Trifluridine/tipiracil + oxaliplatin ± nivolumab vs FOLFOX ± nivolumab in HER2 negative advanced oesogastric adenocarcinoma: The PRODIGE73-UCGI40-LOGICAN trial.

BACKGROUND: Trifluridine/tipiracil (FTD/TPI) is approved in third-line treatment of patients with advanced/metastatic gastric and gastroesophageal junction adenocarcinomas (aGA/GEJA). The association of oxaliplatin with FTD/TPI is promising and the combination of FTD/TPI + oxaliplatin + nivolumab has shown a predictable and manageable safety profile. AIMS: The aim is to evaluate the efficacy and safety of FTD/TPI plus oxaliplatin with or without nivolumab in patients, with HER2 negative aGA/GEJA, unfit for triplet chemotherapy (TFOX/mFLOT regimen), in the first-line metastatic setting in comparison with the standard of care FOLFOX with or without nivolumab. METHODS: This study is a prospective randomised, open label, comparative, multicentre, phase II trial designed to include 118 patients. The primary objective is to evaluate the superiority of FTD/TPI plus oxaliplatin with or without nivolumab over FOLFOX regimen with or without nivolumab in terms of PFS in a population of patients non candidate for triplet chemotherapy. Nivolumab will be used for patients whose tumour express PD-L1 with a CPS score ≥5. DISCUSSION: PRODIGE73-UCGI40-LOGICAN study will provide efficacy and safety data on the association of FTD/TPI plus oxaliplatin with or without nivolumab versus FOLFOX regimen with or without nivolumab in first-line palliative setting, in patients with aGA/GEJA (NCT05476796).

Cerebellum/liver index on baseline 18F-FDG PET/CT to improve prognostication in post-transplant lymphoproliferative disorders: a multicenter retrospective study.

BACKGROUND: Besides International Prognostic Index (IPI) score, baseline prognostic factors of post-transplant lymphoproliferative disorders (PTLD) are poorly identified due to the rarity of the disease. New indexes derived from healthy organ uptake in baseline 18F-FDG PET/CT have been studied in immunocompetent lymphoma patients. The aim of this study is to evaluate the performances of the cerebellum-to-liver uptake ratio (denoted as CLIP) as a prognostic factor for PFS and OS. This retrospective multicenter study is based on patients with PTLD included in the K-VIROGREF cohort. The previously published threshold of 3.24 was used for CLIP in these analyses. RESULTS: A total of 97 patients was included with a majority of monomorphic diffuse large B-cell lymphoma subtype (78.3%). Both IPI score (≥ 3) and CLIP (< 3.24) were significant risk factors of PFS with corresponding hazard ratios of 2.0 (1.0-4.0) and 2.4 (1.3-4.5) respectively. For OS, CLIP was not significant and resulted in a hazard ratio of 2.6 (p = 0.059). Neither IPI score or Total Metabolic Tumor Volume reached significance for OS. CONCLUSION: CLIP is a promising predictor of PFS and perhaps OS in PTLD. Further prospective studies are needed to confirm these results.

High PDL1/PDL2 gene expression correlates with worse outcome in primary mediastinal large B-cell lymphoma.

Primary mediastinal B-cell lymphoma (PMBL) is an uncommon entity of aggressive B-cell lymphoma with an unusually good prognosis, except for 10-15% of chemotherapy-refractory cases. To identify earlier these higher risk patients, we performed molecular characterization of a retrospective multicenter cohort of patients treated with firstline immunochemotherapy. The traits of the patients with gene-expression profiling data (n = 120) were as follows: median age of 34 years (range, 18-67 years); female sex, 58.3%; elevated lactate dehydrogenase, 82.5%; Eastern Cooperative Oncology Group performance status score of 0 to 1, 85.7%; Ann Arbor stage I/II, 55%; International Prognostic Index score of 1 to 2, 64.4%; and median metabolic tumor volume, 290.4 cm3 (range, 15.7-1147.5 cm3). Among all 137 markers tested for correlation with survival data, only programmed death-ligand (PDL) 1 and PDL2 expression showed a prognostic impact. Overall, both PDL1 and PDL2 genes were highly expressed in 37 patients (30.8%; PDL1high/PDL2high). The baseline clinical characteristics of patients with PDL1high/PDL2high were similar to those of other patients. In univariate analysis, PDL1high/PDL2high status was associated with poor progression-free survival (PFS) (hazard ratio [HR], 4.292) and overall survival (OS; HR, 8.24). In multivariate analysis, PDL1high/PDL2high status was an independent prognostic factor of adverse outcomes (PFS: HR, 5.22; OS: HR, 10.368). We validated these results in an independent cohort of 40 patients and confirmed the significant association between PDL1high/PDL2high status and inferior PFS (HR, 6.11). High PDL1/PDL2 gene expression defines a population with strong immune privilege and poorer outcomes from standard chemotherapy who might benefit from firstline checkpoint inhibitor therapy.

Synergic prognostic value of 3D CT scan subcutaneous fat and muscle masses for immunotherapy-treated cancer.

BACKGROUND: Our aim was to explore the prognostic value of anthropometric parameters in a large population of patients treated with immunotherapy. METHODS: We retrospectively included 623 patients with advanced non-small cell lung cancer (NSCLC) (n=318) or melanoma (n=305) treated by an immune-checkpoint-inhibitor having a pretreatment (thorax-)abdomen-pelvis CT scan. An external validation cohort of 55 patients with NSCLC was used. Anthropometric parameters were measured three-dimensionally (3D) by a deep learning software (Anthropometer3DNet) allowing an automatic multislice measurement of lean body mass, fat body mass (FBM), muscle body mass (MBM), visceral fat mass (VFM) and sub-cutaneous fat mass (SFM). Body mass index (BMI) and weight loss (WL) were also retrieved. Receiver operator characteristic (ROC) curve analysis was performed and overall survival was calculated using Kaplan-Meier (KM) curve and Cox regression analysis. RESULTS: In the overall cohort, 1-year mortality rate was 0.496 (95% CI: 0.457 to 0.537) for 309 events and 5-year mortality rate was 0.196 (95% CI: 0.165 to 0.233) for 477 events. In the univariate Kaplan-Meier analysis, prognosis was worse (p<0.001) for patients with low SFM (<3.95 kg/m2), low FBM (<3.26 kg/m2), low VFM (<0.91 kg/m2), low MBM (<5.85 kg/m2) and low BMI (<24.97 kg/m2). The same parameters were significant in the Cox univariate analysis (p<0.001) and, in the multivariate stepwise Cox analysis, the significant parameters were MBM (p<0.0001), SFM (0.013) and WL (0.0003). In subanalyses according to the type of cancer, all body composition parameters were statistically significant for NSCLC in ROC, KM and Cox univariate analysis while, for melanoma, none of them, except MBM, was statistically significant. In multivariate Cox analysis, the significant parameters for NSCLC were MBM (HR=0.81, p=0.0002), SFM (HR=0.94, p=0.02) and WL (HR=1.06, p=0.004). For NSCLC, a KM analysis combining SFM and MBM was able to separate the population in three categories with the worse prognostic for the patients with both low SFM (<5.22 kg/m2) and MBM (<6.86 kg/m2) (p<0001). On the external validation cohort, combination of low SFM and low MBM was pejorative with 63% of mortality at 1 year versus 25% (p=0.0029). CONCLUSIONS: 3D measured low SFM and MBM are significant prognosis factors of NSCLC treated by immune checkpoint inhibitors and can be combined to improve the prognostic value.

Anti-leucine-rich glioma-inactivated 1 encephalitis revealed by a manic episode: insights from frontal lobe dysfunction in neuropsychiatry through neuropsychology and metabolic imaging. A case report.

Background: Anti-leucine-rich glioma-inactivated 1 (LGI1) encephalitis is a limbic encephalitis that rarely presents as an isolated psychiatric syndrome. Case presentation: A 70-year-old patient first presented with behavioral disorder including hyperactivity, euphoria, with disinhibition and accelerated speech associated with severe insomnia and cognitive disorder. A manic episode was diagnosed and he received various psychotropic medications with no improvement. Invesitgations were negative (MRI showed T2 aspecific hyperintensities with no hyperintensities in limbic regions and EEG was normal). He was transferred to a nursing home, with a diagnosis of neurodegenerative condition. Later, he was referred to our unit for further investigations. A cerebral 18F-FDG-PET revealed an association of frontal hypometabolism and temporal and striatum hypermetabolism and CSF analysis revealed slightly increased white blood cell counts. Plasmatic anti-LGI1 antibodies were detected. The patient was treated with intra-venous immunoglobulin (IvIg) but showed no improvement. Second-line treatment (a combination of rituximab and cyclophosmphamide) was then administered for a year, leading to an improvement of neuropsychiatric symptoms and normalization of metabolic impairment on 18F-FDG-PET. Conclusion: In this report, we describe a novel case of a patient withanti-LGI1 encephalitis with a predominant long-term psychiatric presentation. An atypical presentation (such as atypical psychiatric symptoms, neurocognitive disorder, and hyponatremia) should prompt further investigations such as CSF analysis, considering that MRI and EEG may be normal. FDG-PET might be of interest but few data are available in the literature. Early treatment of anti-LGI1 encephalitis is crucial for overall prognosis and may delay the development of dementia in some cases.

High prevalence of pre-existing sarcopenia in critically ill patients with hematologic malignancies admitted to the intensive care unit for sepsis or septic shock.

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.

Overview of the HECKTOR Challenge at MICCAI 2022: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT.

This paper presents an overview of the third edition of the HEad and neCK TumOR segmentation and outcome prediction (HECKTOR) challenge, organized as a satellite event of the 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2022. The challenge comprises two tasks related to the automatic analysis of FDG-PET/CT images for patients with Head and Neck cancer (H&N), focusing on the oropharynx region. Task 1 is the fully automatic segmentation of H&N primary Gross Tumor Volume (GTVp) and metastatic lymph nodes (GTVn) from FDG-PET/CT images. Task 2 is the fully automatic prediction of Recurrence-Free Survival (RFS) from the same FDG-PET/CT and clinical data. The data were collected from nine centers for a total of 883 cases consisting of FDG-PET/CT images and clinical information, split into 524 training and 359 test cases. The best methods obtained an aggregated Dice Similarity Coefficient (DSCagg) of 0.788 in Task 1, and a Concordance index (C-index) of 0.682 in Task 2.

Respiratory muscle metabolic activity on PET/CT correlates with obstructive ventilatory defect severity and prognosis in patients undergoing lung cancer surgery.

BACKGROUND AND OBJECTIVE: Respiratory muscle activity is increased in patients with chronic respiratory disease. 18 F-FDG-PET/CT can assess respiratory muscle activity. We hypothesized that respiratory muscles metabolism was correlated to lung function impairment and was associated to prognosis in patients undergoing lung cancer surgery based on the research question whether respiratory muscle metabolism quantitatively correlates with the severity of lung function impairment in patients? Does respiratory muscle hypermetabolism have prognostic value? METHODS: Patients undergoing 18 F-FDG-PET/CT and pulmonary function tests prior to lung cancer surgery were identified. Maximum Standardized Uptake Value (SUVm) were measured in each respiratory muscle group (sternocleidomastoid, scalene, intercostal, diaphragm), normalized against deltoid SUVm. Respiratory muscle hypermetabolism was defined as SUVm >90th centile in any respiratory muscle group. Clinical outcomes were collected from a prospective cohort. RESULTS: One hundred fifty-six patients were included, mostly male [110 (71%)], 53 (34%) with previous diagnosis of COPD. Respiratory muscle SUVm were: scalene: 1.84 [1.51-2.25], sternocleidomastoid 1.64 [1.34-1.95], intercostal 1.01 [0.84-1.16], diaphragm 1.79 [1.41-2.27]. Tracer uptake was inversely correlated to FEV1 for the scalene (r = -0.29, p < 0.001) and SCM (r = -0.17, p = 0.03) respiratory muscle groups and positively correlated to TLC for the scalene (r = 0.17, p = 0.04). Respiratory muscle hypermetabolism was found in 45 patients (28.8%), who had a lower VO2 max (15.4 [14.2-17.5] vs. 17.2 mL/kg/min [15.2-21.1], p = 0.07) and poorer overall survival when adjusting to FEV1% (p < 0.01). CONCLUSION: Our findings show respiratory muscle hypermetabolism is associated with lung function impairment and has prognostic significance. 18 F-FDG/PET-CT should be considered as a tool for assessing respiratory muscle activity and to identify high-risk patients.

Advances in PET and MRI imaging of tumor hypoxia.

Tumor hypoxia is a complex and evolving phenomenon both in time and space. Molecular imaging allows to approach these variations, but the tracers used have their own limitations. PET imaging has the disadvantage of low resolution and must take into account molecular biodistribution, but has the advantage of high targeting accuracy. The relationship between the signal in MRI imaging and oxygen is complex but hopefully it would lead to the detection of truly oxygen-depleted tissue. Different ways of imaging hypoxia are discussed in this review, with nuclear medicine tracers such as [18F]-FMISO, [18F]-FAZA, or [64Cu]-ATSM but also with MRI techniques such as perfusion imaging, diffusion MRI or oxygen-enhanced MRI. Hypoxia is a pejorative factor regarding aggressiveness, tumor dissemination and resistance to treatments. Therefore, having accurate tools is particularly important.

Baseline 18F-FDG Metabolic Tumor Volume Predicts Response to Rituximab Induction in Post-transplant Lymphoproliferative Disorders: A Multi-institutional Retrospective Study.

Post-transplant lymphoproliferative disorder (PTLD) is a rare complication of immunosuppression. Sequential treatment is commonly proposed, combining induction with rituximab (R-induction) followed by either continuation of treatment or addition of chemotherapy depending on response. Response to R-induction, often assessed by CT scan, is a major predictor of overall survival (OS). The aim of the study was to analyze predictive factors of R-induction response, including total metabolic tumor volume (TMTV), and investigate the role of 18F-FDG PET/CT in response assessment. This retrospective multicenter study is based on patients with PTLD included in the K-VIROGREF cohort. Only patients treated by R-induction with a baseline 18F-FDG PET/CT were included. Response to R-induction was assessed by 18F-FDG PET/CT. The optimal threshold of TMTV for rituximab response was determined using receiver operating characteristic curves. Univariate and multivariate analyses were conducted to identify predictive factors of response. A total of 67 patients were included. Survival characteristics were similar to those previously reported: the complete response rate to R-induction was 30%, the 3-year OS estimate was 66%, and the treatment-related mortality was 4%. The optimal threshold for TMTV to predict R-induction response was 135 cm3. The response rate to R-induction was 38% in the 21 patients with TMTV ≥ 135 cm3 and 72% in the 46 patients with TMTV < 135 cm3. TMTV was a significant predictor of response, both at univariate and multivariate analyses (odd ratios = 3.71, P = 0.022). Baseline TMTV is predictive of response to R-induction. Early assessment of patient response is feasible with 18F-FDG PET/CT.

Body Composition to Define Prognosis of Cancers Treated by Anti-Angiogenic Drugs.

Background: Body composition could help to better define the prognosis of cancers treated with anti-angiogenics. The aim of this study is to evaluate the prognostic value of 3D and 2D anthropometric parameters in patients given anti-angiogenic treatments. Methods: 526 patients with different types of cancers were retrospectively included. The software Anthropometer3DNet was used to measure automatically fat body mass (FBM3D), muscle body mass (MBM3D), visceral fat mass (VFM3D) and subcutaneous fat mass (SFM3D) in 3D computed tomography. For comparison, equivalent two-dimensional measurements at the L3 level were also measured. The area under the curve (AUC) of the receiver operator characteristics (ROC) was used to determine the parameters' predictive power and optimal cut-offs. A univariate analysis was performed using Kaplan−Meier on the overall survival (OS). Results: In ROC analysis, all 3D parameters appeared statistically significant: VFM3D (AUC = 0.554, p = 0.02, cutoff = 0.72 kg/m2), SFM3D (AUC = 0.544, p = 0.047, cutoff = 3.05 kg/m2), FBM3D (AUC = 0.550, p = 0.03, cutoff = 4.32 kg/m2) and MBM3D (AUC = 0.565, p = 0.007, cutoff = 5.47 kg/m2), but only one 2D parameter (visceral fat area VFA2D AUC = 0.548, p = 0.034). In log-rank tests, low VFM3D (p = 0.014), low SFM3D (p < 0.0001), low FBM3D (p = 0.00019) and low VFA2D (p = 0.0063) were found as a significant risk factor. Conclusion: automatic and 3D body composition on pre-therapeutic CT is feasible and can improve prognostication in patients treated with anti-angiogenic drugs. Moreover, the 3D measurements appear to be more effective than their 2D counterparts.

The impact of sarcopenia on survival and treatment tolerance in patients with head and neck cancer treated with chemoradiotherapy.

BACKGROUND: Sarcopenia appears to be a negative prognostic factor for poor survival outcomes and worse treatment tolerance in patients with head-and-neck squamous cell carcinoma (HNSCC). We evaluated sarcopenia's impact on overall survival (OS), disease-free survival (DFS) and chemo-radiation tolerance in patients with head-and-neck cancer (HNC) treated with chemoradiotherapy (CRT) from a monocentric observational study. METHODS: We identified patients with HNC treated by CRT between 2009 and 2018 with pretreatment imaging using positron emission tomography-computed tomography scans (PET/CT). Sarcopenia was measured using the pretreatment PET/CT at the L3 vertebral body using previously published methods. Clinical variables were retrospectively retrieved. RESULTS: Of 216 patients identified, 54 patients (25.47%) met the criteria for sarcopenia. These patients had a lower mean body mass index before treatment (21.92 vs. 25.65 cm/m2 , p < 0.001) and were more likely to have a history of smoking (88.89% vs. 71.52%, p = 0.01), alcohol use (55.56% vs. 38.61%, p = 0.03) and positive human papilloma virus status (67.74% vs. 41.75%, p = 0.011). At 3 years of follow-up, OS and DFS were 75% and 70% versus 82% and 85% for sarcopenic and non-sarcopenic patients, respectively (p = 0.1 and p = 0.00015). On multivariate analysis, sarcopenia appeared as a pejorative factor on DFS (hazard ratio 2.174, p = 0.0001) in the overall cohort. Sarcopenic patients did not require more chemotherapy and radiation-treatment interruptions and did not suffer from more chemo-induced and radiation-induced grade 3-4 toxicities than their non-sarcopenic counterparts. CONCLUSION: Sarcopenia in HNSCC patients is an independent adverse prognostic factor for DFS after definitive chemoradiotherapy.

Multi-scale feature similarity-based weakly supervised lymphoma segmentation in PET/CT images.

Accurate lymphoma segmentation in PET/CT images is important for evaluating Diffuse Large B-Cell Lymphoma (DLBCL) prognosis. As systemic multiple lymphomas, DLBCL lesions vary in number and size for different patients, which makes DLBCL labeling labor-intensive and time-consuming. To reduce the reliance on accurately labeled datasets, a weakly supervised deep learning method based on multi-scale feature similarity is proposed for automatic lymphoma segmentation. Weak labeling was performed by randomly dawning a small and salient lymphoma volume for the patient without accurate labels. A 3D V-Net is used as the backbone of the segmentation network and image features extracted in different convolutional layers are fused with the Atrous Spatial Pyramid Pooling (ASPP) module to generate multi-scale feature representations of input images. By imposing multi-scale feature consistency constraints on the predicted tumor regions as well as the labeled tumor regions, weakly labeled data can also be effectively used for network training. The cosine similarity, which has strong generalization, is exploited here to measure feature distances. The proposed method is evaluated with a PET/CT dataset of 147 lymphoma patients. Experimental results show that when using data, half of which have accurate labels and the other half have weak labels, the proposed method performed similarly to a fully supervised segmentation network and achieved an average Dice Similarity Coefficient (DSC) of 71.47%. The proposed method is able to reduce the requirement for expert annotations in deep learning-based lymphoma segmentation.

Using 18F-FDG-PET/CT Metrics to Predict Survival in Ra-Dio-Iodine Refractory Thyroid Cancers.

Radio-iodine refractory (RAI-R) differentiated thyroid cancer (DTC) is a rare disease with a poor prognosis and limited therapeutic resources. Therefore, identifying prognostic factors is essential in order to select patients who could benefit from an early start of treatment. The aim of this study is to identify positron emission tomography with 18F-fluorodeoxyglucose with integrated computed tomography (18F-FDG-PET/CT) parameters to predict overall survival (OS) in patients with RAI-R DTC. In this single-center retrospective study, we analyze the 18F-FDG-PET/CT parameters of 34 patients with RAI-R DTC between April 2007 and December 2019. The parameters collected are MTV, SUVmax and progression for each site of metastasis (neck, mediastinum, lungs, liver, bone) and total sites. ROC curves, Kaplan-Meier survival analysis curves, univariate and multivariate Cox analyses determine prognostic factors for 1-year and 5-year OS. The parameters for mediastinum, liver and total sites are significantly associated with worse 1-year and 5-year OS by both ROC curve analysis and Kaplan-Meier survival analysis. Univariate Cox analysis confirms significance of mediastinum SUVmax (HR 1.08; 95% CI [1.02-1.15]; p = 0.014) and total SUVmax (HR 1.06; 95% CI [1-1.12]; p = 0.042) for worse 1-year OS; of mediastinum SUVmax (HR 1.06; 95% CI [1.02-1.10]; p = 0.003), liver SUVmax (HR 1.04; 95% CI [1.01-1.08]; p = 0.02), liver MTV (HR 2.56; 95% CI [1.13-5.82]; p = 0.025), overall SUVmax (HR 1.05; 95% CI [1.02-1.08]; p = 0.001) and total MTV (HR 1.41; 95% CI [1.07-1.86]; p = 0.016) for worse 5-year OS. Multivariate Cox analysis confirms a significant association between liver MTV (HR 1.02; 95% CI [1-1.04]; p = 0.042) and decrease 1-year OS. In this study, we demonstrate that in RAI-R DTC, 18F-FDG-PET/CT parameters of the mediastinum, liver and overall tumor burden were prognostic factors of poor 1-year and 5-year OS. Identifying these criteria could allow early therapeutic intervention in order to improve patients' survival.

A tumor volume and performance status model to predict outcome before treatment in diffuse large B-cell lymphoma.

Aggressive large B-cell lymphoma (LBCL) has variable outcomes. Current prognostic tools use factors for risk stratification that inadequately identify patients at high risk of refractory disease or relapse before initial treatment. A model associating 2 risk factors, total metabolic tumor volume (TMTV) >220 cm3 (determined by fluorine-18 fluorodeoxyglucose positron emission tomography coupled with computed tomography) and performance status (PS) ≥2, identified as prognostic in 301 older patients in the REMARC trial (#NCT01122472), was validated in 2174 patients of all ages treated in 2 clinical trials, PETAL (Positron Emission Tomography-Guided Therapy of Aggressive Non-Hodgkin Lymphomas; N = 510) and GOYA (N = 1315), and in real-world clinics (N = 349) across Europe and the United States. Three risk categories, low (no factors), intermediate (1 risk factor), and high (2 risk factors), significantly discriminated outcome in most of the series. Patients with 2 risk factors had worse outcomes than patients with no risk factors in the PETAL, GOYA, and real-world series. Patients with intermediate risk also had significantly worse outcomes than patients with no risk factors. The TMTV/Eastern Cooperative Oncology Group-PS combination outperformed the International Prognostic Index with a positive C-index for progression-free survival and overall survival in most series. The combination of high TMTV > 220 cm3 and ECOG-PS ≥ 2 is a simple clinical model to identify aggressive LBCL risk categories before treatment. This combination addresses the unmet need to better predict before treatment initiation for aggressive LBCL the patients likely to benefit the most or not at all from therapy.

Clinical and phantom validation of a deep learning based denoising algorithm for F-18-FDG PET images from lower detection counting in comparison with the standard acquisition.

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 SUVmax 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 SUVmax 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.

Characterization of positioning uncertainties in PET-CT-MR trimodality solutions for radiotherapy.

The purpose of this study was to evaluate the positioning uncertainties of two PET/CT-MR imaging setups, C1 and C2. Because the PET/CT data were acquired on the same hybrid device with automatic image registration, experiments were conducted using CT-MRI data. In C1, a transfer table was used, which allowed the patient to move from one imager to another while maintaining the same position. In C2, the patient stood up and was positioned in the same radiotherapy treatment position on each imager. The two setups provided a set of PET/CT and MR images. The accuracy of the registration software was evaluated on the CT-MRI data of one patient using known translations and rotations of MRI data. The uncertainties on the two setups were estimated using a phantom and a cohort of 30 patients. The accuracy of the positioning uncertainties was evaluated using descriptive statistics and a t-test to determine whether the mean shift significantly deviated from zero (p < 0.05) for each setup. The maximum registration errors were less than 0.97 mm and 0.6° for CT-MRI registration. On the phantom, the mean total uncertainties were less than 2.74 mm and 1.68° for C1 and 1.53 mm and 0.33° for C2. For C1, the t-test showed that the displacements along the z-axis did not significantly deviate from zero (p = 0.093). For C2, significant deviations from zero were present for anterior-posterior and superior-inferior displacements. The mean total uncertainties were less than 4 mm and 0.42° for C1 and less than 1.39 mm and 0.27° for C2 in the patients. Furthermore, the t-test showed significant deviations from zero for C1 on the anterior-posterior and roll sides. For C2, there was a significant deviation from zero for the left-right displacements.This study shows that transfer tables require careful evaluation before use in radiotherapy.

Deep learning analysis of contrast-enhanced spectral mammography to determine histoprognostic factors of malignant breast tumours.

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.

Prognostic value of total tumour volume, adding necrosis to metabolic tumour volume, in advanced or metastatic non-small cell lung cancer treated with first-line pembrolizumab.

BACKGROUND: Metabolic tumour volume (MTV) measured on fluorodeoxyglucose F18 (FDG) positron emission tomography coupled with computed tomography (PET/CT) is a prognostic factor of advanced non-small cell lung cancer (NSCLC) treated by first-line immunotherapy. However, these tumours are often necrotic and the necrosis, which is hypometabolic in PET FDG, is not included in the MTV. The aim of this study was to evaluate the prognostic value of total tumour volume (TTV), adding necrotic tumour volume (NTV) to metabolic tumour volume (MTV). METHODS: We retrospectively included 65 patients with NSCLC treated with pembrolizumab as monotherapy. All patients had a pretreatment FDG PET/CT. PET/CT measured parameters were MTV, NTV and TTV. Clinical, biological and tumour parameters were also retrieved. Receiver operator characteristics (ROC) analysis was performed and overall survival at 1 year was studied using Kaplan-Meier and uni/multivariate Cox analysis. RESULTS: In the ROC analysis, MTV, NTV, TTV, age at diagnosis, polynuclear blood neutrophil, derived neutrophil/leukocyte ratio (dNLR), and haemoglobin had an area under the curve (AUC) significantly higher than 0.5. In Kaplan-Meier analysis, prognosis was worse for patients with high MTV (p = 0.02), high TTV (p = 0.003), high NTV (p = 0.014), low haemoglobin (p < 0.001), older people (p = 0.002), neutrophil polynucleosis (p < 0.001) and dNLR (p = 0.022). All these parameters, except age and neutrophil polynucleosis, were significant prognostic factors in univariate Cox analysis (p < 0.05). In a stepwise multivariate Cox analysis focused on PET parameters, the only significant parameter was TTV (HR = 3.66, p = 0.002) and in a stepwise multivariate Cox analysis exploring all the parameters, a model combining TTV, performance status and brain metastasis was found (p = 0.002). CONCLUSIONS: TTV and NTV measured on pretreatment FDG PET/CT are significant prognosis factor for stage III-IV NSCLC treated by pembrolizumab and TTV could have a higher prognostic value than MTV.

Outcomes after first-line immunochemotherapy for primary mediastinal B-cell lymphoma: a LYSA study.

Primary mediastinal B-cell lymphoma (PMBL) is a rare type of aggressive lymphoma typically affecting young female patients. The first-line standard of care remains debated. We performed a large multicenter retrospective study in 25 centers in France and Belgium to describe PMBL patient outcomes after first-line treatment in real-life settings. A total of 313 patients were enrolled and received rituximab (R) plus ACVBP (doxorubicin, cyclophosphamide, vindesine, bleomycin, and prednisone) (n = 180) or CHOP (cyclophosphamide, doxorubicin, vincristine, and prednisone) delivered every 14 days (R-CHOP14, n = 76) or 21 days (R-CHOP21, n = 57) and consolidation strategies in modalities that varied according to time and institution, mainly guided by positron emission tomography. Consolidation autologous stem cell transplantation was performed for 46 (25.6%), 24 (31.6%), and 1 (1.8%) patient in the R-ACVBP, R-CHOP14, and R-CHOP21 groups, respectively (P < .001); only 17 (5.4%) patients received mediastinal radiotherapy. The end-of-treatment complete metabolic response rates were 86.3%, 86.8%, and 76.6% (P = .23) in the R-ACVBP, R-CHOP14, and R-CHOP21 groups. The median follow-up was 44 months, and the R-ACVBP, R-CHOP14, and R-CHOP21 three-year progression-free survival probabilities were 89.4% (95% confidence interval [CI], 84.8-94.2), 89.4% (95% CI, 82.7-96.6), and 74.7% (95% CI, 64-87.1) (P = .018). A baseline total metabolic tumor volume (TMTV) ≥360 cm3 was associated with a lower progression-free survival (hazard ratio, 2.18; 95% CI, 1.05-4.53). Excess febrile neutropenia (24.4% vs 5.3% vs 5.3%; P < .001) and mucositis (22.8% vs 3.9% vs 1.8%; P < .001) were observed with R-ACVBP compared with the R-CHOP regimens. Patients with PMBL treated with dose-dense immunochemotherapy without radiotherapy have excellent outcomes. R-ACVBP acute toxicity was higher than that of R-CHOP14. Our data confirmed the prognostic importance of baseline TMTV.