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PURPOSE: The goal of this guideline/procedure standard is to assist nuclear medicine physicians, other nuclear medicine professionals, oncologists or other medical specialists for recommended use of [18F]FDG PET/CT in oncological patients undergoing immunotherapy, with special focus on response assessment in solid tumors. METHODS: In a cooperative effort between the EANM, the SNMMI and the ANZSNM, clinical indications, recommended imaging procedures and reporting standards have been agreed upon and summarized in this joint guideline/procedure standard. CONCLUSIONS: The field of immuno-oncology is rapidly evolving, and this guideline/procedure standard should not be seen as definitive, but rather as a guidance document standardizing the use and interpretation of [18F]FDG PET/CT during immunotherapy. Local variations to this guideline should be taken into consideration. PREAMBLE: The European Association of Nuclear Medicine (EANM) is a professional non-profit medical association founded in 1985 to facilitate worldwide communication among individuals pursuing clinical and academic excellence in nuclear medicine. The Society of Nuclear Medicine and Molecular Imaging (SNMMI) is an international scientific and professional organization founded in 1954 to promote science, technology and practical application of nuclear medicine. The Australian and New Zealand Society of Nuclear Medicine (ANZSNM), founded in 1969, represents the major professional society fostering the technical and professional development of nuclear medicine practice across Australia and New Zealand. It promotes excellence in the nuclear medicine profession through education, research and a commitment to the highest professional standards. EANM, SNMMI and ANZSNM members are physicians, technologists, physicists and scientists specialized in the research and clinical practice of nuclear medicine. All three societies will periodically put forth new standards/guidelines for nuclear medicine practice to help

The goal of this guideline/procedure standard is to assist nuclear medicine physicians, other nuclear medicine professionals, oncologists or other medical specialists for recommended use of [F]FDG PET/CT in oncological patients undergoing immunotherapy, with special focus on response assessment in solid tumors. In a cooperative effort between the EANM, the SNMMI and the ANZSNM, clinical indications, recommended imaging procedures and reporting standards have been agreed upon and summarized in this joint guideline/procedure standard. The field of immuno-oncology is rapidly evolving, and this guideline/procedure standard should not be seen as definitive, but rather as a guidance document standardizing the use and interpretation of [F]FDG PET/CT during immunotherapy. Local variations to this guideline should be taken into consideration. The European Association of Nuclear Medicine (EANM) is a professional non-profit medical association founded in 1985 to facilitate worldwide communication among individuals pursuing clinical and academic excellence in nuclear medicine. The Society of Nuclear Medicine and Molecular Imaging (SNMMI) is an international scientific and professional organization founded in 1954 to promote science, technology and practical application of nuclear medicine. The Australian and New Zealand Society of Nuclear Medicine (ANZSNM), founded in 1969, represents the major professional society fostering the technical and professional development of nuclear medicine practice across Australia and New Zealand. It promotes excellence in the nuclear medicine profession through education, research and a commitment to the highest professional standards. EANM, SNMMI and ANZSNM members are physicians, technologists, physicists and scientists specialized in the research and clinical practice of nuclear medicine. All three societies will periodically put forth new standards/guidelines for nuclear medicine practice to help advance the science of nuclear medicine and i

Response assessment in the context of immunomodulatory treatments represents a major challenge for the medical imaging community and requires a multidisciplinary approach with involvement of oncologists, radiologists, and nuclear medicine specialists. There is evolving evidence that [18F]FDG PET/CT is a useful diagnostic modality for this purpose. The clinical indications for, and the principal aspects of its standardization in this context have been detailed in the recently published "Joint EANM/SNMMI/ANZSNM practice guidelines/procedure standards on recommended use of [18F]FDG PET/CT imaging during immunomodulatory treatments in patients with solid tumors version 1.0". These recommendations arose from a fruitful collaboration between international nuclear medicine societies and experts in cancer treatment. In this perspective, the key elements of the initiative are reported, summarizing the core aspects of the guidelines for radiologists and nuclear medicine physicians. Beyond the previous guidelines, this perspective adds further commentary on how this technology can advance development of novel therapeutic approaches and guide management of individual patients.

Purpose: We present the results of an investigation of the role of FDG PET in response evaluation of bulky masses in paediatric patients with Hodgkin’s lymphoma (HL) enrolled in the Italian AIEOP-LH2004 trial. Methods: We analysed data derived from 703 patients (388 male, 315 female; mean age 13 years) with HL and enrolled in 41 different Italian centres from March 2004 to September 2012, all treated with the AIEOP-LH2004 protocol. The cohort comprised 309 patients with a bulky mass, of whom 263 were evaluated with FDG PET at baseline and after four cycles of chemotherapy. Responses were determined according to combined functional and morphological criteria. Patients were followed up for a mean period of 43 months and for each child we calculated time-to-progression (TTP) and relapse rates considering clinical monitoring, and instrumental and histological data as the reference standard. Statistical analyses were performed for FDG PET and morphological responses with respect to TTP. Multivariate analysis was used to define independent predictive factors. Results: Overall, response evaluation revealed 238 PET-negative patients (90.5%) and 25 PET-positive patients (9.5%), with a significant difference in TTP between these groups (mean TTP: 32.67 months for negative scans, 23.8 months for positive scans; p < 0.0001, log-rank test). In the same cohort, computed tomography showed a complete response (CR) in 85 patients (32.3%), progressive disease (PD) in 6 patients (2.3%), and a partial response (PR) in 165 patients (62.7%), with a significant difference in TTP between patients with CR and patients with PD (31.1 months and 7.9 months, respectively; p < 0.001, log-rank test). Similarly, there was a significant difference in relapse rates between PET-positive and PET-negative patients (p = 0000). In patients with PR, there was also a significant difference in TTP between PET-positive and PET-negative patients (24.6 months and 34.9 months, respectively; p < 0.0001). In the

Background: Positron emission tomography (PET) is a valuable tool for the characterization of brain tumors in vivo. However, few studies have investigated the correlation between carbon-11-methionine (11C-METH) PET metrics and the clinical, radiological, histological, and molecular features of patients affected by lower grade gliomas (LGGs). The present observational study evaluated the relationships between 11C-METH PET metrics and structural magnetic resonance imaging (MRI) findings with the histomolecular biomarkers in patients with LGGs who were candidates for surgery. Methods: We enrolled 96 patients with pathologically proven LGG (51 men, 45 women; age 44.1 ± 13.7 years; 45 with grade II, 51 with grade III), who had been referred from March 2012 to January 2015 for tumor resection and had undergone preoperative 11C-METH PET. The semiquantitative metrics for 11C-METH PET included maximum standardized uptake value (SUVmax), SUV ratio to normal brain, and metabolic tumor burden (MTB). The PET semiquantitative metrics were analyzed and compared with the MRI features, histological diagnosis, isocitrate dehydrogenase-1/2 status, and 1p/19q codeletion. Results: Histological grade was associated with SUVmax (P = 0.002), SUV ratio (P = 0.011), and MTB (P = 0.001), with grade III lesions showing higher values. Among the nonenhancing lesions on MRI, SUVmax (P = 0.001), SUV ratio (P = 0.003) and MTB (P < 0.001) were significantly different statistically for grade II versus grade III. The MRI lesion volume correlated poorly with MTB (r2 = 0.13). The SUVmax and SUV ratio were greater (P < 0.05) in isocitrate dehydrogenase-1/2 wild-type lesions, and the SUV ratio was associated with the presence of the 1p19q codeletion. Conclusions: The 11C-METH PET metrics correlated significantly with histological grade and the molecular profile. Semiquantitative PET metrics can improve the preoperative evaluation of LGGs and thus support clinical decision-making.

Contains fulltext : 238654.pdf (Publisher’s version ) (Open Access), Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials. KEY POINTS: * Data-driven processes like radiomics risk false discoveries due to high-dimensionality of the da

Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials. Key Points: • Data-driven processes like radiomics risk false discoveries due to high-dimensionality

Contains fulltext : 238654.pdf (Publisher’s version ) (Open Access), Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials. KEY POINTS: * Data-driven processes like radiomics risk false discoveries due to high-dimensionality of the da

Contains fulltext : 238654.pdf (Publisher’s version ) (Open Access), Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials. KEY POINTS: * Data-driven processes like radiomics risk false discoveries due to high-dimensionality of the da

Contains fulltext : 220923.pdf (Publisher’s version ) (Closed access)

Contains fulltext : 220923.pdf (Publisher’s version ) (Closed access)

Contains fulltext : 220923.pdf (Publisher’s version ) (Closed access)

This paper follows the immunotherapy symposium held during the European Association of Nuclear Medicine (EANM) 2017 Annual Congress. The biological basis of the immune checkpoint inhibitors and the drugs most frequently used for the treatment of solid tumours are reviewed. The issues of pseudoprogression (frequency, timeline), hyperprogression and immune-related side effects are discussed, as well as their implications for patient management. A review of the recent literature on the use of FDG PET for assessment of immunotherapy is presented, and recommendations are provided for assessing tumour response and reporting immune-related side effects with FDG PET based on published data and experts' experience. Representative clinical cases are also discussed.

The present study investigated the utility of fluorine-18 ( 18 F) fluoro-2-deoxy-D-glucose (FDG) positron emission tomography/computed tomography (PET/CT) in assessing bone marrow involvement (BMI) compared with bone marrow biopsy (BMB) in newly diagnosed pediatric Hodgkin lymphoma (HL). 18 F-FDG PET/CT shows high diagnostic performance in evaluating BMI in pediatric HL. BMB should be ideally reserved for patients with doubtful 18 F-FDG PET/CT BMI findings. Introduction: The present study investigated the utility of fluorine-18 ( 18 F) fluoro-2-deoxy-D-glucose ( 18 F-FDG) positron emission tomography/computed tomography (PET/CT) in assessing bone marrow involvement (BMI) compared with bone marrow biopsy (BMB) in newly diagnosed pediatric Hodgkin lymphoma (HL). Patients and Methods: A total of 224 pediatric patients with HL underwent 18 F-FDG PET/CT at staging. BMB or follow-up imaging was used as the standard of reference for the evaluation of BMI. Results: 18 F-FDG PET/CT was negative for BMI in 193 cases. Of the 193 patients, the findings for 16 were originally reported as doubtful and later interpreted as negative for BMI, with negative findings on follow-up imaging and BMB. At BMB, 1 of the 16 patients (6.25%) had BMI. Of the 193 patients, 192 (99.48%) had negative BMB findings. Thus, the 18 F-FDG PET/CT findings were truly negative for 192 patients and falsely negative for 1 patient for BMI. Conclusion: 18 F-FDG PET/CT showed high diagnostic performance in the evaluation of BMI in pediatric HL. Thus, BMB should be ideally reserved for patients presenting with doubtful 18 F-FDG PET/CT findings for BMI.

Radical external-beam radiotherapy (EBRT) is a standard treatment for prostate cancer (PC) patients. Despite this, the rate of intraprostatic relapses after primary EBRT is still not negligible. There is no consensus on the most appropriate management of these patients after EBRT failure. Treatment strategies after PC relapse are strongly influenced by the effective site of the tumor recurrence, and thus the instrumental evaluation with different imaging techniques becomes crucial. In cases of demonstrated intraprostatic failure, several systemic (androgen deprivation therapy) or local (salvage prostatectomy, cryotherapy, high-intensity focused ultrasound, brachytherapy, stereotactic EBRT) treatment options could be proposed and are currently delivered by clinicians with a variety of results. In this review we analyze the correct definition of intraprostatic relapse after radiotherapy, focusing on the recent developments in imaging to detect intraprostatic recurrence. Furthermore, all available salvage treatment options after a radiation therapy local failure are presented and thoroughly discussed.

Aim: To evaluate the role of postchemotherapy FDG PET and compare it with other predictive factors in paediatric Hodgkin's disease (HD). Materials and methods: In this retrospective study, 98 paediatric patients with HD (enrolled in eight Italian centres) were analysed. Their mean age was 13.8 years (range 5-19 years). A PET scan was performed at the end of chemotherapy and reported as positive or negative on the basis of visual and/or semiquantitative analysis. True outcome was defined as remission or disease on the basis of combined criteria (clinical, instrumental and/or histological) with a mean follow-up period of 25 months. Statistical analyses were performed for the postchemotherapy PET results and other potential predictive factors (age cut-off, stage, presence of bulky masses and therapeutic group) with respect to patient outcome and progression-free survival (PFS). Results: Overall the patients had a mean PFS of 23.5 months (range 4-46 months): 87 achieved remission (88.8%) and 11 showed disease. Of the 98 patients, 17 were positive on postchemotherapy PET. Seven patients (41%) showed disease during follow-up, and relapse occurred in only four out of the 81 patients who were negative on PET (p=0.0001). Kaplan-Meier analysis demonstrated significant correlations between PFS and the postchemotherapy PET result (p=0.0001) and a cut-off age at diagnosis of 13.3 years (p=0.0337), whereas disease stage (p=0.7404), therapeutic group (p=0.5240) and presence of bulky masses (p=0.2208) were not significantly correlated with PFS. Multivariate analysis confirmed a statistically significant correlation with PFS only for the postchemotherapy PET findings (p=0.0009). Conclusion: In paediatric HD, age at diagnosis and postchemotherapy PET results are the main predictors of patient outcome and PFS, with FDG PET being the only independent predictive factor for PFS. © Springer-Verlag 2011

Response evaluation criteria in solid tumours (RECIST) v1.1 are currently the reference standard for evaluating efficacy of therapies in patients with solid tumours who are included in clinical trials, and they are widely used and accepted by regulatory agencies. This expert statement discusses the principles underlying RECIST, as well as their reproducibility and limitations. While the RECIST framework may not be perfect, the scientific bases for the anticancer drugs that have been approved using a RECIST-based surrogate endpoint remain valid. Importantly, changes in measurement have to meet thresholds defined by RECIST for reponse classification within thus partly circumventing the problems of measurement variability. The RECIST framework also applies to clinical patients in individual settings even though the relationship between tumour size changes and outcome from cohort studies is not necessarily translatable to individual cases. As reproducibility of RECIST measurements is impacted by reader experience, choice of target lesions and detection/interpretation of new lesions, it can result in patients changing response categories when measurements are near threshold values or if new lesions are missed or incorrectly interpreted. There are several situations where RECIST will fail to evaluate treatment-induced changes correctly; knowledge and understanding of these is crucial for correct interpretation. Also, some patterns of response/progression cannot be correctly documented by RECIST, particularly in relation to organ-site (e.g. bone without associated soft-tissue lesion) and treatment type (e.g. focal therapies). These require specialist reader experience and communication with oncologists to determine the actual impact of the therapy and best evaluation strategy. In such situations, alternative imaging markers for tumour response may be used but the sources of variability of individual imaging techniques need to be known and accounted for. Communication betwe

Existing Quantitative Imaging Biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials.