Irene Buvat

Institut Curie - Inserm · Laboratory of Translational Imaging in Oncology

Purpose To determine if pretreatment [18F]FDG PET/CT could contribute to predicting complete pathological complete response (pCR) in patients with early-stage triple-negative breast cancer (TNBC) undergoing neoadjuvant chemotherapy with or without pembrolizumab. Methods In this retrospective bicentric study, we included TNBC patients who underwent...

Background: To investigate the outcomes of patients who underwent curative reirradiation (reRT), with intensity-modulated radiation therapy (IMRT) or proton therapy (PT) for unresectable recurrent or second primary head and neck adenoid cystic carcinoma (HNACC). Methods: Ten patients, mostly KPS 90%, were reirradiated (3/10 with IMRT and 7/10 wi...

e21164 Background: Overall survival of patients with metastatic non-small cell lung cancer (NSCLC) has increased with the use of anti-PD-1 immune checkpoint inhibitors. However, the duration of response remains highly variable between patients, and only 20-30% of patients are alive at 2 years. Thus, new biomarkers for predicting response to treatme...

Introduction: Reliable and automatic lesion segmentation might facilitate the investigation of prognostic image-based biomarkers by reducing the delineation time and inter/intra-observer variability. This work proposes an artificial intelligence (AI) pipeline to automatically detect and segment metabolically active lesions on [18F]-FDG PET images i...

Background Our study aims to identify predictive factors of moderate to severe (grade ≥ 2) late toxicity after reirradiation (reRT) of recurrent head and neck carcinoma (HNC) and explore the correlations between dose organs at risk (OAR) and grade ≥ 2 toxicity. Material and methods Between 09/2007 and 09/2019, 55 patients were re-irradiated with I...

Given the paucity of high-certainty evidence, and differences in opinion on the use of nuclear medicine for hematological malignancies, we embarked on a consensus process involving key experts in this area. We aimed to assess consensus within a panel of experts on issues related to patient eligibility, imaging techniques, staging and response asses...

Automated lesion detection and segmentation might assist radiation therapy planning and contribute to the identification of prognostic image-based biomarkers towards personalized medicine. In this paper, we propose a pipeline to segment the primary and metastatic lymph nodes from fluorodeoxyglucose (FDG) positron emission tomography and computed to...

Trustworthiness is a core tenet of medicine. The patient-physician relationship is evolving from a dyad to a broader ecosystem of healthcare. With the emergence of artificial intelligence (AI) in medicine, the elements of trust must be revisited. We envision a roadmap for the establishment of trustworthy AI ecosystems in nuclear medicine. In this r...

The SNMMI Artificial Intelligence (SNMMI-AI) Summit, organized by the SNMMI AI Task Force, took place in Bethesda, MD on March 21-22, 2022. It brought together various community members and stakeholders from academia, healthcare, industry, patient representatives, and government (NIH, FDA), and considered various key themes to envision and facilita...

PurposeTo evaluate whether radiomics from [18F]-FDG PET and/or MRI before re-irradiation (reRT) of recurrent head and neck cancer (HNC) could predict the occurrence and the location “in-field” or “outside” of a second locoregional recurrence (LR).Methods Among the 55 patients re-irradiated at curative intend for HNC from 2012 to 2019, 48 had an MRI...

Aim/Introduction: Axillary lymph node (ALN) assessment is a key step in breast cancer (BC) management. Yet, the non-invasive evaluation of ALN involvement using imaging lacks sensitivity, and sentinel lymph node excision procedure remains the gold standard. Imaging studies suggested that primary tumor (PT) features might be associated with ALN stat...

Purpose: To analyze outcomes of patients treated with curative reirradiation (reRT), with intensity-modulated radiation therapy (IMRT) or proton therapy (PT) for recurrent head and neck squamous cell carcinoma (HNSCC). Materials: Among the 55 patients reirradiated for head and neck cancer from 30/08/2012 to 08/04/2019, 23 had HNSCC and received...

Total metabolic tumor volume (TMTV) and tumor dissemination (Dmax) calculated from baseline 18F-FDG PET/CT images are prognostic biomarkers in diffuse large B-cell lymphoma (DLBCL) patients. Yet, their automated calculation remains challenging. The purpose of this study was to investigate whether TMTV and Dmax features could be replaced by surrogat...

Introduction: Differential diagnosis between glioma progression and treatment-related radionecrosis using MRI is often difficult [1]. Recent studies have shown the potential of dynamic and dual time [18F]-FDOPA PET as well as radiomics in this context [2, 3]. Yet, the image information on which radiomic models are based remain unclear. In this work...

An important need exists for strategies to perform rigorous objective clinical-task-based evaluation of artificial intelligence (AI) algorithms for nuclear medicine. To address this need, we propose a four-class framework to evaluate AI algorithms for promise, technical task-specific efficacy, clinical decision making, and post-deployment efficacy....

We evaluated the prognostic role of the largest distance between two lesions (Dmax), defined by positron emission tomography (PET) in a retrospective cohort of newly diagnosed classical Hodgkin Lymphoma (cHL) patients. We also explored the molecular bases underlying Dmax through a gene expression analysis of diagnostic biopsies.We included patients...

Objective: In clinical positron emission tomography (PET) imaging, quantification of radiotracer uptake in tumours is often performed using semi-quantitative measurements such as the standardised uptake value (SUV). For small objects, the accuracy of SUV estimates is limited by the noise properties of PET images and the partial volume effect. Ther...

Cancer-Associated Fibroblasts (CAFs) represent the most prominent component of the tumor microenvironment (TME). Recent studies demonstrated that CAF are heterogeneous and composed of different subpopulations exerting distinct functions in cancer. CAF populations differentially modulate various aspects of tumor growth, including cancer cell prolife...

Background: Translation of predictive and prognostic image-based learning models to clinical applications are challenging due in part to their lack of interpretability. Some deep-learning-based methods provide information about the regions driving the model output. Yet, due to the high-level abstraction of deep features, these methods do not comple...

Purpose The identification of pathological mediastinal lymph nodes is an important step in the staging of lung cancer, with the presence of metastases significantly affecting survival rates. Nodes are currently identified by a physician, but this process is time-consuming and prone to errors. In this paper, we investigate the use of artificial inte...

Machine learning is revolutionising medical image analysis, and clearly the future of the field lies in this direction. However, with increasing automation there is a danger of misunderstanding or misinterpreting models. In this paper, we expose an underlying bias in a commonly used publicly available brain tumour MRI dataset. We propose that this...

Positron emission tomography (PET) radiomics applied to oncology allows the measurement of intra-tumoral heterogeneity. This quantification can be affected by image protocols hence there is an increased interest in understanding how radiomic expression on PET images is affected by different imaging conditions. To address that, this study explores h...

The nuclear medicine field has seen a rapid expansion of academic and commercial interests in developing artificial intelligence (AI) algorithms. Users and developers can avoid some of the pitfalls of AI by recognizing and following best practices in AI algorithm development. In this article, recommendations for technical best practices for develop...

PurposeWe evaluated whether biomarkers on baseline [18F]-FDG PET/CT are associated with recurrence after surgery in patients with invasive breast cancer of no special type (NST).Methods In this retrospective single-center study, we included consecutive patients with non-metastatic breast cancer of NST who underwent [18F]-FDG PET/CT before treatment...

Radiomics has undergone considerable development in recent years. In PET imaging, very promising results concerning the ability of handcrafted features to predict the biological characteristics of lesions and to assess patient prognosis or response to treatment have been reported in the literature. This article presents a checklist for designing a...

The impact of PET image acquisition and reconstruction parameters on SUV measurements or radiomic feature values is widely documented. This "scanner" effect is detrimental to the design and validation of predictive or prognostic models and limits the use of large multicenter cohorts. To reduce the impact of this scanner effect, the ComBat method ha...

Background Manual quantification of the metabolic tumor volume (MTV) from whole-body ¹⁸F-FDG PET/CT is time consuming and therefore usually not applied in clinical routine. It has been shown that neural networks might assist nuclear medicine physicians in such quantification tasks. However, little is known if such neural networks have to be designe...

Dissemination, expressed recently by the largest Euclidian distance between lymphoma sites (SDmax), appeared a promising risk factor in DLBCL patients. We investigated alternative distance metrics to characterize the robustness of the dissemination information. In 290 patients from the REMARC trial (NCT01122472), the Euclidean (Euc), Manhattan (Man...

In tomography, quantitative image analysis – or quantitation in short – is the extraction of parameters from an image or a set of images, as opposed to visual analysis. Quantitation is expected to provide objective, accurate, precise, reproducible, and efficient image interpretation, hence making the most of the signal delivered by the imaging devi...

We read with great interest the paper by Ibrahim et al. [...]

Objectives: Translational applications of predictive and prognostic image-based learning models are challenging due to their lack of interpretability. When using deep learning, Class Activation Maps (CAM) give information about the regions driving the models. Yet, due to the high-level abstraction of deep features, deep CAM are difficult to interpr...

We assessed the predictive value of new radiomic features characterizing the lesion dissemination in baseline 18F-FDG PET and tested whether combining them with baseline metabolic tumour volume (MTV) could improve prediction of progression free survival (PFS) and overall survival (OS) in diffuse large B cell lymphoma (DLBCL) patients.

Many studies are devoted to the design of radiomic models for a prediction task. When no effective model is found, it is often difficult to know whether the radiomic features do not include information relevant to the task or because of insufficient data. We propose a downsampling method to answer that question when considering a classification tas...

Objective: Quantitative analysis in MRI is challenging due to variabilities in intensity distributions across patients, acquisitions and scanners and suffers from bias field inhomogeneity. Radiomic studies are impacted by these effects that affect radiomic feature values. This paper describes a dedicated pipeline to increase reproducibility in brea...

Background We analysed the prognostic value of a new baseline PET parameter reflecting the spread of the disease, the largest distance between two lesions (Dmax). We tested its complementarity to metabolic tumor volume (MTV) in a large cohort of diffuse large B cell lymphoma (DLBCL) patients from the REMARC trial (NCT01122472). Patients and method...

State-of-the-art patient management frequently mandates the investigation of both anatomy and physiology of the patients. Hybrid imaging modalities such as the PET/MRI, PET/CT and SPECT/CT have the ability to provide both structural and functional information of the investigated tissues in a single examination. With the introduction of such advance...

Longitudinal mouse PET imaging is becoming increasingly popular due to the large number of transgenic and disease models available but faces challenges. These challenges are related to the small size of the mouse brain and the limited spatial resolution of microPET scanners, along with the small blood volume making arterial blood sampling challengi...

Objective: Test a practical realignment approach to compensate the technical variability of MR radiomic features. Methods: T1 phantom images acquired on 2 scanners, FLAIR and contrast-enhanced T1-weighted (CE-T1w) images of 18 brain tumor patients scanned on both 1.5-T and 3-T scanners, and 36 T2-weighted (T2w) images of prostate cancer patients...

Total metabolic tumor volume (TMTV), calculated from 18F-labeled fluoro-2-deoxyglucose (18F-FDG) positron-emission tomography-computed tomography (PET/CT) baseline studies, is a prognostic factor in diffuse large B-cell lymphoma (DLBCL) whose measurement requires the segmentation of all malignant foci throughout the body. No consensus currently exi...

Background Radiomic features may quantify characteristics present in medical imaging. However, the lack of standardized definitions and validated reference values have hampered clinical use. Purpose To standardize a set of 174 radiomic features. Materials and Methods Radiomic features were assessed in three phases. In phase I, 487 features were der...

Purpose: To design and validate a preprocessing procedure dedicated to T2-weighted MR images of lung cancers so as to improve the ability of radiomic features to distinguish between adenocarcinoma and other histological types. Materials and Methods: A discovery set of 52 patients with advanced lung cancer who underwent T2-weighted MR imaging at 3 T...

Many studies are devoted to the design of radiomic models for a prediction task. When no effective model is found, it is often difficult to know whether the radiomic features do not include information relevant to the task or because of insufficient data. We propose a downsampling method to answer that question when considering a classification tas...

Diagnosis of large vessel vasculitis (LVV) and evaluation of its inflammatory activity can be challenging. Our aim was to investigate the value of hybrid positron-emission tomography/magnetic resonance imaging (PET/MRI) in LVV. All consecutive patients with LVV from the Department of Internal Medicine who underwent PET/MRI were included. Three PET/...

We assessed the prognostic value of new radiomic features (RF) characterizing the lesion dissemination in baseline 18F-FDG PET and tested whether combining them with baseline metabolic tumour volume (MTV) could improve prediction of progression free survival (PFS) and overall survival (OS) in DLBCL patients. Methods: From the LNH073B trial (NCT0049...

Introduction La prise en charge de patients en oncologie digestive est parfois complexe, du fait d’antécédents thérapeutiques lourds (chirurgie, radiofréquence, radiothérapie). L’objectif est d’évaluer l’apport du TEP/MR dans le bilan des récidives des tumeurs abdominopelviennes. Méthodes Vingt-neuf patients du service d’oncologie digestive de l’h...

Overcoming the efflux mediated by ATP–binding cassette (ABC) transporters at the blood-brain barrier (BBB) remains a challenge for the delivery of small molecule tyrosine kinase inhibitors (TKIs) such as erlotinib to the brain. Inhibition of ABCB1 and ABCG2 at the mouse BBB improved the BBB permeation of erlotinib but could not be achieved in human...

Background Lung cancer, and more precisely, non-small cell lung cancer (NSCLC) is the leading cause of cancer-related mortality due to its high prevalence. Likewise, brain metastases from lung cancer are the most frequent type of secondary brain tumors. Different prognostic scores have been proposed to better stratify the treatment of brain metasta...

Objectif La buprénorphine (BUP), utilisée comme traitement de substitution aux opiacés, possède des effets respiratoires plafonnés qui lui confèrent une meilleure marge de sécurité en cas de surdosage. Pourtant, des intoxications avec dépression respiratoire sévère et des décès ont été attribués à la BUP, principalement en cas de co-ingestion d’une...

Background To help interpret measurements in breast tissue and breast tumors from ¹⁸F-FDG PET scans, we studied the influence of age in measurements of PET parameters in normal breast tissue and in a breast cancer (BC) population. Results 522 women were included: 331 pts without history of BC (B-VOI) and 191 patients with BC (T-VOI). In B-VOI, the...

Textural and shape analysis is gaining considerable interest in medical imaging, particularly to identify parameters characterizing tumor heterogeneity and to feed radiomic models. Here, we present a free, multiplatform, and easy-to-use freeware called LIFEx, which enables the calculation of conventional, histogram-based, textural, and shape featur...

Background The diagnosis and the activity determination could be challenging in large-vessel vasculitis (LVV). Objectives The aim of this study was to analyze the value of hybrid PET/MR in LVV. Methods All consecutive patients with LVV who underwent PET/MR were included. PET/MR patterns were defined as inflammatory in the case of positive PET (gr...

Rationale: PET imaging using radiolabeled high-affinity substrates of P-glycoprotein (ABCB1) has convincingly revealed the role of this major efflux transporter in limiting the influx of its substrates from blood into the brain across the blood-brain barrier (BBB). Many drugs, such as metoclopramide, are weak ABCB1 substrates and distribute into th...

Objectif En imagerie TEP, les études multicentriques sont limitées car les mesures effectuées sur les images (SUV et autres index radiomiques) sont sensibles aux protocoles d’acquisition et de reconstruction. Notre but est de valider l’utilisation de la méthode d’harmonisation ComBat afin de supprimer l’« effet centre » dans les études multicentriq...

Objectives Mesiotemporal lobe epilepsy (MTLE) is the most common type of drug-resistant partial epilepsy with a specific history which begins by a status epilepticus due to a neurological insult followed by a silent period before the recurrent seizures begin. Once established, these seizures can become resistant to medications. Along this period a...

Introduction La P-glycoprotéine (P-gp, ABCB1) est un important transporteur d’efflux de la barrière hémato-encéphalique (BHE). Les radiotraceurs d’imagerie TEP actuellement utilisés pour étudier la P-gp sont des substrats de forte affinité. Ils ont permis de montrer que la P-gp limite le passage cérébral xénobiotique du sang vers le cerveau. Cepend...

Introduction La barrière hémato-encéphalique (BHE) constitue une barrière « physique » liée à la présence de jonctions serrées entre les cellules endothéliales. C’est également une barrière « fonctionnelle », du fait de l’existence de transporteurs d’efflux : la P-glycoprotéine (P-gp, ABCB1) et de la Breast Cancer Resistance Protein (BCRP, ABCG2)....

Radiomics is a recent area of research in precision medicine, based on the extraction of a large variety of features from medical images. In the field of radiation oncology, comprehensive image analysis is crucial to personalize treatments. A better characterization of local heterogeneity and shape of the tumor, depicting individual cancer aggressi...