Romain Modzelewski

Simultaneous positron emission tomography (PET) assessment of metabolism with 18F-fluoro-2-deoxy-d-glucose (FDG), proliferation with 18F-fluoro-thymidine (FLT), and hypoxia with 18fluoro-misonidazole (F-miso) before and during radiotherapy in patients with non-small-cell lung cancer (NSCLC): A pilot study

OBJECTIVES To investigate the changes in tumour proliferation (using FLT), metabolism (using FDG), and hypoxia (using F-miso) during curative (chemo-) radiotherapy (RT) in patients with non-small-cell lung cancer (NSCLC). PATIENTS AND METHODS Thirty PET scans were performed in five patients (4 males, 1 female) that had histological proof of NSCLC and were candidates for curative-intent RT. Three PET-CT (Biograph S16, Siemens) scans were performed before (t(0)) and during (around dose 46 Gy, t(46)) RT with minimal intervals of 48 h between each PET-CT scan. The tracers used were (18)fluoro-2deoxyglucose (FDG) for metabolism, (18)fluorothymidine (FLT) for proliferation, and (18)F-misonidasole (F-miso) for hypoxia. The 3 image sets obtained at each time point were co-registered (rigid: n=9, elastic: n=1, Leonardo, TrueD, Siemens) using FDG PET-CT as reference. VOIs were delineated (40% SUV(max) values were used as a threshold) for tumours and lymph nodes on FDG PET-CT, and they were automatically pasted on FLT and F-miso PET-CT images. ANOVA and correlation analyses were used for comparison of SUV(max) values. RESULTS Four tumours and twelve nodes were identified on initial FDG PET-CT images. FLT SUV(max) values were significantly lower (p<0.0006) at t(46) in both tumours and nodes. The decrease in FDG SUV(max) values had a trend towards significance (p=0.048). F-Miso SUV(max) values were significantly higher in tumours than in nodes (p=0.02) and did not change during radiotherapy (p=0.39). A significant correlation was observed between FLT and FDG uptake (r=0.56, p<10(-4)) when all data were pooled together, and they remained similar when the before and during RT data were analysed separately. FDG and F-miso uptakes were significantly correlated (r=0.59, p=0.0004) when all data were analysed together. The best fit was obtained after adjusting for lesion type (tumour vs. node). This correlation was observed for the SUV(max) measured during RT (r=0.70, p=0.008) but not for the pre-RT data (r=0.19, p=0.35). The weak correlation between FLT and F-miso uptakes only became significant (r=0.66, p=0.002) when the analysis was restricted to the data acquired during RT. CONCLUSION Three different PET acquisitions can be performed quasi-simultaneously (4-7 days) before and during radiotherapy in patients with NSCLC. Our results at 46 Gy suggest that a fast decrease in the proliferation of both tumours and nodes exists during radiotherapy with differences in metabolism (borderline significant decrease) and hypoxia (stable).

Sarcopenia is an independent prognostic factor in elderly patients with diffuse large B-cell lymphoma treated with immunochemotherapy

Abstract Approximately 25–35% of patients with diffuse large B-cell lymphoma (DLBCL) are older than 70 years. The aim of this study was to investigate the prognostic impact of depletion of skeletal muscle (sarcopenia) in elderly patients with DLBCL. This retrospective analysis included 82 patients with DLBCL older than 70 years and treated with R-CHOP (rituximab, cyclophosphamide, doxorubicin, Oncovin, prednisone) or R-miniCHOP. Sarcopenia was measured by the analysis of stored computed tomography (CT) images at the L3 level at baseline. The surface of the muscular tissues was selected according to the CT Hounsfield unit. This value was normalized for stature in order to calculate the lumbar L3 skeletal muscle index (LSMI, in cm2/m2). The mean age of the population was 78 years. According to the defined cut-offs for LSMI, 45 patients with DLBCL were considered sarcopenic. Sarcopenic patients displayed a higher revised International Prognostic Index (R-IPI) compared with patients without sarcopenia, and were older, with a mean age of 80 years and 77 years, respectively (p = 0.006). With a median follow-up of 39 months, the 2-year overall survival in the sarcopenic population was 46% compared with 84% in the non-sarcopenic group (HR = 3.22; 95% CI = 1.73–5.98; p = 0.0002). In a multivariate analysis, sarcopenia remained predictive of outcome (p = 0.005). Sarcopenia is a relevant and predictive factor in elderly patients with DLBCL treated with rituximab plus chemotherapy.

Prognostic impact of fat tissue loss and cachexia assessed by computed tomography scan in elderly patients with diffuse large B‐cell lymphoma treated with immunochemotherapy

Approximately 30% of DLBCL patients are older than 70 yr. This study evaluated the prognostic impact of a cachexia score (CS) including fat tissue loss (adipopenia) and sarcopenia as assessed by computed tomography (CT scan) in elderly DLBCL patients treated with chemotherapy and rituximab (R).

Does Recombinant Human Thyrotropin-Stimulated Positron Emission Tomography with [18F]Fluoro-2-Deoxy-d-Glucose Improve Detection of Recurrence of Well-Differentiated Thyroid Carcinoma in Patients with Low Serum Thyroglobulin?

BACKGROUND Thyrotropin (TSH) stimulates thyrocyte metabolism, glucose transport, and glycolysis. The interest in using recombinant human TSH (rhTSH) stimulation of fluoro-2-deoxy-D-glucose (FDG) with positron emission tomography (PET) has been shown, but mainly for patients with high serum thyroglobulin (Tg) concentration. We evaluated the use of rhTSH-stimulated PET-FDG in patients with low serum Tg concentration. METHODS Sixty-one PET/computed tomography (CT)-FDG (Biograph Sensation 16; Siemens Medical Solutions, Knoxville, TN) were performed in 44 patients (28 women and 16 men; 51 +/- 16 years) with positive Tg levels, negative or no contributive iodine-131 whole-body scintigraphy results, and no contributive morphological imaging results (ultrasound, magnetic resonance imaging, and CT). Thirty-eight patients had papillary carcinoma and six had follicular thyroid carcinoma. All patients had previously undergone total thyroidectomy and postoperative iodine ablation of thyroid bed remnant tissue. The rhTSH-stimulated PET/CT-FDG (5 MBq/kg) was performed after two 0.9 mg intramuscular doses of rhTSH (Thyrogen; Genzyme) which were administered 48 and 24 hours before imaging, while patients continued levothyroxine (LT(4)). Blood sampling was performed immediately before FDG injection for measurement of serum TSH and Tg concentrations (TSH(1) and Tg(1)) and after 48 hours (TSH(2) and Tg(2)). PET/CT-FDG findings were compared with the Tg: (i) at the initial iodine treatment during T(4) withdrawal (Tg(ini)), (ii) under T(4) (Tg(T4)) within 3 months before the PET/CT-FDG, (iii) with Tg(1), and (iv) with Tg(2). PET/CT-FDG findings were correlated with the findings of histology, iodine-131 whole-body scintigraphy, morphological imaging, or clinical follow-up. RESULTS The mean Tg(ini) was 785 +/- 2707 microg/L for a TSH of 73 +/- 64 mU/L. The mean Tg(T4) was 7 +/- 15 microg/L (T(4) = 195 +/- 59 microg/day; mean TSH of 0.24 +/- 0.57 mU/L). Among the 44 patients, PET/CT-FDG findings were positive in 20 and negative in 24. Among the 61 PET/CT-FDG, 25 PET/CT-FDG were positive (41%). Among the 25 positive PET, the Tg(T4) values were less than 10 microg/L for 19, including 9 true-positive patients (20% of the 44 patients). There was no difference of PET/CT-FDG results (positive vs. negative) as related to the serum Tg concentrations (p = 0.99 for Tg(ini), p = 0.95 for Tg(T4), p = 0.07 for Tg(1), and p = 0.42 for Tg(2)). No relation was observed with PET/CT-FDG results and initial tumor size (p = 0.52) or node metastasis (p = 0.14). CONCLUSION In the diagnosis of recurrent disease in patients with differentiated thyroid carcinoma and low Tg level, the sensitivity of rhTSH-stimulated PET/CT-FDG seems to be low and no correlation was observed between PET/CT-FDG findings and Tg level. However, positive PET-FDG results have been found in 9/44 (20%) patients with serum Tg levels lower than 10 microg/L. Therefore, this series shows that a cutoff value of 10 microg/L for the Tg under T(4) is probably not the best criteria to select patient candidates for PET/CT-FDG examination to detect the recurrence of differentiated thyroid carcinoma.

Areas of High 18F-FDG Uptake on Preradiotherapy PET/CT Identify Preferential Sites of Local Relapse After Chemoradiotherapy for Non–Small Cell Lung Cancer

The high rates of failure in the radiotherapy target volume suggest that patients with stage II or III non–small cell lung cancer (NSCLC) should receive an increased total dose of radiotherapy. Areas of high 18F-FDG uptake on preradiotherapy 18F-FDG PET/CT have been reported to identify intratumor subvolumes at high risk of relapse after radiotherapy. We wanted to confirm these observations on a cohort of patients included in 3 sequential prospective studies. Our aim was to assess an appropriate threshold (percentage of maximum standardized uptake value [SUVmax]) to delineate subvolumes on staging 18F-FDG PET/CT scans assuming that a smaller target volume would facilitate isotoxic radiotherapy dose escalation. Methods: Thirty-nine patients with inoperable stage II or III NSCLC, treated with chemoradiation or with radiotherapy alone, were extracted from 3 prospective studies (ClinicalTrials.gov identifiers NCT01261585, NCT01261598, and RECF0645). All patients underwent 18F-FDG PET/CT at initial staging, before radiotherapy, during radiotherapy, and during systematic follow-up in a single institution. All 18F-FDG PET/CT acquisitions were coregistered on the initial scan. Various subvolumes in the initial acquisition (30%, 40%, 50%, 60%, 70%, 80%, and 90% SUVmax thresholds) and in the 3 subsequent acquisitions (40% and 90% SUVmax thresholds) were pasted on the initial scan and compared. Results: Seventeen patients had a local relapse. The SUVmax measured during radiotherapy was significantly higher in locally relapsed tumors than in locally controlled tumors (mean, 6.8 vs. 4.6; P = 0.02). The subvolumes delineated on initial PET/CT scans with 70%–90% SUVmax thresholds were in good agreement with the recurrent volume at a 40% SUVmax threshold (common volume/baseline volume, 0.60–0.80). The subvolumes delineated on initial PET/CT scans with 30%–60% SUVmax thresholds were in good to excellent agreement with the core volume of the relapse (90% SUVmax threshold) (common volume/recurrent volume and overlap fraction indices, 0.60–0.93). The agreement was moderate (>0.51) when a 70% SUVmax threshold was used to delineate on initial PET/CT scans. Conclusion: High 18F-FDG uptake areas on pretreatment PET/CT scans identify tumor subvolumes at greater risk of relapse in patients with NSCLC treated by concomitant chemoradiation. We propose a 70% SUVmax threshold to delineate areas of high 18F-FDG uptake on initial PET/CT scans as the target volumes for potential radiotherapy dose escalation.

Interobserver Agreement of Qualitative Analysis and Tumor Delineation of 18F-Fluoromisonidazole and 3′-Deoxy-3′-18F-Fluorothymidine PET Images in Lung Cancer

As the preparation phase of a multicenter clinical trial using 18F-fluoro-2-deoxy-d-glucose (18F-FDG), 18F-fluoromisonidazole (18F-FMISO), and 3′-deoxy-3′-18F-fluorothymidine (18F-FLT) in non–small cell lung cancer (NSCLC) patients, we investigated whether 18 nuclear medicine centers would score tracer uptake intensity similarly and define hypoxic and proliferative volumes for 1 patient and we compared different segmentation methods. Methods: Ten 18F-FDG, ten 18F-FMISO, and ten 18F-FLT PET/CT examinations were performed before and during curative-intent radiotherapy in 5 patients with NSCLC. The gold standards for uptake intensity and volume delineation were defined by experts. The between-center agreement (18 nuclear medicine departments connected with a dedicated network, SFMN-net [French Society of Nuclear Medicine]) in the scoring of uptake intensity (5-level scale, then divided into 2 levels: 0, normal; 1, abnormal) was quantified by κ-coefficients (κ). The volumes defined by different physicians were compared by overlap and κ. The uptake areas were delineated with 22 different methods of segmentation, based on fixed or adaptive thresholds of standardized uptake value (SUV). Results: For uptake intensity, the κ values between centers were, respectively, 0.59 for 18F-FDG, 0.43 for 18F-FMISO, and 0.44 for 18F-FLT using the 5-level scale; the values were 0.81 for 18F-FDG and 0.77 for both 18F-FMISO and 18F-FLT using the 2-level scale. The mean overlap and mean κ between observers were 0.13 and 0.19, respectively, for 18F-FMISO and 0.2 and 0.3, respectively, for 18F-FLT. The segmentation methods yielded significantly different volumes for 18F-FMISO and 18F-FLT (P < 0.001). In comparison with physicians, the best method found was 1.5 × maximum SUV (SUVmax) of the aorta for 18F-FMISO and 1.3 × SUVmax of the muscle for 18F-FLT. The methods using the SUV of 1.4 and the method using 1.5 × the SUVmax of the aorta could be used for 18F-FMISO and 18F-FLT. Moreover, for 18F-FLT, 2 other methods (adaptive threshold based on 1.5 or 1.6 × muscle SUVmax) could be used. Conclusion: The reproducibility of the visual analyses of 18F-FMISO and 18F-FLT PET/CT images was demonstrated using a 2-level scale across 18 centers, but the interobserver agreement was low for the 18F-FMISO and 18F-FLT volume measurements. Our data support the use of a fixed threshold (1.4) or an adaptive threshold using the aorta background to delineate the volume of increased 18F-FMISO or 18F-FLT uptake. With respect to the low tumor-on-background ratio of these tracers, we suggest the use of a fixed threshold (1.4).

Segmentation of heterogeneous or small FDG PET positive tissue based on a 3D-locally adaptive random walk algorithm

A segmentation algorithm based on the random walk (RW) method, called 3D-LARW, has been developed to delineate small tumors or tumors with a heterogeneous distribution of FDG on PET images. Based on the original algorithm of RW [1], we propose an improved approach using new parameters depending on the Euclidean distance between two adjacent voxels instead of a fixed one and integrating probability densities of labels into the system of linear equations used in the RW. These improvements were evaluated and compared with the original RW method, a thresholding with a fixed value (40% of the maximum in the lesion), an adaptive thresholding algorithm on uniform spheres filled with FDG and FLAB method, on simulated heterogeneous spheres and on clinical data (14 patients). On these three different data, 3D-LARW has shown better segmentation results than the original RW algorithm and the three other methods. As expected, these improvements are more pronounced for the segmentation of small or tumors having heterogeneous FDG uptake.

3D random walk based segmentation for lung tumor delineation in PET imaging

This article presents a segmentation approach based on random walk (RW) method to delineate tumors having inhomogeneous activity distributions of 18FDG on Positron Emission Tomography (PET) images. Based on the original algorithm of RW [1], we propose an improved approach using an adaptive parameter instead of a fixed one and integrating probability densities of label into the system of linear equations used in the RW. The proposed segmentation method initializes automatically seeds in tumor voxels using Fuzzy-C Means (FCM), and then delineates the tumor volume using the improved RW. The performances of the algorithm were assessed on PET images of a physical phantom, covering a range of hot spheres simulating tumor lesions of volume [0.99-97.3 mL] and contrast [2-7.7] for a voxel size of 4.1×4.1×2.0 mm3. A comparison study with a fixed threshold value of 40 % [2] and an adaptative thresholding algorithm [3] have been carried out. Results show that the proposed method is more effective than the other methodologies for spherical volume measurement. The good performances of the improved RW method have been also confirmed on data of three patients having heterogeneous 18FDG uptakes.

IODA: an Input/Output Deep Architecture for image labeling

In this paper, we propose a deep neural network (DNN) architecture called Input Output Deep Architecture (IODA) for solving the problem of image labeling. IODA directly links a whole image to a whole label map, assigning a label to each pixel using a single neural network forward step. Instead of designing a handcrafted a priori model on labels (such as an atlas in the medical domain), we propose to automatically learn the dependencies between labels. The originality of IODA is to transpose DNN input pre-training trick to the output space, in order to learn a high level representation of labels. It allows a fast image labeling inside a fully neural network framework, without the need of any preprocessing such as feature designing or output coding. In this paper, IODA is applied on both a toy texture problem and a real-world medical image dataset, showing promising results. We provide an open source implementation of IODA.1,2

Baseline Total Metabolic Tumor Volume measured with fixed or different adaptive thresholding methods equally predicts outcome in Peripheral T cell lymphoma.

The purpose of this study was to compare in a large series of peripheral T cell lymphoma, as a model of diffuse disease, the prognostic value of baseline total metabolic tumor volume (TMTV) measured on 18F-FDG PET/CT with adaptive thresholding methods with TMTV measured with a fixed 41% SUVmax threshold method. Methods: One hundred six patients with peripheral T cell lymphoma, staged with PET/CT, were enrolled from 5 Lymphoma Study Association centers. In this series, TMTV computed with the 41% SUVmax threshold is a strong predictor of outcome. On a dedicated workstation, we measured the TMTV with 4 adaptive thresholding methods based on characteristic image parameters: Daisne (Da) modified, based on signal-to-background ratio; Nestle (Ns), based on tumor and background intensities; Fit, including a 3-dimensional geometric model based on spatial resolution (Fit); and Black (Bl), based on mean SUVmax. The TMTV values obtained with each adaptive method were compared with those obtained with the 41% SUVmax method. Their respective prognostic impacts on outcome prediction were compared using receiver-operating-characteristic (ROC) curve analysis and Kaplan–Meier survival curves. Results: The median value of TMTV41%, TMTVDa, TMTVNs, TMTVFit, and TMTVBl were, respectively, 231 cm3 (range, 5–3,824), 175 cm3 (range, 8–3,510), 198 cm3 (range, 3–3,934), 175 cm3 (range, 8–3,512), and 333 cm3 (range, 3–5,113). The intraclass correlation coefficients were excellent, from 0.972 to 0.988, for TMTVDa, TMTVFit, and TMTVNs, and less good for TMTVBl (0.856). The mean differences obtained from the Bland–Altman plots were 48.5, 47.2, 19.5, and −253.3 cm3, respectively. Except for Black, there was no significant difference within the methods between the ROC curves (P > 0.4) for progression-free survival and overall survival. Survival curves with the ROC optimal cutoff for each method separated the same groups of low-risk (volume ≤ cutoff) from high-risk patients (volume > cutoff), with similar 2-y progression-free survival (range, 66%–72% vs. 26%–29%; hazard ratio, 3.7–4.1) and 2-y overall survival (79%–83% vs. 50%–53%; hazard ratio, 3.0–3.5). Conclusion: The prognostic value of TMTV remained quite similar whatever the methods, adaptive or 41% SUVmax, supporting its use as a strong prognosticator in lymphoma. However, for implementation of TMTV in clinical trials 1 single method easily applicable in a multicentric PET review must be selected and kept all along the trial.