Track sealing in CT-guided lung biopsy using gelatin sponge slurry versus saline in reducing post-biopsy pneumothorax: a prospective randomised study.

PURPOSE: To compare the efficacy of two track sealing techniques following CT-guided lung biopsy, using either gelatin sponge slurry (GSS) or saline to reduce the rate of post-biopsy pneumothorax. MATERIALS AND METHODS: In this prospective study, patients referred for a CT-guided lung biopsy, in whom the needle would pass through aerated lung, were randomly assigned to receive either GSS or saline track sealing technique in a 1:1 ratio. All biopsies were performed using a 19-gauge coaxial needle in a tertiary hospital by one of four interventional radiologists with varying levels of experience. The outcomes were pneumothorax occurrence, pneumothorax-related intervention (simple aspiration and/or drainage) and biopsy-related hospital stay length. RESULTS: A total of 266 patients (median age, 66.2 years; range, 25.5-89.2 years; 150 men) were included between July 2019 and January 2023 and randomly distributed to either GSS (n=132) or saline (n=134) groups. Pneumothorax rates were 12.1% in the GSS group and 24.6% in the saline group (p=.008). Hospital length of stay was significantly shorter in the GSS group (p=.003). There was no significant difference in pneumothorax-related intervention between the groups (6.8% vs. 12.7%; p=.107). In the multiple logistic regression analysis, track sealing with GSS was a protective factor for pneumothorax (OR: 0.44, 95%CI: 0.22-0.87; p=.019), and emphysema was associated with higher risk of pneumothorax (OR: 2.67, 95%CI: 1.31-5.44; p=.007). CONCLUSION: Track sealing with GSS following a CT-guided lung biopsy is significantly more efficient than saline in reducing post-biopsy pneumothorax, and results in shorter hospital stay.

2-deoxy-2-[18F]FDG PET Imaging for Therapy Assessment in Hodgkin's and Non-Hodgkin Lymphomas.

The 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography combined with computed tomography (PET/CT) has contributed to outcome improvement of patients with lymphoma. The use of [18F]FDG PET/CT for staging and response assessment is successfully applied both in routine clinical practice and in clinical trials. The challenges lie in enhancing the outcomes of lymphoma patients, particularly those with advanced or refractory/relapsed disease, and to minimize the long-term toxicity associated with treatments, including radiation therapy. The objective of this review article is to present contemporary data on the use of [18F]FDG PET/CT for treatment assessment of aggressive lymphomas.

Prognostic value of visual IMPeTUs criteria and metabolic tumor burden at baseline [18F]FDG PET/CT in patients with newly diagnosed multiple myeloma.

BACKGROUND: 2-[18F]fluoro-2-deoxy-D-glucose ([18F]FDG) positron emission tomography combined with low-dose computed tomography (PET/CT) can be used at diagnosis to identify myeloma-defining events and also provides prognostic factors. The aim of this study was to assess the prognostic significance of baseline [18F]FDG PET/CT visual IMPeTUs (Italian myeloma criteria for PET Use)-based parameters and/or total metabolic tumor volume (TMTV) in a single-center population of patients with newly diagnosed multiple myeloma (NDMM) eligible for transplantation. METHODS: Patients with MM who underwent a baseline [18F]FDG PET/CT were retrospectively selected from a large internal database of the University Hospital of Liege (Liege, Belgium). Initially, all PET/CT images were visually analyzed using IMPeTUs criteria, followed by delineation of TMTV using a semi-automatic lesion delineation workflow, including [18F]FDG-positive MM focal lesions (FL) with an absolute SUV threshold set at 4.0. In a first step, to ensure PET/CT scans accurate reporting, the agreement between two nuclear medicine physicians with distinct experience was assessed. In the second step, univariable and multivariable analyses were conducted to determine the prognostic significance of [18F]FDG PET/CT parameters on progression free survival (PFS) and overall survival (OS), respectively. RESULTS: A total of 40 patients with NDMM were included in the study. The observers agreement in the analysis [18F]FDG PET/CT images was substantial for the presence of spine FL, extra spine FL, at least one fracture and paramedullary disease (Cohen's kappa 0.79, 0.87, 0.75 and 0.64, respectively). For the presence of skull FL and extramedullary disease the agreement was moderate (Cohen's kappa 0.56 and 0.53, respectively). Among [18F]FDG PET/CT parameters, a high number of delineated volumes of interest (VOI) using the SUV4.0 threshold was the only independent prognostic factor associated with PFS [HR (95% CI): 1.03 (1.004-1.05), P = 0.019] while a high number of FL (n > 10; F group 4) was the only independent prognostic factor associated with OS [HR (95% CI): 19.10 (1.90-191.95), P = 0.01]. CONCLUSION: Our work confirms the reproducibility IMPeTUs criteria. Furthermore, it demonstrates that a high number of FL (n > 10; IMPeTUs F group 4), reflecting a high [18F]FDG-avid tumor burden, is an independent prognostic factor for OS. The prognostic value of the TMTV delineated using a SUV4.0 threshold was not significant. Nevertheless, the count of delineated [18F]FDG-avid lesions VOI using a SUV4.0 threshold was an independent prognostic factor for PFS.

[PET/CT in radiotherapy : indications and potential applications]. / TEP/TDM en radiothérapie : indications et perspectives.

Functional imaging, including positron emission tomography combined with computed tomography (PET/CT), allows the evaluation of numerous biological properties that could be considered at all steps of the therapeutic management of patients treated with radiotherapy. Indeed, it enables better initial staging of the disease, and some parameters may also be used as predictive biomarkers for treatment response, allowing better selection of patients eligible for radiotherapy. It may also improve the definition of target volumes with the aim of dose escalations by dose-painting. Finally, it could be useful during the follow-up to assess response to treatment. In this review, we report how functional imaging is integrated at the present time during the radiotherapy procedure, and what are its potential future contributions.

L'imagerie fonctionnelle, dont la tomographie par émission de positons couplée à la tomodensitométrie (TEP/TDM), permet l'évaluation de nombreuses propriétés biologiques qui pourraient être prises en compte à toutes les étapes de la prise en charge des patients traités par radiothérapie. En effet, elle permet une meilleure stadification initiale de la maladie, et certains paramètres peuvent également être utilisés comme biomarqueurs prédictifs de la réponse au traitement, permettant ainsi une meilleure sélection des patients éligibles à la radiothérapie. Elle peut également améliorer la définition des volumes cibles dans le but d'escalader la dose par dose-painting. Enfin, elle pourrait être utile lors du suivi pour évaluer la réponse au traitement. Dans cette revue, nous rapportons comment l'imagerie fonctionnelle est intégrée, à l'heure actuelle, au cours d'un traitement par radiothérapie, et nous discutons quelles sont ses futures contributions potentielles dans les principales localisations tumorales où la radiothérapie est recommandée.

Identification of CT radiomic features robust to acquisition and segmentation variations for improved prediction of radiotherapy-treated lung cancer patient recurrence.

The primary objective of the present study was to identify a subset of radiomic features extracted from primary tumor imaged by computed tomography of early-stage non-small cell lung cancer patients, which remain unaffected by variations in segmentation quality and in computed tomography image acquisition protocol. The robustness of these features to segmentation variations was assessed by analyzing the correlation of feature values extracted from lesion volumes delineated by two annotators. The robustness to variations in acquisition protocol was evaluated by examining the correlation of features extracted from high-dose and low-dose computed tomography scans, both of which were acquired for each patient as part of the stereotactic body radiotherapy planning process. Among 106 radiomic features considered, 21 were identified as robust. An analysis including univariate and multivariate assessments was subsequently conducted to estimate the predictive performance of these robust features on the outcome of early-stage non-small cell lung cancer patients treated with stereotactic body radiation therapy. The univariate predictive analysis revealed that robust features demonstrated superior predictive potential compared to non-robust features. The multivariate analysis indicated that linear regression models built with robust features displayed greater generalization capabilities by outperforming other models in predicting the outcomes of an external validation dataset.

Association between PET/CT Scan Findings, Treatment, and Cancer Incidence in a Cohort of AAA Patients.

Background: Abdominal aortic aneurysm (AAA) is a chronic inflammatory disease that poses several challenges. Given the increasing evidence that AAA patients are more likely to develop cancer and the importance of its early detection, we strived to develop a non-invasive tool based on serial FDG-PET/CT scan examinations to identify, among AAA patients, those at risk of cancer. Methods: Between 2006 and 2011 we recruited 149 AAA patients, free of cancer at baseline, and followed them until the end of 2021. All patients underwent an FDG-PET/CT scan at inclusion and possibly more scans during follow-up. At each medical imaging examination, the aneurysmal FDG uptake was recorded. Patients were stratified based on their aortic wall PET status (negative/positive). Any occurrence of cancer was reported. A Cox regression analysis and competing-risk modeling were applied to the data. Results: The proportion of AAA patients who developed cancer was 31.5% (mean time to diagnosis was 5.7 ± 3.4 years) and the death rate was 59%. A difference in cancer incidence between PET+ and PET- patients was detected (46.8% vs. 27.3%; HR = 1.96, 95%CI: 1.07-3.57, p = 0.028). Moreover, AAA patients undergoing surgical treatment had a lower risk of cancer than unoperated patients (28% vs. 50%; HR = 0.41, 95%CI: 0.21-0.80, p = 0.009). Conclusions: In AAA patients, diagnostic imaging with an FDG-PET/CT scan can help identify those patients at a higher risk of developing cancer. Moreover, the higher cancer risk in non-surgically treated patients calls for further analysis of associations between aneurysm growth and malignant disease.

Predictive clinical and dosimetric parameters for risk of relapse in early-stage non-small cell lung cancer treated by SBRT: A large single institution experience.

Purpose: To evaluate the impact of dosimetric parameters on efficacy of stereotactic body radiation therapy (SBRT) in early-stage non-small cell lung cancer (ES-NSCLC), using Hypofractionated Treatment Effects in the Clinic (HyTEC) reporting standards. Methods: From April 2010 to December 2020, 497 patients who received SBRT for ES-NSCLC at the University Hospital of Liège were retrospectively enrolled. A total dose of 40 to 60 Gy in 3-5 fractions (72-180 Gy biologically effective dose with an α/ß ratio of 10 (BED10)) was prescribed to the 80 % isodose line of the PTV. Potential clinical and dosimetric predictors of recurrence, overall survival (OS) and disease specific survival (DSS) were evaluated using univariate and multivariate analyses. Results: After a median follow-up of 32 months (range 3-143 months), the local control and disease-free survival (DFS) rates at 3 years were 91 % (95 % CI: 90 %-93 %) and 75 % (95 % CI: 73 %-77 %), respectively. The median OS was 41.6 months and the median DSS was not reached. On multivariate analysis, a higher gross tumor volume (GTV) Dmax (BED10) (cut-off 198 Gy) and a larger percent of the GTV receiving ≥110 % of the prescribed dose were predictive of a better local control, only GTV volume was correlated with DSS and no parameter was correlated with OS and regional or distant recurrences. Conclusion: Lung SBRT for ES-NSCLC in 3 to 5 fractions resulted in high local control rates. A higher percent of GTV receiving ≥110 % of the prescribed dose and a higher GTV Dmax (BED10) seem to allow a better local control.

Multicentric development and evaluation of [18F]FDG PET/CT and CT radiomic models to predict regional and/or distant recurrence in early-stage non-small cell lung cancer treated by stereotactic body radiation therapy.

PURPOSE: To develop machine learning models to predict regional and/or distant recurrence in patients with early-stage non-small cell lung cancer (ES-NSCLC) after stereotactic body radiation therapy (SBRT) using [18F]FDG PET/CT and CT radiomics combined with clinical and dosimetric parameters. METHODS: We retrospectively collected 464 patients (60% for training and 40% for testing) from University Hospital of Liège and 63 patients from University Hospital of Brest (external testing set) with ES-NSCLC treated with SBRT between 2010 and 2020 and who had undergone pretreatment [18F]FDG PET/CT and planning CT. Radiomic features were extracted using the PyRadiomics toolbox®. The ComBat harmonization method was applied to reduce the batch effect between centers. Clinical, radiomic, and combined models were trained and tested using a neural network approach to predict regional and/or distant recurrence. RESULTS: In the training (n = 273) and testing sets (n = 191 and n = 63), the clinical model achieved moderate performances to predict regional and/or distant recurrence with C-statistics from 0.53 to 0.59 (95% CI, 0.41, 0.67). The radiomic (original_firstorder_Entropy, original_gldm_LowGrayLevelEmphasis and original_glcm_DifferenceAverage) model achieved higher predictive ability in the training set and kept the same performance in the testing sets, with C-statistics from 0.70 to 0.78 (95% CI, 0.63, 0.88) while the combined model performs moderately well with C-statistics from 0.50 to 0.62 (95% CI, 0.37, 0.69). CONCLUSION: Radiomic features extracted from pre-SBRT analog and digital [18F]FDG PET/CT outperform clinical parameters in the prediction of regional and/or distant recurrence and to discuss an adjuvant systemic treatment in ES-NSCLC. Prospective validation of our models should now be carried out.

External validation of a radiomic signature to predict p16 (HPV) status from standard CT images of anal cancer patients.

The paper deals with the evaluation of the performance of an existing and previously validated CT based radiomic signature, developed in oropharyngeal cancer to predict human papillomavirus (HPV) status, in the context of anal cancer. For the validation in anal cancer, a dataset of 59 patients coming from two different centers was collected. The primary endpoint was HPV status according to p16 immunohistochemistry. Predefined statistical tests were performed to evaluate the performance of the model. The AUC obtained here in anal cancer is 0.68 [95% CI (0.32-1.00)] with F1 score of 0.78. This signature is TRIPOD level 4 (57%) with an RQS of 61%. This study provides proof of concept that this radiomic signature has the potential to identify a clinically relevant molecular phenotype (i.e., the HPV-ness) across multiple cancers and demonstrates potential for this radiomic signature as a CT imaging biomarker of p16 status.

Radiomics and Delta-Radiomics Signatures to Predict Response and Survival in Patients with Non-Small-Cell Lung Cancer Treated with Immune Checkpoint Inhibitors.

The aim of our study was to determine the potential role of CT-based radiomics in predicting treatment response and survival in patients with advanced NSCLC treated with immune checkpoint inhibitors. We retrospectively included 188 patients with NSCLC treated with PD-1/PD-L1 inhibitors from two independent centers. Radiomics analysis was performed on pre-treatment contrast-enhanced CT. A delta-radiomics analysis was also conducted on a subset of 160 patients who underwent a follow-up contrast-enhanced CT after 2 to 4 treatment cycles. Linear and random forest (RF) models were tested to predict response at 6 months and overall survival. Models based on clinical parameters only and combined clinical and radiomics models were also tested and compared to the radiomics and delta-radiomics models. The RF delta-radiomics model showed the best performance for response prediction with an AUC of 0.8 (95% CI: 0.65-0.95) on the external test dataset. The Cox regression delta-radiomics model was the most accurate at predicting survival with a concordance index of 0.68 (95% CI: 0.56-0.80) (p = 0.02). The baseline CT radiomics signatures did not show any significant results for treatment response prediction or survival. In conclusion, our results demonstrated the ability of a CT-based delta-radiomics signature to identify early on patients with NSCLC who were more likely to benefit from immunotherapy.

EANM enabling guide: how to improve the accessibility of clinical dosimetry.

Dosimetry can be a useful tool for personalization of molecular radiotherapy (MRT) procedures, enabling the continuous development of theranostic concepts. However, the additional resource requirements are often seen as a barrier to implementation. This guide discusses the requirements for dosimetry and demonstrates how a dosimetry regimen can be tailored to the available facilities of a centre. The aim is to help centres wishing to initiate a dosimetry service but may not have the experience or resources of some of the more established therapy and dosimetry centres. The multidisciplinary approach and different personnel requirements are discussed and key equipment reviewed example protocols demonstrating these factors are given in the supplementary material for the main therapies carried out in nuclear medicine, including [131I]-NaI for benign thyroid disorders, [177Lu]-DOTATATE and 131I-mIBG for neuroendocrine tumours and [90Y]-microspheres for unresectable hepatic carcinoma.

Multicentric development and evaluation of 18F-FDG PET/CT and MRI radiomics models to predict para-aortic lymph node involvement in locally advanced cervical cancer.

PURPOSE: To develop machine learning models to predict para-aortic lymph node (PALN) involvement in patients with locally advanced cervical cancer (LACC) before chemoradiotherapy (CRT) using 18F-FDG PET/CT and MRI radiomics combined with clinical parameters. METHODS: We retrospectively collected 178 patients (60% for training and 40% for testing) in 2 centers and 61 patients corresponding to 2 further external testing cohorts with LACC between 2010 to 2022 and who had undergone pretreatment analog or digital 18F-FDG PET/CT, pelvic MRI and surgical PALN staging. Only primary tumor volumes were delineated. Radiomics features were extracted using the Radiomics toolbox®. The ComBat harmonization method was applied to reduce the batch effect between centers. Different prediction models were trained using a neural network approach with either clinical, radiomics or combined models. They were then evaluated on the testing and external validation sets and compared. RESULTS: In the training set (n = 102), the clinical model achieved a good prediction of the risk of PALN involvement with a C-statistic of 0.80 (95% CI 0.71, 0.87). However, it performed in the testing (n = 76) and external testing sets (n = 30 and n = 31) with C-statistics of only 0.57 to 0.67 (95% CI 0.36, 0.83). The ComBat-radiomic (GLDZM_HISDE_PET_FBN64 and Shape_maxDiameter2D3_PET_FBW0.25) and ComBat-combined (FIGO 2018 and same radiomics features) models achieved very high predictive ability in the training set and both models kept the same performance in the testing sets, with C-statistics from 0.88 to 0.96 (95% CI 0.76, 1.00) and 0.85 to 0.92 (95% CI 0.75, 0.99), respectively. CONCLUSIONS: Radiomic features extracted from pre-CRT analog and digital 18F-FDG PET/CT outperform clinical parameters in the decision to perform a para-aortic node staging or an extended field irradiation to PALN. Prospective validation of our models should now be carried out.

Unusual Cardiac Manifestations of a Pheochromocytoma in a Girl.

We report the case of an 11-year-old girl who complained about severe asthenia, orthostatic dizziness and abdominal pain for 4 weeks. The primary investigation concluded on febrile urinary tract infection treated by antibiotics. Symptom persistence prompted cardiological and endocrinological investigations. A fluctuation in blood pressure, long QT interval, dilation of the aortic root and left ventricular hypertrophy were documented. Elevated levels of urinary catecholamines together with the presence of a right-sided adrenal mass shown via abdominal ultrasound and magnetic resonance imaging were highly suggestive of a pheochromocytoma. This was confirmed by through iodine-123-metaiodobenzylguathdine ([123I]-mIBG) scintigraphy. Genetic analysis allowed for the exclusion of pathogenic mutations in genes implicated in hereditary paragangliomas and pheochromocytomas but showed a rare somatic mutation in exon 3 of the von Hippel-Lindau gene. The patient was treated with a ß-blocker and calcium channel antagonist and underwent laparoscopic right-sided adrenalectomy. Cardiac manifestations resolved soon after surgery indicating that they were secondary to the pheochromocytoma. After 5 years of follow-up, the patient remains asymptomatic without any sign of tumor recurrence. The presence of aortic root dilation, a prolonged QT-interval and left ventricular hypertrophy may be early cardiac manifestations of a pheochromocytoma in a child and should prompt this diagnosis to be evoked.

Deep learning based identification of bone scintigraphies containing metastatic bone disease foci.

PURPOSE: Metastatic bone disease (MBD) is the most common form of metastases, most frequently deriving from prostate cancer. MBD is screened with bone scintigraphy (BS), which have high sensitivity but low specificity for the diagnosis of MBD, often requiring further investigations. Deep learning (DL) - a machine learning technique designed to mimic human neuronal interactions- has shown promise in the field of medical imaging analysis for different purposes, including segmentation and classification of lesions. In this study, we aim to develop a DL algorithm that can classify areas of increased uptake on bone scintigraphy scans. METHODS: We collected 2365 BS from three European medical centres. The model was trained and validated on 1203 and 164 BS scans respectively. Furthermore we evaluated its performance on an external testing set composed of 998 BS scans. We further aimed to enhance the explainability of our developed algorithm, using activation maps. We compared the performance of our algorithm to that of 6 nuclear medicine physicians. RESULTS: The developed DL based algorithm is able to detect MBD on BSs, with high specificity and sensitivity (0.80 and 0.82 respectively on the external test set), in a shorter time compared to the nuclear medicine physicians (2.5 min for AI and 30 min for nuclear medicine physicians to classify 134 BSs). Further prospective validation is required before the algorithm can be used in the clinic.

The uptake of [18F]-fluorodeoxyglucose by the renal allograft correlates with the acute Banff scores of cortex inflammation but not with the 1-year graft outcomes.

Introduction: [18F]FDG PET/CT noninvasively disproves acute kidney allograft rejection (AR) in kidney transplant recipients (KTRs) with suspected AR. However, the correlation of biopsy-based Banff vs. PET/CT-based scores of acute inflammation remains unknown, as does the prognostic performance of [18F]FDG PET/CT at one year post suspected AR. Methods: From 2012 to 2019, 114 [18F]FDG-PET/CTs were prospectively performed in 105 adult KTRs who underwent per cause transplant biopsies. Ordinal logistic regression assessed the correlation between the extent of histological inflammation and the mean standardized [18F]FDG uptake values (mSUVmean). Functional outcomes of kidney allografts were evaluated at one year post per cause biopsy and correlated to mSUVmean. Results: A significant correlation between mSUVmean and acute Banff score was found, with an adjusted R 2 of 0.25. The mSUVmean was significantly different between subgroups of "total i", with 2.30 ± 0.71 in score 3 vs. 1.68 ± 0.24 in score 0. Neither the function nor the survival of the graft at one year was statistically related to mSUVmean. Discussion: [18F]FDG-PET/CT may help noninvasively assess the severity of kidney allograft inflammation in KTRs with suspected AR, but it does not predict graft outcomes at one year.

Application of artificial intelligence in nuclear medicine and molecular imaging: a review of current status and future perspectives for clinical translation.

Artificial intelligence (AI) will change the face of nuclear medicine and molecular imaging as it will in everyday life. In this review, we focus on the potential applications of AI in the field, both from a physical (radiomics, underlying statistics, image reconstruction and data analysis) and a clinical (neurology, cardiology, oncology) perspective. Challenges for transferability from research to clinical practice are being discussed as is the concept of explainable AI. Finally, we focus on the fields where challenges should be set out to introduce AI in the field of nuclear medicine and molecular imaging in a reliable manner.

The role of PET imaging in inflammatory bowel diseases: state-of-the-art review.

Inflammatory bowel diseases (IBD), i.e. Crohn disease and ulcerative colitis, are autoimmune processes of undetermined origin characterized by the chronic inflammation of the digestive tract. There is no single gold-standard to diagnose IBD which is therefore carried out through the combination of endoscopy, biopsy, radiological and biological investigations; and the development of non-invasive technique allowing the assessment and monitoring of these diseases is necessary. In this state-of-the-art review of the literature, we present the results of PET imaging studies for the diagnosis and staging of IBD (suspected or known), response evaluation to treatment and evaluation of one the main complication, i.e. strictures; explain the reasons why this examination is currently not considered in the IBD guidelines, e.g. radiation exposure, lack of standardization and not validated performances; and finally discuss the perspectives that could possibly allow it to find a place in the future, e.g. digital PET-CT, dynamic PET images acquisition, new radiopharmaceuticals, use of radiomics and use of artificial intelligence for automatically characterize and quantify digestive [18F]FDG uptake.

Facts and Fictions About [18F]FDG versus Other Tracers in Managing Patients with Brain Tumors: It Is Time to Rectify the Ongoing Misconceptions.

MRI is the first-choice imaging technique for brain tumors. Positron emission tomography can be combined together with multiparametric MRI to increase diagnostic confidence. Radiolabeled amino acids have gained wide clinical acceptance. The reported pooled specificity of [18F]FDG positron emission tomography is high and [18F]FDG might still be the first-choice positron emission tomography tracer in cases of World Health Organization grade 3 to 4 gliomas or [18F]FDG-avid tumors, avoiding the use of more expensive and less available radiolabeled amino acids. The present review discusses the additional value of positron emission tomography with a focus on [18F]FDG and radiolabeled amino acids.