Quantitative positron emission tomography/computed tomography (PET/CT) can be used as diagnostic or prognostic tools (i.e. single measurement) or for therapy monitoring (i.e. longitudinal studies) in multicentre studies. Use of quantitative parameters, such as standardized uptake values (SUVs), metabolic active tumor volumes (MATVs) or total lesion glycolysis (TLG), in a multicenter setting requires that these parameters be comparable among patients and sites, regardless of the PET/CT system used. This review describes the motivations and the methodologies for quantitative PET/CT performance harmonization with emphasis on the EANM Research Ltd. (EARL) Fluorodeoxyglucose (FDG) PET/CT accreditation program, one of the international harmonization programs aiming at using FDG PET as a quantitative imaging biomarker. In addition, future accreditation initiatives will be discussed. The validation of the EARL accreditation program to harmonize SUVs and MATVs is described in a wide range of tumor types, with focus on therapy assessment using either the European Organization for Research and Treatment of Cancer (EORTC) criteria or PET Evaluation Response Criteria in Solid Tumors (PERCIST), as well as liver-based scales such as the Deauville score. Finally, also presented in this paper are the results from a survey across 51 EARL-accredited centers reporting how the program was implemented and its impact on daily routine and in clinical trials, harmonization of new metrics such as MATV and heterogeneity features.

PurposeWe prospectively evaluated whether a strategy using point spread function (PSF) reconstruction for both diagnostic and quantitative analysis in non-small cell lung cancer (NSCLC) patients meets the European Association of Nuclear Medicine (EANM) guidelines for harmonization of quantitative values.MethodsThe NEMA NU-2 phantom was used to determine the optimal filter to apply to PSF-reconstructed images in order to obtain recovery coefficients (RCs) fulfilling the EANM guidelines for tumour positron emission tomography (PET) imaging (PSFEANM). PET data of 52 consecutive NSCLC patients were reconstructed with unfiltered PSF reconstruction (PSFallpass), PSFEANM and with a conventional ordered subset expectation maximization (OSEM) algorithm known to meet EANM guidelines. To mimic a situation in which a patient would undergo pre- and post-therapy PET scans on different generation PET systems, standardized uptake values (SUVs) for OSEM reconstruction were compared to SUVs for PSFEANM and PSFallpass reconstruction.ResultsOverall, in 195 lesions, Bland-Altman analysis demonstrated that the mean ratio between PSFEANM and OSEM data was 1.03 [95 % confidence interval (CI) 0.94–1.12] and 1.02 (95 % CI 0.90–1.14) for SUVmax and SUVmean, respectively. No difference was noticed when analysing lesions based on their size and location or on patient body habitus and image noise. Ten patients (84 lesions) underwent two PET scans for response monitoring. Using the European Organization for Research and Treatment of Cancer (EORTC) criteria, there was an almost perfect agreement between OSEMPET1/OSEMPET2 (current standard) and OSEMPET1/PSFEANM-PET2 or PSFEANM-PET1/OSEMPET2 with kappa values of 0.95 (95 % CI 0.91–1.00) and 0.99 (95 % CI 0.96–1.00), respectively. The use of PSFallpass either for pre- or post-treatment (i.e. OSEMPET1/PSFallpass-PET2 or PSFallpass-PET1/OSEMPET2) showed considerably less agreement with kappa values of 0.75 (95 % CI 0.67–0.83) and 0.86 (95 % CI 0.78–0.94), respectively.ConclusionProtocol-optimized images and compliance with EANM guidelines allowed for a reliable pre- and post-therapy evaluation when using different generation PET systems. These data obtained in NSCLC patients could be extrapolated to other solid tumours.Electronic supplementary materialThe online version of this article (doi:10.1007/s00259-013-2391-1) contains supplementary material, which is available to authorized users.

By improving activity recovery, especially for nonenlarged nodes, PSF significantly improves the sensitivity, NPV, and negative LR of FDG-PET for nodal staging in non-small cell lung cancer. These data suggest that preoperative invasive nodal staging may be omitted in the case of a negative PSF FDG-PET/CT.

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PurposeOur purpose was to evaluate the diagnostic and prognostic value of skeletal textural features (TFs) on baseline FDG PET in diffuse large B cell lymphoma (DLBCL) patients.MethodsEighty-two patients with DLBCL who underwent a bone marrow biopsy (BMB) and a PET scan between December 2008 and December 2015 were included. Two readers blinded to the BMB results visually assessed PET images for bone marrow involvement (BMI) in consensus, and a third observer drew a volume of interest (VOI) encompassing the axial skeleton and the pelvis, which was used to assess skeletal TFs. ROC analysis was used to determine the best TF able to diagnose BMI among four first-order, six second-order and 11 third-order metrics, which was then compared for diagnosis and prognosis in disease-free patients (BMB−/PET-) versus patients considered to have BMI (BMB+/PET-, BMB−/PET+, and BMB+/PET+).ResultsTwenty-two out of 82 patients (26.8%) had BMI: 13 BMB−/PET+, eight BMB+/PET+ and one BMB+/PET-. Among the nine BMB+ patients, one had discordant BMI identified by both visual and TF PET assessment. ROC analysis showed that SkewnessH, a first-order metric, was the best parameter for identifying BMI with sensitivity and specificity of 81.8% and 81.7%, respectively. SkewnessH demonstrated better discriminative power over BMB and PET visual analysis for patient stratification: hazard ratios (HR), 3.78 (P = 0.02) versus 2.81 (P = 0.06) for overall survival (OS) and HR, 3.17 (P = 0.03) versus 1.26 (P = 0.70) for progression-free survival (PFS). In multivariate analysis accounting for IPI score, bulky status, haemoglobin and SkewnessH, the only independent predictor of OS was the IPI score, while the only independent predictor of PFS was SkewnessH.ConclusionThe better discriminative power of skeletal heterogeneity for risk stratification compared to BMB and PET visual analysis in the overall population, and more specifically in BMB−/PET- patients, suggests that it can be useful to identify diagnostically overlooked BMI.

I n many countries today, women make up half of medical students, and the number of female students choosing to pursue a career in medical imaging (radiology and nuclear medicine) is rising (1,2). However, the higher up the career ladder, the lower the proportion of women, a phenomenon known as the leaky pipeline (3). Compared with their male colleagues, women are underrepresented as authors, and leadership positions in medical imaging-either within institutions or within scientific organizations, committees, boards, or journals-are still dominated by men (4-6). Examples of challenges women face in general are maledominated cultures and networks, lack of female mentors, and explicit and implicit gender biases in recruitment, research allocation, outcomes of peer reviews, and citations (7-10). Working mothers face the well-described maternal wall bias, where maternal stereotyping and discrimination undermine their professional performance (11).Early reports on the effects of the COVID-19 pandemic on scientific research, all fields concerned, mention the deleterious effect the pandemic might have on the careers of parents working in science, and in particular on the scientific output of female researchers (12)(13)(14)(15)(16)(17). This is due to an unbalanced division of work, as women still perform the majority of household chores and care work, even in developed countries perceived as gender-egalitarian (18,19). Because schools and daycare facilities closed in many countries during the first COVID-19-related lockdown, the pandemic might thus eventually affect female career advancement, as the number and quality of publications in peer-reviewed journals one has authored are essential.The purpose of this study was to investigate whether the COVID-19 pandemic might have an impact on scientific publishing by female physicians in medical imaging. We performed a descriptive bibliometric analysis of female first and last authorship over the 3-month period corresponding to the first lockdown period in most countries due to the COVID-19 pandemic.Background: Early reports show the unequal effect the COVID-19 pandemic might have on men versus women engaged in medical research.Purpose: To investigate whether the COVID-19 pandemic has had an impact on scientific publishing by female physicians in medical imaging. Materials and Methods:The authors conducted a descriptive bibliometric analysis of the gender of the first and last authors of manuscripts submitted to the top 50 medical imaging journals from March to May 2020 (n = 2480) compared with the same period of the year in 2018 (n = 2238) and 2019 (n = 2355). Manuscript title, date of submission, first and last names of the first and last authors, journal impact factor, and author country of provenance were recorded. The Gender-API software was used to determine author gender. Statistical analysis comprised x 2 tests and multivariable logistic regression.

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No significant difference was observed between any of the metrics considered (SUV or heterogeneity features) extracted from OSEM and PSF7 reconstructions. Furthermore, the distributions of TF for OSEM and PSF7 reconstructions according to tumour volumes were similar for all ranges of volumes.Conclusion: PSF reconstruction with Gaussian filtering chosen to meet harmonizing standards resulted in similar SUV values and heterogeneity information, compared to OSEM images, which validates its use within the harmonization strategy context. However, unfiltered PSF-reconstructed images also showed higher heterogeneity according to some metrics, as well as a wider range of heterogeneity values than OSEM images, for most of the metrics considered, especially when analysing larger tumours. This suggests that, whenever 3 available, unfiltered PSF images should also be exploited to obtain the most discriminative quantitative heterogeneity features.