Ulrich’s study 26% of the lesions with a low degree of 99mTc-MAA perfusion effectively responded may be explained by at least one factor other than quantification underestimation. Although quantification of bremsstrahlung images of 90Y distribution was not performed, the authors conclude that even in hypovascularized lesions the amount of 90Y-resin microspheres is sufficient to induce an antitumoral effect. We wonder whether, for some patients, this antitumoral effect might have been embolic rather than induced by radiation, once properly quantified. Indeed, even though the absence of histologic signs of embolization in normal liver was demonstrated in a preclinical study (8), the potential embolic effect on tumoral neovascularization is still a matter of debate. Third, Ulrich et al., despite their poor methodology, suggest that “. . .in 99mTc-MAA SPECT no prediction of response in colorectal COPYRIGHT

Radioembolisation and portal vein embolization before resection of large hepatocellular carcinoma.

Resectability of hepatocellular carcinoma in patients with chronic liver disease is dramatically limited by the need to preserve sufficient remnant liver in order to avoid postoperative liver insufficiency. Preoperative treatments aimed at downsizing the tumor and promoting hypertrophy of the future remnant liver may improve resectability and reduce operative morbidity. Here we report the case of a patient with a large hepatocellular carcinoma arising from chronic liver disease. Preoperative treatment, including tumor downsizing with transarterial radioembolization and induction of future remnant liver hypertrophy with right portal vein embolization, resulted in a 53% reduction in tumor volume and compensatory hypertrophy in the contralateral liver. The patient subsequently underwent extended right hepatectomy with no postoperative signs of liver decompensation. Pathological examination demonstrated a margin-free resection and major tumor response. This new therapeutic sequence, combining efficient tumor targeting and subsequent portal vein embolization, could improve the feasibility and safety of major liver resection for hepatocellular carcinoma in patients with liver injury.