Search

Background and Purpose: To promote the development of auto-segmentation methods for head and neck (HaN) radiation treatment (RT) planning that exploit the information of computed tomography (CT) and magnetic resonance (MR) imaging modalities, we organized HaN-Seg: The Head and Neck Organ-at-Risk CT and MR Segmentation Challenge., Materials and Methods: The challenge task was to automatically segment 30 organs-at-risk (OARs) of the HaN region in 14 withheld test cases given the availability of 42 publicly available training cases. Each case consisted of one contrast-enhanced CT and one T1-weighted MR image of the HaN region of the same patient, with up to 30 corresponding reference OAR delineation masks. The performance was evaluated in terms of the Dice similarity coefficient (DSC) and 95-percentile Hausdorff distance (HD 95 ), and statistical ranking was applied for each metric by pairwise comparison of the submitted methods using the Wilcoxon signed-rank test., Results: While 23 teams registered for the challenge, only seven submitted their methods for the final phase. The top-performing team achieved a DSC of 76.9 % and a HD 95 of 3.5 mm. All participating teams utilized architectures based on U-Net, with the winning team leveraging rigid MR to CT registration combined with network entry-level concatenation of both modalities., Conclusion: This challenge simulated a real-world clinical scenario by providing non-registered MR and CT images with varying fields-of-view and voxel sizes. Remarkably, the top-performing teams achieved segmentation performance surpassing the inter-observer agreement on the same dataset. These results set a benchmark for future research on this publicly available dataset and on paired multi-modal image segmentation in general., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Thoracic radiation intensification is debated in patients with stage III non-small-cell lung cancer (NSCLC). We aimed to assess the activity and safety of a boost radiotherapy dose up to 74 Gy in a functional sub-volume given according to on-treatment [ 18 F]fluorodeoxyglucose ([ 18 F]FDG)-PET results., Methods: In this multicentre, randomised, controlled non-comparative phase 2 trial, we recruited patients aged 18 years or older with inoperable stage III NSCLC without EGFR mutation or ALK rearrangement with an Eastern Cooperative Oncology Group performance status of 0-1, and who were affiliated with or a beneficiary of a social benefit system, with evaluable tumour or node lesions, preserved lung function, and who were amenable to curative-intent radiochemotherapy. Patients were randomly allocated using a central interactive web-response system in a non-masked method (1:1; minimisation method used [random factor of 0·8]; stratified by radiotherapy technique [intensity-modulated radiotherapy vs three-dimensional conformal radiotherapy] and by centre at which patients were treated) either to the experimental adaptive radiotherapy group A, in which only patients with positive residual metabolism on [ 18 F]FDG-PET at 42 Gy received a boost radiotherapy (up to 74 Gy in 33 fractions), with all other patients receiving standard radiotherapy dosing (66 Gy in 33 fractions over 6·5 weeks), or to the standard radiotherapy group B (66 Gy in 33 fractions) over 6·5 weeks. All patients received two cycles of induction platinum-based chemotherapy cycles (paclitaxel 175 mg/m 2 intravenously once every 3 weeks and carboplatin area under the curve [AUC]=6 once every 3 weeks, or cisplatin 80 mg/m 2 intravenously once every 3 weeks and vinorelbine 30 mg/m 2 intravenously on day 1 and 60 mg/m 2 orally [or 30 mg/m 2 intravenously] on day 8 once every 3 weeks). Then they concomitantly received radiochemotherapy with platinum-based chemotherapy (three cycles for 8 weeks, with once per week paclitaxel 40 mg/m 2 intravenously and carboplatin AUC=2 or cisplatin 80 mg/m 2 intravenously and vinorelbine 20 mg/m 2 intravenously on day 1 and 40 mg/m 2 orally (or 20 mg/m 2 intravenously) on day 8 in 21-day cycles). The primary endpoint was the 15-month local control rate in the eligible patients who received at least one dose of concomitant radiochemotherapy. This RTEP7-IFCT-1402 trial is registered with ClinicalTrials.gov (NCT02473133), and is ongoing., Findings: From Nov 12, 2015, to July 7, 2021, we randomly assigned 158 patients (47 [30%] women and 111 [70%] men) to either the boosted radiotherapy group A (81 [51%]) or to the standard radiotherapy group B (77 [49%)]. In group A, 80 (99%) patients received induction chemotherapy and 68 (84%) received radiochemotherapy, of whom 48 (71%) with residual uptake on [ 18 F]FDG-PET after 42 Gy received a radiotherapy boost. In group B, all 77 patients received induction chemotherapy and 73 (95%) received radiochemotherapy. At the final analysis, the median follow-up for eligible patients who received radiochemotherapy (n=140) was 45·1 months (95% CI 39·3-48·3). The 15-month local control rate was 77·6% (95% CI 67·6-87·6%) in group A and 71·2% (95% CI 60·8-81·6%) in group B. Acute (within 90 days from radiochemotherapy initiation) grade 3-4 adverse events were observed in 20 (29%) of 68 patients in group A and 33 (45%) of 73 patients in group B, including serious adverse events in five (7%) patients in group A and ten (14%) patients in group B. The most common grade 3-4 adverse events were febrile neutropenia (seven [10%] of 68 in group A vs 16 [22%] of 73 in group B), and anaemia (five [7%] vs nine [12%]). In the acute phase, two deaths (3%) occurred in group B (one due to a septic shock related to chemotherapy, and the other due to haemotypsia not related to study treatment), and no deaths occurred in group A. After 90 days, one additional treatment-unrelated death occurred in group A and two deaths events occurred in group B (one radiation pneumonitis and one pneumonia unrelated to treatment)., Interpretation: A thoracic radiotherapy boost, based on interim [ 18 F]FDG-PET, led to a meaningful local control rate with no difference in adverse events between the two groups in organs at risk, in contrast with previous attempts at thoracic radiation intensification, warranting a randomised phase 3 evaluation of such [ 18 F]FDG-PET-guided radiotherapy dose adaptation in patients with stage III NSCLC., Funding: Programme Hospitalier de Recherche Clinique National 2014., Competing Interests: Declaration of interests EM declared payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from Varian Medical Systems, AstraZeneca, MSD, Janssen, and Sanofi; support for attending meetings or travel, or both, from Ipsen, Janssen, and AstraZeneca; and participation on a data safety monitoring board or advisory board for AstraZeneca and Janssen. IB-R declares payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from Novartis 3A and Curium; payment for expert testimony from Curium; and support for attending meetings or travel, or both, from Novartis 3A. CLP declares payment or honoraria to her institution for lectures, presentations, speakers bureaus, manuscript writing, or educational events from AstraZeneca and Amgen; support for attending meetings or travel, or both, paid to her institution from Janssen and Roche; and participation on a data safety monitoring board or advisory board paid to her institution for AstraZeneca, Varian, MSD, and Roche. EG-L declares payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from Amgen, AstraZeneca, Ipsen, Janssen, Lilly, MSD, Novartis, Pfizer, Sanofi, and Takeda; and support for attending meetings or travel, or both, from Takeda, MSD, AstraZeneca, and Roche. CA-V declares support for attending meetings or travel, or both, from Roche, Sanofi, MSD, BMS, Lilly, Pfizer, AstraZeneca, Janssen, and Abbvie; and participation on a data safety monitoring board or advisory board for Roche, Sanofi, MSD, BMS, Lilly, Pfizer, AstraZeneca, Janssen, and Abbvie. ALan and EA are employees of the French Intergroup (Intergroupe Francophone de Cancérologie Thoracique). GZ declares consulting fees paid to his institution from AstraZeneca, BMS, Takeda, and Roche; payment or honoraria to his institution for lectures, presentations, speakers bureaus, manuscript writing, or educational events from AstraZeneca, Inventiva, BMS, and Pfizer; support for attending meetings or travel, or both, from Roche, BMS, Abbvie, Pfizer, and AstraZeneca; and receipt of equipment, materials, drugs, medical writing, gifts, or other services to his institution by Foundation Roche. All other authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies.)

This prospective study aimed to investigate the prognostic effect of sarcopenia, geriatric, and nutritional status in older patients with diffuse large B-cell lymphoma (DLBCL). Ninety-five patients with DLBCL older than 70 years who were treated with immunochemotherapy were included. The lumbar L3 skeletal muscle index (L3-SMI) was measured by computed tomography at baseline, and sarcopenia was defined as low L3-SMI. Geriatric assessment included G8 score, CIRS-G scale, Timed Up and Go test, and instrumental activity of daily living. Nutritional status was assessed using the Mini Nutritional Assessment and the body mass index, and several scores used in the literature incorporating nutritional and inflammatory biomarkers, namely the Nutritional and inflammatory status (NIS), Geriatric Nutritional Risk Index, Prognostic Nutritional Index, and Glasgow Prognostic Score.Fifty-three patients were considered sarcopenic. Sarcopenic patients displayed higher levels of inflammation markers and lower levels of prealbumin than non-sarcopenic patients. Sarcopenia was associated with NIS, but was not associated with severe adverse events and treatment disruptions. They were, however, more frequent among patients with elevated NIS. Sarcopenia did not appear in this study as a prognostic factor for progression-free survival (PFS) or overall survival (OS). However, NIS emerged as predictive of the outcome with a 2-year PFS rate of 88% in the NIS ≤ 1 group and 49% in the NIS > 1 group and a significant effect in a multivariate analysis for both PFS (p = 0.049) and OS (HR = 9.61, CI 95% = [1.03-89.66], p = 0.04). Sarcopenia was not associated with adverse outcomes, but was related to NIS, which appeared to be an independent prognostic factor., (© 2023. The Author(s).)

Background & Aims: We aimed to evaluate body composition (BC) by computed tomography (CT) in hematologic malignancy (HM) patients admitted to the intensive care unit (ICU) for sepsis or septic shock., Methods: We retrospectively assessed BC and its impact on outcome of 186 patients at the 3rd lumbar (L3) and 12th thoracic vertebral levels (T12) using CT-scan performed before ICU admission., Results: The median patient age was 58.0 [47; 69] years. Patients displayed adverse clinical characteristics at admission with median [q1; q3] SAPS II and SOFA scores of 52 [40; 66] and 8 [5; 12], respectively. The mortality rate in the ICU was 45.7%. Overall survival rates at 1 month after admission in the pre-existing sarcopenic vs. non pre-existing sarcopenic patients were 47.9% (95% CI [37.6; 61.0]) and 55.0% (95% CI [41.6; 72.8]), p = 0.99), respectively, at the L3 level and 48.4% (95% CI [40.4; 58.0]) vs. 66.7% (95% CI [51.1; 87.0]), p = 0.062), respectively, at the T12 level., Conclusions: Sarcopenia is assessable by CT scan at both the T12 and L3 levels and is highly prevalent in HM patients admitted to the ICU for severe infections. Sarcopenia may contribute to the high mortality rate in the ICU in this population., Competing Interests: Declaration of competing interest No conflicts of interest., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Brain tumor is one of the leading causes of cancer death. The high-grade brain tumors are easier to recurrent even after standard treatment. Therefore, developing a method to predict brain tumor recurrence location plays an important role in the treatment planning and it can potentially prolong patient's survival time. There is still little work to deal with this issue. In this paper, we present a deep learning-based brain tumor recurrence location prediction network. Since the dataset is usually small, we propose to use transfer learning to improve the prediction. We first train a multi-modal brain tumor segmentation network on the public dataset BraTS 2021. Then, the pre-trained encoder is transferred to our private dataset for extracting the rich semantic features. Following that, a multi-scale multi-channel feature fusion model and a nonlinear correlation learning module are developed to learn the effective features. The correlation between multi-channel features is modeled by a nonlinear equation. To measure the similarity between the distributions of original features of one modality and the estimated correlated features of another modality, we propose to use Kullback-Leibler divergence. Based on this divergence, a correlation loss function is designed to maximize the similarity between the two feature distributions. Finally, two decoders are constructed to jointly segment the present brain tumor and predict its future tumor recurrence location. To the best of our knowledge, this is the first work that can segment the present tumor and at the same time predict future tumor recurrence location, making the treatment planning more efficient and precise. The experimental results demonstrated the effectiveness of our proposed method to predict the brain tumor recurrence location from the limited dataset., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Purpose: The delineation of target volumes and organs at risk is the main source of uncertainty in radiation therapy. Numerous interobserver variability (IOV) studies have been conducted, often with unclear methodology and nonstandardized reporting. We aimed to identify the parameters chosen in conducting delineation IOV studies and assess their performances and limits., Methods and Materials: We conducted a systematic literature review to highlight major points of heterogeneity and missing data in IOV studies published between 2018 and 2021. For the main used metrics, we did in silico analyses to assess their limits in specific clinical situations., Results: All disease sites were represented in the 66 studies examined. Organs at risk were studied independently of tumor site in 29% of reviewed IOV studies. In 65% of studies, statistical analyses were performed. No gold standard (GS; ie, reference) was defined in 36% of studies. A single expert was considered as the GS in 21% of studies, without testing intraobserver variability. All studies reported both absolute and relative indices, including the Dice similarity coefficient (DSC) in 68% and the Hausdorff distance (HD) in 42%. Limitations were shown in silico for small structures when using the DSC and dependence on irregular shapes when using the HD. Variations in DSC values were large between studies, and their thresholds were inconsistent. Most studies (51%) included 1 to 10 cases. The median number of observers or experts was 7 (range, 2-35). The intraclass correlation coefficient was reported in only 9% of cases. Investigating the feasibility of studying IOV in delineation, a minimum of 8 observers with 3 cases, or 11 observers with 2 cases, was required to demonstrate moderate reproducibility., Conclusions: Implementation of future IOV studies would benefit from a more standardized methodology: clear definitions of the gold standard and metrics and a justification of the tradeoffs made in the choice of the number of observers and number of delineated cases should be provided., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Intratumoral hypoxia is associated with a poor prognosis and poor response to treatment in head and neck cancers. Its identification would allow for increasing the radiation dose to hypoxic tumor subvolumes. 18F-FMISO PET imaging is the gold standard; however, quantitative multiparametric MRI could show the presence of intratumoral hypoxia. Thus, 16 patients were prospectively included and underwent 18F-FDG PET/CT, 18F-FMISO PET/CT, and multiparametric quantitative MRI (DCE, diffusion and relaxometry T1 and T2 techniques) in the same position before treatment. PET and MRI sub-volumes were segmented and classified as hypoxic or non-hypoxic volumes to compare quantitative MRI parameters between normoxic and hypoxic volumes. In total, 13 patients had hypoxic lesions. The Dice, Jaccard, and overlap fraction similarity indices were 0.43, 0.28, and 0.71, respectively, between the FDG PET and MRI-measured lesion volumes, showing that the FDG PET tumor volume is partially contained within the MRI tumor volume. The results showed significant differences in the parameters of SUV in FDG and FMISO PET between patients with and without measurable hypoxic lesions. The quantitative MRI parameters of ADC, T1 max mapping and T2 max mapping were different between hypoxic and normoxic subvolumes. Quantitative MRI, based on free water diffusion and T1 and T2 mapping, seems to be able to identify intra-tumoral hypoxic sub-volumes for additional radiotherapy doses.

Background: Molecular factors influence relapse patterns in glioblastoma. The hotspot mutation located at position 289 of the extracellular domain of the epidermal growth factor receptor (EGFR A289mut ) is associated with a more infiltrative phenotype. The primary objective of this study was to explore the impact of the EGFR A289 mutation on the pattern of relapse after chemoradiotherapy-based treatment of patients suffering from newly diagnosed glioblastoma., Patients and Methods: An ancillary study from a prospective cohort of patients suffering from glioblastoma was conducted. All patients received radiotherapy and concomitant temozolomide. The population was divided into two groups according to EGFR A289 status (mutated versus wild-type). The primary endpoint was the overlap score (varying from 0 to 1) between the initial irradiated tumor volume (Vinit) and the relapse volume (Vr). Secondary endpoints explored the impact of EGFR A289mut on survival., Results: One hundred twenty-eight patients were included and analyzed: 11% had EGFR A289mut glioblastoma (n = 14/128). EGFR A289mut glioblastomas had a relapse pattern that was more marginal than EGFR A289wt glioblastomas: a median overlap score Vinit/Vr of 0.96 was observed in the EGFR A289mut group versus 1 in the EGFR A289wt group (P = 0.05). Half of the population with EGFR A289mut tumor (n = 7/14) had a marginal relapse (i.e. overlap score Vr/Vinit ≤ 0.95) compared to 23.7% (n = 27/114) in the EGFR A289wt group, P = 0.035. EGFR A289mut did not influence survival., Conclusion: We highlighted a link between the EGFR A289 mutation and the relapse pattern in glioblastoma. The independent role of EGFR A289mut and its clinical implication should now be explored in further studies., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: The aim of the study was to prospectively evaluate different biomarkers to identify the most reliable for anticipating complications after major abdominal surgery for digestive cancer in older patients and compare their performance to the existing definition and screening algorithm of sarcopenia from EWGSOP., Methods: Ninety-five consecutive patients aged over 65 years who underwent elective surgery for digestive cancer were prospectively included in the SAXO study. Sarcopenia was defined according to EWGSOP criteria (four level from no sarcopenia to severe sarcopenia). Strength and physical performance were evaluated with the handgrip test (HGT) and gait speed test (GST), respectively. CT scan analysis was used to calculate the skeletal muscle index (SMI), intermuscular adipose tissue (IMAT), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT). Measures were adjusted to body mass index (BMI). Complication grading was performed using the Clavien‒Dindo classification. A doubly robust estimator with multivariable regression was used to limit bias., Results: Sixteen patients presented with sarcopenia. Adjusted to BMI, sarcopenic patients had an increased IMAT BMI (0.35 vs. 0.22; p = 0.003) and increased VAT BMI (7.85 vs. 6.13; p = 0.048). In multivariable analysis, IMAT was an independent risk factor for minor and severe complications (OR = 1.298; 95% CI [1.031: 1.635] p = 0.027), while an increased SAT area was a protective factor (OR = 0.982; 95% CI [0.969: 0.995] p = 0.007). Twenty-two patients were obese (BMI ≥30 kg/m 2 ). While no association was observed between obesity and sarcopenia (according to EWGSOP definition), obese patients had increased IMAT BMI (0.31 vs. 0.23; p = 0.010) and VAT BMI (8.40 vs. 6.49; p = 0.019). The combination of SAT, VAT and IMAT performed well to anticipate severe complication (AUC = 0.759) while AUC of EWGSOP 2010 and 2019 algorithm were 0.660 and 0.519, respectively., Discussion: Non-invasive and imaging related measures of IMAT, SAT and VAT seems to be valuable tools to refine risk-assessment of older patients in surgery and specially to detect myosteatosis in obese ones., Competing Interests: Declaration of competing interest None of the authors has a conflict of interest to declare., (Copyright © 2022. Published by Elsevier Ltd.)

Background and Objectives: Predicting patient response to treatment and survival in oncology is a prominent way towards precision medicine. To this end, radiomics has been proposed as a field of study where images are used instead of invasive methods. The first step in radiomic analysis in oncology is lesion segmentation. However, this task is time consuming and can be physician subjective. Automated tools based on supervised deep learning have made great progress in helping physicians. However, they are data hungry, and annotated data remains a major issue in the medical field where only a small subset of annotated images are available., Methods: In this work, we propose a multi-task, multi-scale learning framework to predict patient's survival and response. We show that the encoder can leverage multiple tasks to extract meaningful and powerful features that improve radiomic performance. We also show that subsidiary tasks serve as an inductive bias so that the model can better generalize., Results: Our model was tested and validated for treatment response and survival in esophageal and lung cancers, with an area under the ROC curve of 77% and 71% respectively, outperforming single-task learning methods., Conclusions: Multi-task multi-scale learning enables higher performance of radiomic analysis by extracting rich information from intratumoral and peritumoral regions., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Despite significant therapeutic advances in the treatment of locally advanced inoperable non-small cell lung cancer (NSCLC), notably through adjuvant immunotherapy, the rate of therapeutic failure remains high. The use of positron emission tomography with fluorodeoxyglucose (FDG-PET), respiratory motion and intensity modulated radiotherapy (IMRT) have led to therapeutic improvements with reduced toxicity and better local control. The optimal dose to be delivered remains unknown due to discordant results of studies for almost 20 years and the way to define the area to benefit from a dose increase (whole volume, subvolume defined by pre- or per-radiotherapy PET)., (Copyright © 2022. Published by Elsevier Masson SAS.)

Gestational diabetes mellitus (GDM), which is defined as a state of hyperglycemia that is first recognized during pregnancy, is currently the most common medical complication in pregnancy. GDM affects approximately 15% of pregnancies worldwide, accounting for approximately 18 million births annually. Mothers with GDM are at risk of developing gestational hypertension, pre-eclampsia and termination of pregnancy via Caesarean section. In addition, GDM increases the risk of complications, including cardiovascular disease, obesity and impaired carbohydrate metabolism, leading to the development of type 2 diabetes (T2DM) in both the mother and infant. The increase in the incidence of GDM also leads to a significant economic burden and deserves greater attention and awareness. A deeper understanding of the risk factors and pathogenesis becomes a necessity, with particular emphasis on the influence of SARS-CoV-2 and diagnostics, as well as an effective treatment, which may reduce perinatal and metabolic complications. The primary treatments for GDM are diet and increased exercise. Insulin, glibenclamide and metformin can be used to intensify the treatment. This paper provides an overview of the latest reports on the epidemiology, pathogenesis, diagnosis and treatment of GDM based on the literature.

The aim of the study was to compare the perception of stress and the characteristic coping-strategies among students in the context of the different anti-pandemic measures taken in Belarus, Poland, and the Russian exclave of Kaliningrad. A cross-sectional online survey using standardized questionnaires (Perceived Stress Scale-PSS-10 and Brief-COPE-Mini-COPE inventory) was conducted among 3113 students of seven universities in three neighboring regions on both sides of the eastern border of the EU. The groups that are the most prone to stress are the Polish and Russians students. Among the students from Belarus, 122 (13.7%) have high levels of stress symptoms. Among the respondents from Poland-238 (19.4%), and 191 (19.2%) from Kaliningrad have high levels of stress, respectively. The different approaches of the authorities to the COVID-19 pandemic diversified the choice of students' stress coping strategies. The behavior of the students from Kaliningrad and Poland was similar. The Belarusian students used active coping strategies less often, while an avoidance-focused style, and denial were more frequent. The neglect of restrictive anti-pandemic measures by the Belarusian students was manifested by a higher incidence of disease and minimal use of vaccinations.

Objective: To evaluate if a deep learning model can be used to characterise breast cancers on contrast-enhanced spectral mammography (CESM)., Methods: This retrospective mono-centric study included biopsy-proven invasive cancers with an enhancement on CESM. CESM images include low-energy images (LE) comparable to digital mammography and dual-energy subtracted images (DES) showing tumour angiogenesis. For each lesion, histologic type, tumour grade, estrogen receptor (ER) status, progesterone receptor (PR) status, HER-2 status, Ki-67 proliferation index, and the size of the invasive tumour were retrieved. The deep learning model used was a CheXNet-based model fine-tuned on CESM dataset. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was calculated for the different models: images by images and then by majority voting combining all the incidences for one tumour., Results: In total, 447 invasive breast cancers detected on CESM with pathological evidence, in 389 patients, which represented 2460 images analysed, were included. Concerning the ER, the deep learning model on the DES images had an AUC of 0.83 with the image-by-image analysis and of 0.85 for the majority voting. For the triple-negative analysis, a high AUC was observable for all models, in particularity for the model on LE images with an AUC of 0.90 for the image-by-image analysis and 0.91 for the majority voting. The AUC for the other histoprognostic factors was lower., Conclusion: Deep learning analysis on CESM has the potential to determine histoprognostic tumours makers, notably estrogen receptor status, and triple-negative receptor status., Key Points: • A deep learning model developed for chest radiography was adapted by fine-tuning to be used on contrast-enhanced spectral mammography. • The adapted models allowed to determine for invasive breast cancers the status of estrogen receptors and triple-negative receptors. • Such models applied to contrast-enhanced spectral mammography could provide rapid prognostic and predictive information., (© 2022. The Author(s), under exclusive licence to European Society of Radiology.)

Background: PET/CT image quality is directly influenced by the F-18-FDG injected activity. The higher the injected activity, the less noise in the reconstructed images but the more radioactive staff exposition. A new FDA cleared software has been introduced to obtain clinical PET images, acquired at 25% of the count statistics considering US practices. Our aim is to determine the limits of a deep learning based denoising algorithm (SubtlePET) applied to statistically reduced PET raw data from 3 different last generation PET scanners in comparison to the regular acquisition in phantom and patients, considering the European guidelines for radiotracer injection activities. Images of low and high contrasted (SBR = 2 and 5) spheres of the IEC phantom and high contrast (SBR = 5) of micro-spheres of Jaszczak phantom were acquired on 3 different PET devices. 110 patients with different pathologies were included. The data was acquired in list-mode and retrospectively reconstructed with the regular acquisition count statistic (PET100), 50% reduction in counts (PET50) and 66% reduction in counts (PET33). These count reduced images were post-processed with SubtlePET to obtain PET50 + SP and PET33 + SP images. Patient image quality was scored by 2 senior nuclear physicians. Peak-signal-to-Noise and Structural similarity metrics were computed to compare the low count images to regular acquisition (PET100)., Results: SubtlePET reliably denoised the images and maintained the SUV max values in PET50 + SP. SubtlePET enhanced images (PET33 + SP) had slightly increased noise compared to PET100 and could lead to a potential loss of information in terms of lesion detectability. Regarding the patient datasets, the PET100 and PET50 + SP were qualitatively comparable. The SubtlePET algorithm was able to correctly recover the SUV max values of the lesions and maintain a noise level equivalent to full-time images., Conclusion: Based on our results, SubtlePET is adapted in clinical practice for half-time or half-dose acquisitions based on European recommended injected dose of 3 MBq/kg without diagnostic confidence loss., (© 2022. The Author(s).)

It is proven that radiomic characteristics extracted from the tumor region are predictive. The first step in radiomic analysis is the segmentation of the lesion. However, this task is time consuming and requires a highly trained physician. This process could be automated using computer-aided detection (CAD) tools. Current state-of-the-art methods are trained in a supervised learning setting, which requires a lot of data that are usually not available in the medical imaging field. The challenge is to train one model to segment different types of tumors with only a weak segmentation ground truth. In this work, we propose a prediction framework including a 3D tumor segmentation in positron emission tomography (PET) images, based on a weakly supervised deep learning method, and an outcome prediction based on a 3D-CNN classifier applied to the segmented tumor regions. The key step is to locate the tumor in 3D. We propose to (1) calculate two maximum intensity projection (MIP) images from 3D PET images in two directions, (2) classify the MIP images into different types of cancers, (3) generate the class activation maps through a multitask learning approach with a weak prior knowledge, and (4) segment the 3D tumor region from the two 2D activation maps with a proposed new loss function for the multitask. The proposed approach achieves state-of-the-art prediction results with a small data set and with a weak segmentation ground truth. Our model was tested and validated for treatment response and survival in lung and esophageal cancers on 195 patients, with an area under the receiver operating characteristic curve (AUC) of 67% and 59%, respectively, and a dice coefficient of 73% and 0.77% for tumor segmentation.

In this paper, we propose to quantitatively compare loss functions based on parameterized Tsallis-Havrda-Charvat entropy and classical Shannon entropy for the training of a deep network in the case of small datasets which are usually encountered in medical applications. Shannon cross-entropy is widely used as a loss function for most neural networks applied to the segmentation, classification and detection of images. Shannon entropy is a particular case of Tsallis-Havrda-Charvat entropy. In this work, we compare these two entropies through a medical application for predicting recurrence in patients with head-neck and lung cancers after treatment. Based on both CT images and patient information, a multitask deep neural network is proposed to perform a recurrence prediction task using cross-entropy as a loss function and an image reconstruction task. Tsallis-Havrda-Charvat cross-entropy is a parameterized cross-entropy with the parameter α. Shannon entropy is a particular case of Tsallis-Havrda-Charvat entropy for α=1. The influence of this parameter on the final prediction results is studied. In this paper, the experiments are conducted on two datasets including in total 580 patients, of whom 434 suffered from head-neck cancers and 146 from lung cancers. The results show that Tsallis-Havrda-Charvat entropy can achieve better performance in terms of prediction accuracy with some values of α.

Hypoxic areas are typically resistant to treatment. However, the fluorine-18-fluoroazomycin-arabinoside (FAZA) and fluorine 18 misonidazole (FMISO) tracers have never been compared in non small cell lung cancer (NSCLC). This study compares the capability of 18F-FAZA PET/CT with that of 18F-FMISO PET/CT for detecting hypoxic tumour regions in early and locally advanced NSCLC patients. We prospectively evaluated patients who underwent preoperative PET scans before surgery for localised NSCLC (i.e., fluorodeoxyglucose (FDG)-PET, FMISO-PET, and FAZA-PET). The PET data of the three tracers were compared with each other and then compared to immunohistochemical analysis (GLUT-1, CAIX, LDH-5, and HIF1-Alpha) after tumour resection. Overall, 19 patients with a mean age of 68.2 ± 8 years were included. There were 18 lesions with significant uptake (i.e., SUVmax >1.4) for the F-MISO and 17 for FAZA. The mean SUVmax was 3 (±1.4) with a mean volume of 25.8 cc (±25.8) for FMISO and 2.2 (±0.7) with a mean volume of 13.06 cc (±13.76) for FAZA. The SUVmax of F-MISO was greater than that of FAZA ( p = 0.0003). The SUVmax of F-MISO shows a good correlation with that of FAZA at 0.86 (0.66-0.94). Immunohistochemical results are not correlated to hypoxia PET regardless of the staining. The two tracers show a good correlation with hypoxia, with FMISO being superior to FAZA. FMISO, therefore, remains the reference tracer for defining hypoxic volumes.

Low skeletal muscle mass is a well-known prognostic factor for patients treated for a non-small-cell lung cancer by surgery or chemotherapy. However, its impact in patients treated by exclusive radiochemotherapy has never been explored. Our study tries to evaluate the prognostic value of low skeletal muscle mass and other antropometric parameters on this population. Clinical, nutritional and anthropometric date were collected for 93 patients treated by radiochemotherapy for a NSCLC. Anthropometric parameters were measured on the PET/CT by two methods. The first method was a manual segmentation at level L3, used to define Muscle Body Area (MBA L3 ), Visceral Fat Area (VFA L3 ) and Subcutaneous Fat Area (SCFA L3 ). The second method was an software (Anthropometer3D), allowing an automatic multislice measurement of Lean Body Mass (LBM Anthro3D ), Fat Body Mass (FBM Anthro3D ), Muscle Body Mass (MBM Anthro3D ), Visceral Fat Mass (VFM Anthro3D ), and Sub-Cutaneous Fat Mass (SCFM Anthro3D ) on the PET/CT. All anthropometrics parameters were normalised by the patient's height. The primary end point was overall survival time. Univariate and then stepwise multivariate cox analysis were performed for significant parameters. Finally, Spearman's correlation between MBA L3 and MBM Anthro3D was assessed. Forty-one (44%) patients had low skeletal muscle mass. The median overall survival was 18 months for low skeletal muscle mass patients versus 36 months for non-low skeletal muscle mass patients (p = 0.019). Low skeletal muscle mass (HR = 1.806, IC95% [1.09-2.98]), serums albumin level < 35 g/l (HR = 2.203 [1.19-4.09]), Buzby Index < 97.5 (HR = 2.31 [1.23-4.33]), WHO score = 0 (HR = 0.59 [0.31-0.86] and MBM Anthro3D  < 8.56 kg/m 2 (HR = 2.36 [1.41-3.90]) were the only significant features in univariates analysis. In the stepwise multivariate Cox analysis, only MBM Anthro3D  < 8.56 kg/m 2 (HR = 2.16, p = 0.003) and WHO score = 0 (HR = 0.59, p = 0.04) were significant. Finally, muscle quantified by MBA L3 and MBM Anthro3D were found to be highly correlated (Spearman = 0.9). Low skeletal muscle mass, assessed on the pre-treatment PET/CT is a powerful prognostic factor in patient treated by radiochemotherapy for a NSCLC. The automatic software Anthropometer3D can easily identify patients a risk that could benefit an adapted therapy.

Glioblastomas (GBMs) are the most common primary brain tumors characterized by strong invasiveness and angiogenesis. GBM cells and microenvironment secrete angiogenic factors and also express chemoattractant G protein-coupled receptors (GPCRs) to their advantage. We investigated the role of the vasoactive peptide urotensin II (UII) and its receptor UT on GBM angiogenesis and tested potential ligand/therapeutic options based on this system. On glioma patient samples, the expression of UII and UT increased with the grade with marked expression in the vascular and peri-necrotic mesenchymal hypoxic areas being correlated with vascular density. In vitro human UII stimulated human endothelial HUV-EC-C and hCMEC/D3 cell motility and tubulogenesis. In mouse-transplanted Matrigel sponges, mouse (mUII) and human UII markedly stimulated invasion by macrophages, endothelial, and smooth muscle cells. In U87 GBM xenografts expressing UII and UT in the glial and vascular compartments, UII accelerated tumor development, favored hypoxia and necrosis associated with increased proliferation (Ki67), and induced metalloproteinase (MMP)-2 and -9 expression in Nude mice. UII also promoted a "tortuous" vascular collagen-IV expressing network and integrin expression mainly in the vascular compartment. GBM angiogenesis and integrin αvβ3 were confirmed by in vivo 99m Tc-RGD tracer imaging and tumoral capture in the non-necrotic area of U87 xenografts in Nude mice. Peptide analogs of UII and UT antagonist were also tested as potential tumor repressor. Urotensin II-related peptide URP inhibited angiogenesis in vitro and failed to attract vascular and inflammatory components in Matrigel in vivo . Interestingly, the UT antagonist/biased ligand urantide and the non-peptide UT antagonist palosuran prevented UII-induced tubulogenesis in vitro and significantly delayed tumor growth in vivo. Urantide drastically prevented endogenous and UII-induced GBM angiogenesis, MMP, and integrin activations, associated with GBM tumoral growth. These findings show that UII induces GBM aggressiveness with necrosis and angiogenesis through integrin activation, a mesenchymal behavior that can be targeted by UT biased ligands/antagonists., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Le Joncour, Guichet, Dembélé, Mutel, Campisi, Perzo, Desrues, Modzelewski, Couraud, Honnorat, Ferracci, Marguet, Laquerrière, Vera, Bohn, Langlois, Morin, Gandolfo and Castel.)

Introduction: Our aim was to evaluate the performance in clinical research and in clinical routine of a research prototype, called positron emission tomography (PET) Assisted Reporting System (PARS) (Siemens Healthineers) and based on a convolutional neural network (CNN), which is designed to detect suspected cancer sites in fluorine-18 fluorodeoxyglucose ( 18 F-FDG) PET/computed tomography (CT). Method: We retrospectively studied two cohorts of patients. The first cohort consisted of research-based patients who underwent PET scans as part of the initial workup for diffuse large B-cell lymphoma (DLBCL). The second cohort consisted of patients who underwent PET scans as part of the evaluation of miscellaneous cancers in clinical routine. In both cohorts, we assessed the correlation between manually and automatically segmented total metabolic tumor volumes (TMTVs), and the overlap between both segmentations (Dice score). For the research cohort, we also compared the prognostic value for progression-free survival (PFS) and overall survival (OS) of manually and automatically obtained TMTVs. Results: For the first cohort (research cohort), data from 119 patients were retrospectively analyzed. The median Dice score between automatic and manual segmentations was 0.65. The intraclass correlation coefficient between automatically and manually obtained TMTVs was 0.68. Both TMTV results were predictive of PFS (hazard ratio: 2.1 and 3.3 for automatically based and manually based TMTVs, respectively) and OS (hazard ratio: 2.4 and 3.1 for automatically based and manually based TMTVs, respectively). For the second cohort (routine cohort), data from 430 patients were retrospectively analyzed. The median Dice score between automatic and manual segmentations was 0.48. The intraclass correlation coefficient between automatically and manually obtained TMTVs was 0.61. Conclusion: The TMTVs determined for the research cohort remain predictive of total and PFS for DLBCL. However, the segmentations and TMTVs determined automatically by the algorithm need to be verified and, sometimes, corrected to be similar to the manual segmentation., Competing Interests: LS and VS are employees of the company Siemens Healthineers. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Pinochet, Eude, Becker, Shah, Sibille, Toledano, Modzelewski, Vera and Decazes.)

This paper presents an automatic classification segmentation tool for helping screening COVID-19 pneumonia using chest CT imaging. The segmented lesions can help to assess the severity of pneumonia and follow-up the patients. In this work, we propose a new multitask deep learning model to jointly identify COVID-19 patient and segment COVID-19 lesion from chest CT images. Three learning tasks: segmentation, classification and reconstruction are jointly performed with different datasets. Our motivation is on the one hand to leverage useful information contained in multiple related tasks to improve both segmentation and classification performances, and on the other hand to deal with the problems of small data because each task can have a relatively small dataset. Our architecture is composed of a common encoder for disentangled feature representation with three tasks, and two decoders and a multi-layer perceptron for reconstruction, segmentation and classification respectively. The proposed model is evaluated and compared with other image segmentation techniques using a dataset of 1369 patients including 449 patients with COVID-19, 425 normal ones, 98 with lung cancer and 397 of different kinds of pathology. The obtained results show very encouraging performance of our method with a dice coefficient higher than 0.88 for the segmentation and an area under the ROC curve higher than 97% for the classification., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Among the available imaging techniques, functional imaging provided by nuclear medicine departments represents a tool of choice for the oncoradiotherapist for targeting tumour activity, with positron emission tomography as the main modality. Before, during or after radiotherapy, functional imaging helps guide the oncoradiotherapist in making decisions and in the strategic choice of pathology management. Setting up a working group to ensure perfect coordination at all levels is the first step. Key points for a common and coordinated management between the two departments are the definition of an organizational logistic, training of personnel at every levels, standardization of nomenclatures, the choice of adapted and common equipment, implementation of regulatory controls, and research/clinical routine continuum. The availability of functional examinations dedicated to radiotherapy in clinical routine is possible and requires a convergence of teams and a pooling of tools and techniques., (Copyright © 2020 Société française de radiothérapie oncologique (SFRO). Published by Elsevier Masson SAS. All rights reserved.)

The assessment of tumour response during and after radiotherapy determines the subsequent management of patients (adaptation of treatment plan, monitoring, adjuvant treatment, rescue treatment or palliative care). In addition to its role in extension assessment and therapeutic planning, positron emission tomography combined with computed tomography provides useful functional information for the evaluation of tumour response. The objective of this article is to review published data on positron emission tomography combined with computed tomography as a tool for evaluating external radiotherapy for cancers. Data on positron emission tomography combined with computed tomography scans acquired at different times (during, after initial and after definitive [chemo-]radiotherapy, during post-treatment follow-up) in solid tumours (lung, head and neck, cervix, oesophagus, prostate and rectum) were collected and analysed. Recent recommendations of the National Comprehensive Cancer Network are also reported. Positron emission tomography combined with computed tomography with ( 18 F)-labelled fluorodeoxyglucose has a well-established role in clinical routine after chemoradiotherapy for locally advanced head and neck cancers, particularly to limit the number of neck lymph node dissection. This imaging modality also has a place for the evaluation of initial chemoradiotherapy of oesophageal cancer, including the detection of distant metastases, and for the post-therapeutic evaluation of cervical cancer. Several radiotracers for positron emission tomography combined with computed tomography, such as choline, are also recommended for patients with prostate cancer with biochemical failure. ( 18 F)-fluorodeoxyglucose positron emission tomography combined with computed tomography is optional in many other circumstances and its clinical benefits, possibly in combination with MRI, to assess response to radiotherapy remain a very active area of research., (Copyright © 2020 Société française de radiothérapie oncologique (SFRO). Published by Elsevier Masson SAS. All rights reserved.)

Purpose: 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. 2-Deoxy-2-[ 18 F]fluoro-D-glucose ([ 18 F]FDG) and [ 18 F]fluoromisonidazole ([ 18 F]FMISO) (hypoxia) uptake on pre-radiotherapy positron emission tomography (PET)/X-ray computed tomography (CT) have been independently reported to identify intratumor subvolumes at higher risk of relapse after radiotherapy. We have compared the [ 18 F]FDG and [ 18 F]FMISO volumes defined by PET/CT in NSCLC patients included in a prospective study., Procedures: Thirty-four patients with non-resectable lung cancer underwent [ 18 F]FDG and [ 18 F]FMISO PET/CT before (pre-RT) and during radiotherapy (around 42 Gy, per-RT). The criteria were to delineate 40 % and 90 % SUVmax thresholds on [ 18 F]FDG PET/CT (metabolic volumes), and SUV > 1.4 on pre-RT [ 18 F]FMISO PET/CT (hypoxic volume). The functional volumes were delineated within the tumor volume as defined on co-registered CTs., Results: The mean pre-RT and per-RT [ 18 F]FDG volumes were not statistically different (30.4 cc vs 22.2; P = 0.12). The mean pre-RT SUVmax [ 18 F]FDG was higher than per-RT SUVmax (12.7 vs 6.5; P < 0.0001). The mean [ 18 F]FMISO SUVmax and volumes were 2.7 and 1.37 cc, respectively. Volume-based analysis showed good overlap between [ 18 F]FDG and [ 18 F]FMISO for all methods of segmentation but a poor correlation for Jaccard or Dice Indices (DI). The DI maximum was 0.45 for a threshold at 40 or 50 %., Conclusion: The correlation between [ 18 F]FDG and [ 18 F]FMISO uptake is low in NSCLC, making it possible to envisage different management strategies as the studies in progress show.

Background: Sarcopenia is defined by a loss of skeletal muscle mass with or without loss of fat mass. Sarcopenia has been associated to reduced tolerance to treatment and worse prognosis in cancer patients, including patients undergoing surgery for limited oesophageal cancer. Concomitant chemo-radiotherapy is the standard treatment for locally-advanced tumour, not accessible to surgical resection. Using automated delineation of the skeletal muscle, we have investigated the prognostic value of sarcopenia in locally advanced oesophageal cancer (LAOC) patients treated by curative-intent chemo-radiotherapy., Methods: The clinical, nutritional, anthropometric, and functional-imaging ( 18 FDG-PET/CT) data were collected in 97 patients treated between 2006 and 2012 in our institution. The skeletal muscle area was automatically delineated on cross-sectional CT images acquired at the 3rd. lumbar vertebra level and divided by the patient's squared height (SML3/h 2 ) to obtain the Skeletal Muscle Index (SMI). The primary endpoint was overall survival probability., Results: Seventy-six deaths were reported. The median survival time was 27 [95% Confidence Interval 23-40] months for the whole population. Univariate analyses (Cox Proportional Hazard Model) showed decreased survival probabilities in patients with reduced SMI, WHO > 0, Body Mass Index ≤21, and Nutritional Risk Index ≤97.5. Multivariate analyses showed that sarcopenia was the only significant prognostic factor (HR 2.32 [1.24-4.34], p = 0.008). Using Receiver Operating Characteristics curves, the Area Under the Curve (AUC) was 0.73 in males (p = 0.0002], the optimal threshold being 51.5 cm 2 /m 2 . In women, the AUC was 0.65 (p = 0.19)., Conclusion: Sarcopenia is a powerful independent prognostic factor, associated with a rise of the overall mortality in patients treated exclusively by radiochemotherapy for a locally advanced oesophageal cancer. L3 CT images are easily gathered from 18 FDG-PET/CT acquisitions.

Background and Objectives: The global epidemic of diabetes, especially type 2 (DM2), is related to lifestyle changes, obesity, and the process of population aging. Diabetic retinopathy (DR) is the most serious complication of the eye caused by diabetes. The aim of this research was to assess the prevalence of diabetic retinopathy in type 1 and type 2 diabetes mellitus patients in north-east Poland. Materials and Methods : The eye fundus was assessed on the basis of two-field 50 degrees color fundus photographs that showed the optic nerve and macula in the center after the pupil was dilated with 1% tropicamide. Results : The experimental group included 315 (26%) patients with type 1 diabetes mellitus (DM1) and 894 (74%) patients with DM2. DM1 patients were diagnosed with DR in 32.58% of cases, with non-proliferative diabetic retinopathy (NPDR) in 24.44% of cases, proliferative diabetic retinopathy (PDR) in 1.59% of cases, diabetic macular edema (DME) in 5.40% of cases, and PDR with DME in 0.95% of cases. DR was found in DM2 patients in 23.04% of cases, NPDR in 17.11% of cases, PDR in 1.01% of cases, DME in 4.81% of cases, and PDR with DME in 0.11% of cases. Conclusions : The presented study is the first Polish study on the prevalence of diabetic retinopathy presenting a large group of patients, and its results could be extrapolated to the whole country. Diabetic retinopathy was found in 25.48% of patients in the whole experimental group. The above results place Poland within the European average, indicating the quality of diabetic care offered in Poland, based on the number of observed complications., Competing Interests: The authors declare no conflict of interest.

Overexpression of G protein-coupled receptors (GPCRs) in tumours is widely used to develop GPCR-targeting radioligands for solid tumour imaging in the context of diagnosis and even treatment. The human vasoactive neuropeptide urotensin II (hUII), which shares structural analogies with somatostatin, interacts with a single high affinity GPCR named UT. High expression of UT has been reported in several types of human solid tumours from lung, gut, prostate, or breast, suggesting that UT is a valuable novel target to design radiolabelled hUII analogues for cancer diagnosis. In this study, two original urotensinergic analogues were first conjugated to a DOTA chelator via an aminohexanoic acid (Ahx) hydrocarbon linker and then -hUII and DOTA-urantide, complexed to the radioactive metal indium isotope to successfully lead to radiolabelled DOTA-Ahx-hUII and DOTA-Ahx-urantide. The 111 In-DOTA-hUII in human plasma revealed that only 30% of the radioligand was degraded after a 3-h period. DOTA-hUII and DOTA-urantide exhibited similar binding affinities as native peptides and relayed calcium mobilization in HEK293 cells expressing recombinant human UT. DOTA-hUII, not DOTA-urantide, was able to promote UT internalization in UT-expressing HEK293 cells, thus indicating that radiolabelled 111 In-DOTA-hUII would allow sufficient retention of radioactivity within tumour cells or radiolabelled DOTA-urantide may lead to a persistent binding on UT at the plasma membrane. The potential of these radioligands as candidates to target UT was investigated in adenocarcinoma. We showed that hUII stimulated the migration and proliferation of both human lung A549 and colorectal DLD-1 adenocarcinoma cell lines endogenously expressing UT. In vivo intravenous injection of 111 In-DOTA-hUII in C57BL/6 mice revealed modest organ signals, with important retention in kidney. 111 In-DOTA-hUII or 111 In-DOTA-urantide were also injected in nude mice bearing heterotopic xenografts of lung A549 cells or colorectal DLD-1 cells both expressing UT. The observed significant renal uptake and low tumour/muscle ratio (around 2.5) suggest fast tracer clearance from the organism. Together, DOTA-hUII and DOTA-urantide were successfully radiolabelled with 111 Indium, the first one functioning as a UT agonist and the second one as a UT-biased ligand/antagonist. To allow tumour-specific targeting and prolong body distribution in preclinical models bearing some solid tumours, these radiolabelled urotensinergic analogues should be optimized for being used as potential molecular tools for diagnosis imaging or even treatment tools., Competing Interests: The authors declare no conflict of interest.

PET/CT has become a standard examination in oncology but is probably still underused for radiotherapy planning. However, except for the clinical research data that shows the interest of this examination in considering personalized and adaptive radiotherapy, it is also important in defining target volumes. However, before using it in clinical practice, a few prerequisites are required to know the acquisition and segmentation methods. Ideally, PET/CT should become a standard examination for radiotherapy departments in the same way as planning CT and tomorrow as MRI., (Copyright © 2019 Société française de radiothérapie oncologique (SFRO). Published by Elsevier Masson SAS. All rights reserved.)

Purpose: Chemoradiotherapy is the reference curative-intent treatment for nonresectable locally advanced non-small-cell lung carcinoma (NSCLC), with unsatisfactory survival, partially due to radiation resistance in hypoxic tissues. The objective was to update survival and toxicity at 3 years following radiotherapy boost to hypoxic tumours in NSCLC patients treated with curative-intent chemoradiotherapy., Methods: This was an open-label, nonrandomized, multicentre, phase II clinical trial. 18 F-Fluoromisonidazole ( 18 F-FMISO) PET/CT was used to determine the hypoxic profile of the patients. 18 F-FMISO-positive patients and those without organ-at-risk constraints received a radiotherapy boost (70-84 Gy); the others received standard radiotherapy (66 Gy). Overall survival (OS), progression-free survival (PFS) and safety were assessed., Results: A total of 54 patients were evaluated. OS and PFS rates at 3 years were 48.5% and 28.8%, respectively. The median OS in the 18 F-FMISO-positive patients was 25.8 months and was not reached in the 18 F-FMISO-negative patients (p = 0.01). A difference between the groups was also observed for PFS (12 months vs. 26.2 months, p = 0.048). In 18 F-FMISO-positive patients, no difference was observed in OS in relation to dose, probably because of the small sample size (p = 0.30). However, the median OS seemed to be in favour of patients who received the radiotherapy boost (26.5 vs. 15.3 months, p = 0.71). In patients who received the radiotherapy boost, no significant late toxicities were observed., Conclusion: 18 F-FMISO uptake in NSCLC patients is strongly associated with features indicating a poor prognosis. In 18 F-FMISO-positive patients, the radiotherapy boost seemed to improve the OS by 11.2 months. A further clinical trial is needed to investigate the efficacy of a radiotherapy boost in patients with hypoxic tumours.

Background and Aims: Changes in body composition have been described in patients with Crohn's disease, but their predictive performances on disease evolution remain undefined. The aims of our study were to assess, in patients with Crohn's disease requiring abdominal computed tomography, body composition by computed tomography, and to study the outcome according to various body composition parameters at the time of the computed tomography., Methods: Patients with Crohn's disease who underwent abdominal computed tomography for suspected complications were retrospectively included. The definition of adverse outcome included death or need for surgery within 6 months of the computed tomography. Skeletal muscle index and visceral and subcutaneous adiposity indexes were calculated from tissue surface areas measured at the third lumbar vertebra, divided by the height squared., Results: The prevalence of underweight was 26.8% and the prevalence of sarcopenia was 33.6%. After gender adjustment, skeletal muscle index tended to be reduced in patients with adverse outcome, compared with patients without surgery or death [p = 0.07]. Moreover, subcutaneous adiposity index and visceral adiposity index were significantly lower in patients with surgery or death [p = 0.009 and p < 0.001, respectively]. These differences were almost equivalent in both genders for the subcutaneous adiposity index but were clearly stronger in men for the visceral adiposity index., Conclusions: Subcutaneous and visceral adiposity indexes correlate inversely with adverse outcome in patients with Crohn's disease. Alteration of body composition assessed by computed tomography in these patients appears to be a marker of disease severity.

Objectives: To propose an easily applicable segmentation method (perPET-RT) for delineation of tumour volume during radiotherapy on interim fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) in patients with non-small cell lung cancer (NSCLC)., Material and Methods: Sixty-seven patients (51 primary tumours, 60 lymph nodes), from 4 prospective studies, underwent an FDG PET/CT scan during the fifth week of radiation therapy, using different generations of PET/CT. Per-therapeutic PET/CT scans were delineated in consensus by two experienced physicians leading to the gold standard threshold to be applied. The mathematical expression of Th opt , the optimal threshold to be applied as a function of the maximum standard uptake value (SUV max ), was determined. The performance of this method (perPET-RT) was assessed by computing the DICE similarity coefficient (DSC) and was compared with 8 fixed threshold values and 3 adaptive thresholding methods., Results: Th opt verified the following expression: Th opt  = A.ln(1/SUV max ) + B where A and B were 2 constants. A and B were independent from the generation of PET/CT, but depended on the type of lesions (primary lung tumours vs. lymph nodes). PerPET-RT showed good to very good agreement in comparison to the gold standard. The mean and standard deviation of DSC value was 0.81 ± 0.13 for lung lesions and 0.78 ± 0.15 for lymph nodes. PerPET-RT showed a significant better agreement than the other segmentation methods (p < 0.001), except for one of the adaptive thresholding method ADT (p = 0.11)., Conclusion: On the database used, perPET-RT has proven its reliability and accuracy for tumour delineation on per-therapeutic FDG PET/CT using only SUV max measurement. This method may be used to delineate tumour volume for dose-escalation planning., Trial Registration: NCT01261598 , NCT01261585 , NCT01576796 .

Background: Concomitant chemo-radiotherapy is the reference treatment for non-resectable locally-advanced Non-Small Cell Lung Cancer (NSCLC). Increasing radiotherapy total dose in the whole tumour volume has been shown to be deleterious. Functional imaging with positron emission tomography (PET/CT) offers the potential to identify smaller and biologically meaningful target volumes that could be irradiated with larger doses without compromising Organs At Risk (OAR) tolerance. This study investigated four scenarios, based on 18 FDG and 18 F-miso PET/CT, to delineate the target volumes and derive radiotherapy plans delivering up to 74Gy., Method: Twenty-one NSCLC patients, selected from a prospective phase II trial, had 18 FDG- and 18 F-miso PET/CT before the start of radiotherapy and 18 FDG PET/CT during the radiotherapy (42Gy). The plans were based planned on a standard plan delivering 66 Gy (plan 1) and on three different boost strategies to deliver 74Gy total dose in pre-treatment 18 FDG hotspot (70% of SUV max ) (plan 2), pre-treatment 18 F-miso target (SUV max  > 1.4) (plan 3) and per-treatment 18 FDG residual (40% of SUV max ). (plan 4)., Results: The mean target volumes were 4.8 cc (± 1.1) for 18 FDG hotspot, 38.9 cc (± 14.5) for 18 F-miso and 36.0 cc (± 10.1) for per-treatment 18 FDG. In standard plan (66 Gy), the mean dose covering 95% of the PTV (D95%) were 66.5 (± 0.33), 66.1 (± 0.32) and 66.1 (± 0.32) Gy for 18 FDG hotspot, 18 F-miso and per-treatment 18 FDG. In scenario 2, the mean D95% was 72.5 (± 0.25) Gy in 18 FDG hotspot versus 67.9 (± 0.49) and 67.9 Gy (± 0.52) in 18 F-miso and per-treatment 18 FDG, respectively. In scenario 3, the mean D95% was 72.2 (± 0.27) Gy to 18 F-miso versus 70.4 (± 0.74) and 69.5Gy (± 0.74) for 18 FDG hotspot and per-treatment 18 FDG, respectively. In scenario 4, the mean D95% was 73.1 (± 0.3) Gy to 18 FDG per-treatment versus 71.9 (± 0.61) and 69.8 (± 0.61) Gy for 18 FDG hotspot and 18 F-miso, respectively. The dose/volume constraints to OARs were matched in all scenarios., Conclusion: Escalated doses can be selectively planned in NSCLC target volumes delineated on 18 FDG and 18 F-miso PET/CT functional images. The most relevant strategy should be investigated in clinical trials., Trial Registration: (RTEP5, NCT01576796 , registered 15 june 2012).

In this article, we present a complete automated system for spotting a particular slice in a complete 3D Computed Tomography exam (CT scan). Our approach does not require any assumptions on which part of the patient's body is covered by the scan. It relies on an original machine learning regression approach. Our models are learned using the transfer learning trick by exploiting deep architectures that have been pre-trained on imageNet database, and therefore it requires very little annotation for its training. The whole pipeline consists of three steps: i) conversion of the CT scans into Maximum Intensity Projection (MIP) images, ii) prediction from a Convolutional Neural Network (CNN) applied in a sliding window fashion over the MIP image, and iii) robust analysis of the prediction sequence to predict the height of the desired slice within the whole CT scan. Our approach is applied to the detection of the third lumbar vertebra (L3) slice that has been found to be representative to the whole body composition. Our system is evaluated on a database collected in our clinical center, containing 642 CT scans from different patients. We obtained an average localization error of 1.91±2.69 slices (less than 5 mm) in an average time of less than 2.5 s/CT scan, allowing integration of the proposed system into daily clinical routines., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

See an invited perspective on this article on page 1043.This multicenter phase II study investigated a selective radiotherapy dose increase to tumor areas with significant 18 F-misonidazole ( 18 F-FMISO) uptake in patients with non-small cell lung carcinoma (NSCLC). Methods: Eligible patients had locally advanced NSCLC and no contraindication to concomitant chemoradiotherapy. The 18 F-FMISO uptake on PET/CT was assessed by trained experts. If there was no uptake, 66 Gy were delivered. In 18 F-FMISO-positive patients, the contours of the hypoxic area were transferred to the radiation oncologist. It was necessary for the radiotherapy dose to be as high as possible while fulfilling dose-limiting constraints for the spinal cord and lungs. The primary endpoint was tumor response (complete response plus partial response) at 3 mo. The secondary endpoints were toxicity, disease-free survival (DFS), and overall survival at 1 y. The target sample size was set to demonstrate a response rate of 40% or more (bilateral α = 0.05, power 1-β = 0.95). Results: Seventy-nine patients were preincluded, 54 were included, and 34 were 18 F-FMISO-positive, 24 of whom received escalated doses of up to 86 Gy. The response rate at 3 mo was 31 of 54 (57%; 95% confidence interval [CI], 43%-71%) using RECIST 1.1 (17/34 responders in the 18 F-FMISO-positive group). DFS and overall survival at 1 y were 0.86 (95% CI, 0.77-0.96) and 0.63 (95% CI, 0.49-0.74), respectively. DFS was longer in the 18 F-FMISO-negative patients ( P = 0.004). The radiotherapy dose was not associated with DFS when adjusting for the 18 F-FMISO status. One toxic death (66 Gy) and 1 case of grade 4 pneumonitis (>66 Gy) were reported. Conclusion: Our approach results in a response rate of 40% or more, with acceptable toxicity. 18 F-FMISO uptake in NSCLC patients is strongly associated with poor prognosis features that could not be reversed by radiotherapy doses up to 86 Gy., (© 2017 by the Society of Nuclear Medicine and Molecular Imaging.)

Background: The potential benefits of 18 F-fluoro-2-deoxy-D-glucose-positron emission tomography/CT (FDG-PET/CT) imaging for radiotherapy (RT) treatment planning of head and neck squamous cell carcinoma (HNSCC) are increasingly being recognized. It has been suggested that intratumoral subvolumes with high FDG avidity ("hotspots") are potential targets for selected dose escalation. The purposes of this study were to demonstrate that pre-RT FDG-PET/CT can identify intratumoral sites at increased risk of local relapse after RT and to determine an optimal threshold to delineate smaller RT target volumes that would facilitate RT dose escalation without impaired tolerance., Methods: Seventy-two consecutive patients with locally advanced HNSCC treated by RT ± chemotherapy were included in this study. All patients underwent FDG-PET/CT at initial staging (PET A ) and during systematic follow-up (PET R ). FDG-PET/CT was coregistered on the initial CT scan with a rigid method. Various subvolumes (A X ; × = 30%, 40%, 50%, 60%, 70%, 80%, and 90% standardized uptake value maximum [SUVmax] thresholds) within the primary tumor and in the subsequent local relapse (R X ; × = 40% and 70% SUVmax thresholds) were compared together (Dice, Jaccard, overlap fraction, common volume/baseline volume, and common volume/recurrent volume)., Results: Nineteen patients (26%) had local relapses. Using a 40% SUVmax threshold, the initial metabolic tumor volume was significantly higher in patients with local relapses than in controlled patients (10.4 ± 8.6 vs 5.1 ± 4.9 cc; p = .002) as well as total lesion glycolysis (117.9 ± 88.6 vs 60.6 ± 80.4; p = .013). For both methods, the overlap index among A 30 , A 40 , and A 50 subvolumes on PET A and the whole metabolic volume of recurrence R 40 and R 70 on PET R showed a moderate agreement (0.52 to 0.43)., Conclusion: Our study does not find high overlap index values between the initial tumor and recurrence subvolumes, probably because of a suboptimal coregistration. Our results also confirm that metabolic tumor volume and total lesion glycolysis are independently correlated with recurrence-free survival in patients with HNSCC. Further larger prospective studies with FDG-PET/CT performed in the same RT position and with a validated elastic registration method are needed. © 2017 Wiley Periodicals, Inc. Head Neck 39: 1155-1165, 2017., (© 2017 Wiley Periodicals, Inc.)

Purpose: In oncology, texture features extracted from positron emission tomography with 18-fluorodeoxyglucose images (FDG-PET) are of increasing interest for predictive and prognostic studies, leading to several tens of features per tumor. To select the best features, the use of a random forest (RF) classifier was investigated., Methods: Sixty-five patients with an esophageal cancer treated with a combined chemo-radiation therapy were retrospectively included. All patients underwent a pretreatment whole-body FDG-PET. The patients were followed for 3 years after the end of the treatment. The response assessment was performed 1 month after the end of the therapy. Patients were classified as complete responders and non-complete responders. Sixty-one features were extracted from medical records and PET images. First, Spearman's analysis was performed to eliminate correlated features. Then, the best predictive and prognostic subsets of features were selected using a RF algorithm. These results were compared to those obtained by a Mann-Whitney U test (predictive study) and a univariate Kaplan-Meier analysis (prognostic study)., Results: Among the 61 initial features, 28 were not correlated. From these 28 features, the best subset of complementary features found using the RF classifier to predict response was composed of 2 features: metabolic tumor volume (MTV) and homogeneity from the co-occurrence matrix. The corresponding predictive value (AUC = 0.836 ± 0.105, Se = 82 ± 9%, Sp = 91 ± 12%) was higher than the best predictive results found using the Mann-Whitney test: busyness from the gray level difference matrix (P < 0.0001, AUC = 0.810, Se = 66%, Sp = 88%). The best prognostic subset found using RF was composed of 3 features: MTV and 2 clinical features (WHO status and nutritional risk index) (AUC = 0.822 ± 0.059, Se = 79 ± 9%, Sp = 95 ± 6%), while no feature was significantly prognostic according to the Kaplan-Meier analysis., Conclusions: The RF classifier can improve predictive and prognostic values compared to the Mann-Whitney U test and the univariate Kaplan-Meier survival analysis when applied to several tens of features in a limited patient database.

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 18 F-FDG PET/CT with adaptive thresholding methods with TMTV measured with a fixed 41% SUV max 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% SUV max 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 SUV max The TMTV values obtained with each adaptive method were compared with those obtained with the 41% SUV max 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 TMTV 41% , TMTV Da , TMTV Ns , TMTV Fit , and TMTV Bl were, respectively, 231 cm 3 (range, 5-3,824), 175 cm 3 (range, 8-3,510), 198 cm 3 (range, 3-3,934), 175 cm 3 (range, 8-3,512), and 333 cm 3 (range, 3-5,113). The intraclass correlation coefficients were excellent, from 0.972 to 0.988, for TMTV Da , TMTV Fit , and TMTV Ns , and less good for TMTV Bl (0.856). The mean differences obtained from the Bland-Altman plots were 48.5, 47.2, 19.5, and -253.3 cm 3 , 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% SUV max , 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., (© 2017 by the Society of Nuclear Medicine and Molecular Imaging.)

Aim: To assess the feasibility of SPECT-computed tomography (CT) in rats with trinitrobenzene sulfonic acid (TNBS)-induced acute colitis and confront it with model inflammatory characteristics., Methods: Colitis was induced in Sprague-Dawley rats by intrarectal injection of TNBS ( n = 10) while controls received vehicle ( n = 10). SPECT-CT with intravenous injection of 10 MBq of 67Ga-Citrate was performed at day 2. SPECT-CT criteria were colon wall thickness and maximal wall signal intensity. Laboratory parameters were assessed: colon weight:length ratio, colon cyclooxygenase-2 expression by western blot and histological inflammatory score., Results: Colon weight/length ratio, colon COX-2 expression and histological inflammatory score were significantly higher in the TNBS group than in the control group ( P = 0.0296, P < 0.0001, P = 0.0007 respectively). Pixel max tend to be higher in the TNBS group than in the control group but did not reach statistical significance ( P = 0.0662). Maximal thickness is significantly increased in the TNBS group compared to the control group ( P = 0.0016) while colon diameter is not ( P = 0.1904). Maximal thickness and colon diameter were correlated to colon COX-2 expression ( P = 0.0093, P = 0.009 respectively) while pixel max was not ( P = 0.22). Maximal thickness was significantly increased when inflammation was histologically observed ( P = 0.0043) while pixel max and colon diameter did not ( P = 0.2452, P = 0.3541, respectively)., Conclusion: SPECT-CT is feasible and easily distinguished control from colitic rats., Competing Interests: Conflict-of-interest statement: We declare that we have no financial and personal relationships with other people or organizations that could inappropriately influence our work.

Purpose: The aim of this study was to evaluate the impact of consensus algorithms on segmentation results when applied to clinical PET images. In particular, whether the use of the majority vote or STAPLE algorithm could improve the accuracy and reproducibility of the segmentation provided by the combination of three semiautomatic segmentation algorithms was investigated., Methods: Three published segmentation methods (contrast-oriented, possibility theory and adaptive thresholding) and two consensus algorithms (majority vote and STAPLE) were implemented in a single software platform (Artiview®). Four clinical datasets including different locations (thorax, breast, abdomen) or pathologies (primary NSCLC tumours, metastasis, lymphoma) were used to evaluate accuracy and reproducibility of the consensus approach in comparison with pathology as the ground truth or CT as a ground truth surrogate., Results: Variability in the performance of the individual segmentation algorithms for lesions of different tumour entities reflected the variability in PET images in terms of resolution, contrast and noise. Independent of location and pathology of the lesion, however, the consensus method resulted in improved accuracy in volume segmentation compared with the worst-performing individual method in the majority of cases and was close to the best-performing method in many cases. In addition, the implementation revealed high reproducibility in the segmentation results with small changes in the respective starting conditions. There were no significant differences in the results with the STAPLE algorithm and the majority vote algorithm., Conclusion: This study showed that combining different PET segmentation methods by the use of a consensus algorithm offers robustness against the variable performance of individual segmentation methods and this approach would therefore be useful in radiation oncology. It might also be relevant for other scenarios such as the merging of expert recommendations in clinical routine and trials or the multiobserver generation of contours for standardization of automatic contouring.

Introduction: Earlier studies indicated that bevacizumab could favorably be combined with radiation. However excessive damage to tumor vasculature can result in radioresistance and clinical data suggest that treatment sequencing may be important when combining bevacizumab with radiation. The aim of this study was to evaluate whether αvβ3 scintigraphic imaging could provide information to determine the optimal combination schedule of bevacizumab and radiotherapy on a lung adenocarcinoma model in mice., Methods: The tumor volume and angiogenesis changes induced after bevacizumab and radiation treatment were evaluated using (99m)Tc-RGD on a microSPECT/CT. First, we determined the optimal dose regimen for bevacizumab and radiotherapy alone. Second, the combined effects of bevacizumab and radiation were evaluated according to the combination timing (radiation 2, 24, 48 hours after bevacizumab and 48 hours before bevacizumab)., Results: The optimal dose regimen is 20mg/kg for bevacizumab and 12.5 Gy for radiotherapy with a significant decrease of tumoral uptake and volume at day 9 compared to the controls (+8.8%, +7.7%, and +44% volume, respectively, and +9.8%, +3.8%, and +207% uptake, respectively). Scintigraphic imaging showed a significant increased RGD tumor uptake two hours after bevacizumab treatment compared to 24 hours and controls (p=0.02). When bevacizumab treatment was combined with radiation, the best combination appears to be the administration of bevacizumab two hours prior to radiation with better results than single treatments (p < 0.05). On the contrary, bevacizumab given 24 hours prior to radiation led to less tumor growth delay compared to a single agent, without significant difference compared to the controls. Histological results confirmed these data with an increased percentage of necrosis (p=0.04) and a decrease of angiogenesis (p=0.04) in the optimal combination group., Conclusions: The RGD tracer helps us identify the vascular normalization window and it shows a supra-additive effect of bevacizumab when administered two hours before radiotherapy., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Purpose: The high failure rates in the radiotherapy (RT) target volume suggest that patients with locally advanced oesophageal cancer (LAOC) would benefit from increased total RT doses. High 2-deoxy-2-[(18)F]fluoro-D-glucose (FDG) uptake (hotspot) on pre-RT FDG positron emission tomography (PET)/CT has been reported to identify intra-tumour sites at increased risk of relapse after RT in non-small cell lung cancer and in rectal cancer. Our aim was to confirm these observations in patients with LAOC and to determine the optimal maximum standardized uptake value (SUVmax) threshold to delineate smaller RT target volumes that would facilitate RT dose escalation without impaired tolerance., Methods: The study included 98 consecutive patients with LAOC treated by chemoradiotherapy (CRT). All patients underwent FDG PET/CT at initial staging and during systematic follow-up in a single institution. FDG PET/CT acquisitions were coregistered on the initial CT scan. Various subvolumes within the initial tumour (30, 40, 50, 60, 70, 80 and 90% SUVmax thresholds) and in the subsequent local recurrence (LR, 40 and 90% SUVmax thresholds) were pasted on the initial CT scan and compared[Dice, Jaccard, overlap fraction (OF), common volume/baseline volume, common volume/recurrent volume]., Results: Thirty-five patients had LR. The initial metabolic tumour volume was significantly higher in LR tumours than in the locally controlled tumours (mean 25.4 vs 14.2 cc; p = 0.002). The subvolumes delineated on initial PET/CT with a 30-60% SUVmax threshold were in good agreement with the recurrent volume at 40% SUVmax (OF = 0.60-0.80). The subvolumes delineated on initial PET/CT with a 30-60% SUVmax threshold were in good to excellent agreement with the core volume (90% SUVmax) of the relapse (common volume/recurrent volume and OF indices 0.61-0.89)., Conclusion: High FDG uptake on pretreatment PET/CT identifies tumour subvolumes that are at greater risk of recurrence after CRT in patients with LAOC. We propose a 60% SUVmax threshold to delineate high FDG uptake areas on initial PET/CT as reduced target volumes for RT dose escalation.

Unlabelled: 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 (18)F-FDG uptake on preradiotherapy (18)F-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 (18)F-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 (18)F-FDG PET/CT at initial staging, before radiotherapy, during radiotherapy, and during systematic follow-up in a single institution. All (18)F-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 (18)F-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 (18)F-FDG uptake on initial PET/CT scans as the target volumes for potential radiotherapy dose escalation., (© 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.)

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., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Purpose: It has been suggested that FDG PET has predictive value for the prognosis of treated oesophageal carcinoma. However, the studies reported in the literature have shown discordant results. The aim of this study was to determine whether pretherapy quantitative metabolic parameters correlate with patient outcomes., Methods: Included in the study were 67 patients with a histological diagnosis of oesophageal squamous cell carcinoma. Each patient underwent (18)F-FDG PET (4.5 MBq/kg) before chemoradiotherapy. Quantitative analysis was performed using the following parameters: age, weight loss, location, N stage, OMS performance status, MTVp and MTVp' (metabolic tumour volume determined by two different physicians), MTV40% (volume for a threshold of 40 % of SUVmax), MTVa (volume automatically determined with a contrast-based adaptive threshold method), SUVmax, SUVmean and TLG (total lesion glycolysis)., Results: MTVp and MTV40% were highly correlated (Pearson's index 0.92). SUVmeanp and SUVmean40% were also correlated (Pearson's index 0.86), as were TLGp and TLG40% (Pearson's index 0.98). Similarly, the parameters obtained with the adaptive threshold method (MTVa, SUVmeana and TLGa) were correlated with those obtained manually (MTVp, SUVmeanp and TLGp). The manual metabolic tumour volume determination (MTVp and MTVp') was reproducible. Multivariate analysis for disease-free survival (DFS) showed that a larger MTVp was associated with a shorter DFS (p = 0.004) and that a higher SUVmax was associated with a longer DFS (p = 0.02). Multivariate analysis for overall survival (OS) showed that a larger MTVp was associated with a shorter OS (p = 0.01) and that a tumour in the distal oesophagus was associated with a longer OS (p = 0.005). The associations among the other parameters were not statistically significant., Conclusion: Metabolic tumour volume is a major prognostic factor for DFS and OS in patients with oesophageal squamous cell carcinoma. Higher SUVmax values were paradoxically associated with longer survival. The location of the tumour also appeared to affect prognosis.

Purpose: Various segmentation methods for 18F-fluoro-2-deoxy-d-glucose (FDG) positron emission tomography/computed tomography (PET/CT) images were correlated with pathological volume in breast cancer patients as a model of small mobile tumours., Methods: Thirty women with T2-T3/M0 breast invasive ductal carcinoma (IDC) were included prospectively. A FDG-PET/CT was acquired 4 ± 3d before surgery in prone and supine positions, with/without respiratory gating. The segmentation methods were as follows: manual (Vm), relative (Vt%) and adaptive (Va) standard uptake value (SUV) threshold and semi-automatic on CT (Vct). Pathological volumes (Vpath) were measured for 26 lesions., Results: The mean (±SD) Vpath was 4.1 ± 2.9 mL, and the lesion displacements were 3.9 ± 2.8 mm (median value: 3 mm). The delineated VOIs did not vary with the acquisition position nor with respiration, regardless of the segmentation method. The Vm, Va, Vct and Vt% methods, except Vt30%, were correlated with Vpath (0.5

Objectives: 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)., Methods: This retrospective analysis included 80 DLBCL patients older than 70 yr treated with R-CHOP or R-miniCHOP. Skeletal muscle (SM) and visceral (V) and subcutaneous (S) adipose (A) tissues were measured by analysing CT images at the third lumbar (L3) level., Results: The median age of the patients was 78 yr. Forty-four and 46 patients were considered sarcopenic and adipopenic, respectively. The median progression-free survival (PFS) was 13.6 months in the adipopenic group and 49.4 months in the non-adipopenic group [hazard ratio (HR) = 2.27; 95% confidence interval (CI): 1.3-4; P = 0.0042]. The median overall survival (OS) was 25.7 months in the adipopenic group and 57.1 months in the non-adipopenic group (HR = 1.93; 95% CI: 1.05-3.55; P = 0.0342). A two-point CS including adipopenia and sarcopenia was created and defined two distinct risk groups with differences in outcomes that were highly significant. The CS was predictive of the prognosis in a multivariate analysis including body mass index (BMI) (< or ≥ 25 kg/m(2) ), age (< or ≥ 80 yr), international prognostic index (IPI) and albuminaemia (HR = 3.67; 95% CI = 1.93-6.97; P < 0.0001)., Conclusion: A CS including sarcopenia and adipopenia, assessed by a single CT scan slice, predicts outcome independent of BMI and the IPI., (© 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)