Application of the Lugano Classification for Initial Evaluation, Staging, and Response Assessment of Hodgkin and Non-Hodgkin Lymphoma: The PRoLoG Consensus Initiative (Part 1-Clinical).

Our objective was to provide consensus recommendations from a consortium of academic and industry experts in the field of lymphoma and imaging for consistent application of the Lugano classification. Methods: Consensus was obtained through a series of meetings from July 2019 until September 2021 sponsored by the Pharma Imaging Network for Therapeutics and Diagnostics (PINTaD) as part of the PINTaD Response Criteria in Lymphoma Working Group (PRoLoG) consensus initiative. Results: Consensus recommendations clarified technical considerations for PET/CT and diagnostic CT from the Lugano classification, including updating the FDG avidity of different lymphoma entities, clarifying the response nomenclature, and refining lesion classification and scoring, especially with regard to scores 4 and 5 and the X category of the 5-point scale. Combination of metabolic and anatomic responses is clarified, as well as response assessment in cases of discordant or missing evaluations. Use of clinical data in the classification, especially the requirement for bone marrow assessment, is further updated on the basis of lymphoma entities. Clarification is provided with regard to spleen and liver measurements and evaluation, as well as nodal response. Conclusion: Consensus recommendations are made to comprehensively address areas of inconsistency and ambiguity in the classification encountered during response evaluation by end users, and such guidance should be used as a companion to the 2014 Lugano classification.

Application of the Lugano Classification for Initial Evaluation, Staging, and Response Assessment of Hodgkin and Non-Hodgkin Lymphoma: The PRoLoG Consensus Initiative (Part 2-Technical).

The aim of this initiative was to provide consensus recommendations from a consortium of academic and industry experts in the field of lymphoma and imaging for the consistent application of imaging assessment with the Lugano classification. Methods: Consensus was obtained through a series of meetings from July 2019 to October 2021 sponsored by the PINTaD (Pharma Imaging Network for Therapeutics and Diagnostics) as part of the ProLoG (PINTaD RespOnse criteria in Lymphoma wOrking Group) consensus initiative. Results: Consensus recommendations encompass all technical imaging aspects of the Lugano classification. Some technical considerations for PET/CT and diagnostic CT are clarified with regards to required imaging series and scan visits, as well as acquisition and reconstruction of PET images and influence of lesion size and background activity. Recommendations are given on the role of imaging and clinical reviewers as well as on training and monitoring. Finally, an example template of an imaging case report form is provided to support efficient collection of data with Lugano Classification. Conclusion: Consensus recommendations are made to comprehensively address technical and imaging areas of inconsistency and ambiguity in the classification encountered by end users. Such guidance should be used to support standardized acquisition and evaluation with the Lugano 2014.

A novel read methodology to evaluate the optimal dose of 68Ga-satoreotide trizoxetan as a PET imaging agent in patients with gastroenteropancreatic neuroendocrine tumours: a phase II clinical trial.

BACKGROUND: 68Ga-satoreotide trizoxetan is a novel somatostatin receptor antagonist exhibiting higher tumour-to-background ratios and sensitivity compared to 68Ga-DOTATOC. This randomised, 2 × 3 factorial, phase II study aimed to confirm the optimal peptide mass and radioactivity ranges for 68Ga-satoreotide trizoxetan, using binary visual reading. To that end, 24 patients with metastatic gastroenteropancreatic neuroendocrine tumours received 5-20 µg of 68Ga-satoreotide trizoxetan on day 1 of the study and 30-45 µg on day 16-22, with one of three gallium-68  radioactivity ranges (40-80, 100-140, or 160-200 MBq) per visit. Two 68Ga-satoreotide trizoxetan PET/CT scans were acquired from each patient post-injection, and were scored by experienced independent blinded readers using a binary system (0 for non-optimal image quality and 1 for optimal image quality). For each patient pair of 68Ga-satoreotide trizoxetan scans, one or both images could score 1. RESULTS: Total image quality score for 68Ga-satoreotide trizoxetan PET scans was lower in the 40-80 MBq radioactivity range (56.3%) compared to 100-140 MBq (90.6%) and 160-200 MBq (81.3%). Both qualitative and semi-quantitative analysis showed that peptide mass (5-20 or 30-45 µg) did not influence 68Ga-satoreotide trizoxetan imaging. There was only one reading where readers diverged on scoring; one reader preferred one image because of higher lesion conspicuity, and the other reader preferred the alternative image because of the ability to identify more lesions. CONCLUSIONS: Binary visual reading, which was associated with a low inter-reader variability, has further supported that the optimal administered radioactivity of 68Ga-satoreotide trizoxetan was 100-200 MBq with a peptide mass up to 50 µg. Trial registration ClinicalTrials.gov, NCT03220217. Registered 18 July 2017, https://clinicaltrials.gov/ct2/show/NCT03220217.

Pre- and per-treatment 18F-FDG PET/CT parameters to predict recurrence and survival in cervical cancer.

PURPOSE: To describe the evolution and to assess the predictive value of metabolic parameters with different SUV threshold segmentations calculated from two 18F-FDG-PET/CT, one prior to and the other one during concomitant chemoradiation therapy (CCRT), for locally-advanced cervical cancer (LACC). MATERIAL AND METHODS: 53 patients treated for LACC by CCRT underwent FDG-PET/CT before treatment (PET1) and another one at 40Gy (PET2). The PET analyzed parameters were: maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG). MTVs were automatically segmented using various percentage SUVmax thresholds (30-70%) and fixed SUV thresholds (all voxels with SUV >1-20). The parameters' predictive capabilities for disease-free (DFS) and overall survival (OS) were assessed using the Harrell's C-index (c) and Cox regression model. RESULTS: Depending on the SUVmax threshold, the relative decreases in MTV and TLG from PET1 to PET2 were, on average, 65% (range: 63-70%) and 85% (range: 83-86%), respectively. The strongest predictive threshold segmentations were 55% SUVmax in PET1 and 32% in PET2. Significant predictors of DFS in multivariate analysis (c=0.82) were MTV1 (55% SUVmax) in PET1 and TLG2 (32% SUVmax) in PET2. MTV1 (55%) was the most significant OS predictor. CONCLUSIONS: MTV and TLG calculated with a threshold of 55% SUVmax and 32% SUVmax from pre- and per-treatment PET scans respectively, can be used to predict patient outcome after CCRT for LACC.

Detection of bladder metabolic artifacts in (18)F-FDG PET imaging.

Positron emission tomography using (18)F-fluorodeoxyglucose ((18)F-FDG-PET) is a widely used imaging modality in oncology. It enables significant functional information to be included in analyses of anatomical data provided by other image modalities. Although PET offers high sensitivity in detecting suspected malignant metabolism, (18)F-FDG uptake is not tumor-specific and can also be fixed in surrounding healthy tissue, which may consequently be mistaken as cancerous. PET analyses may be particularly hampered in pelvic-located cancers by the bladder׳s physiological uptake potentially obliterating the tumor uptake. In this paper, we propose a novel method for detecting (18)F-FDG bladder artifacts based on a multi-feature double-step classification approach. Using two manually defined seeds (tumor and bladder), the method consists of a semi-automated double-step clustering strategy that simultaneously takes into consideration standard uptake values (SUV) on PET, Hounsfield values on computed tomography (CT), and the distance to the seeds. This method was performed on 52 PET/CT images from patients treated for locally advanced cervical cancer. Manual delineations of the bladder on CT images were used in order to evaluate bladder uptake detection capability. Tumor preservation was evaluated using a manual segmentation of the tumor, with a threshold of 42% of the maximal uptake within the tumor. Robustness was assessed by randomly selecting different initial seeds. The classification averages were 0.94±0.09 for sensitivity, 0.98±0.01 specificity, and 0.98±0.01 accuracy. These results suggest that this method is able to detect most (18)F-FDG bladder metabolism artifacts while preserving tumor uptake, and could thus be used as a pre-processing step for further non-parasitized PET analyses.

Inter-Method Performance Study of Tumor Volumetry Assessment on Computed Tomography Test-Retest Data.

RATIONALE AND OBJECTIVES: Tumor volume change has potential as a biomarker for diagnosis, therapy planning, and treatment response. Precision was evaluated and compared among semiautomated lung tumor volume measurement algorithms from clinical thoracic computed tomography data sets. The results inform approaches and testing requirements for establishing conformance with the Quantitative Imaging Biomarker Alliance (QIBA) Computed Tomography Volumetry Profile. MATERIALS AND METHODS: Industry and academic groups participated in a challenge study. Intra-algorithm repeatability and inter-algorithm reproducibility were estimated. Relative magnitudes of various sources of variability were estimated using a linear mixed effects model. Segmentation boundaries were compared to provide a basis on which to optimize algorithm performance for developers. RESULTS: Intra-algorithm repeatability ranged from 13% (best performing) to 100% (least performing), with most algorithms demonstrating improved repeatability as the tumor size increased. Inter-algorithm reproducibility was determined in three partitions and was found to be 58% for the four best performing groups, 70% for the set of groups meeting repeatability requirements, and 84% when all groups but the least performer were included. The best performing partition performed markedly better on tumors with equivalent diameters greater than 40 mm. Larger tumors benefitted by human editing but smaller tumors did not. One-fifth to one-half of the total variability came from sources independent of the algorithms. Segmentation boundaries differed substantially, not ony in overall volume but also in detail. CONCLUSIONS: Nine of the 12 participating algorithms pass precision requirements similar to what is indicated in the QIBA Profile, with the caveat that the present study was not designed to explicitly evaluate algorithm profile conformance. Change in tumor volume can be measured with confidence to within ±14% using any of these nine algorithms on tumor sizes greater than 10 mm. No partition of the algorithms was able to meet the QIBA requirements for interchangeability down to 10 mm, although the partition comprising best performing algorithms did meet this requirement for a tumor size of greater than approximately 40 mm.

Weighted quantification of ¹8F-FDG tumor metabolism activity using fuzzy-thresholding to predict post-treatment tumor recurrence.

Cervical cancer is one of the most common cancer to affect women worldwide. Despite the efficiency of radiotherapy treatment, some patients present post-treatment tumor recurrence which increases the risk of death. Early outcome prediction could help oncologists to adapt the treatment. Several studies suggest that quantification of tumor activity using (18)FFDG PET imaging could be used to predict post-treatment tumor recurrence. In this paper we study the predictive value of weighted quantification of tumor metabolism extracted by fuzzy-thresholding for tumor recurrence of locally advanced cervical cancer. Fifty-three patients with locally advanced cervical cancer treated by chemo-radiotherapy were considered in our study. For each patient, a coregistered (18)F-FDG PET/CT scan was acquired before the treatment and was segmented using different hard and fuzzy segmentations methods. The tumor activity was extracted through the total lesion glycolysis and through a weighted analog of the total lesion glycolysis using the probability maps provided by the fuzzy segmentations. Outcomes prediction was performed using the area under the receiver operating characteristic curve (AUC) and the Harrell's C-index. Results suggest that weighted quantification of tumor activity seems to be strongly informative and could be used to predict post-treatment tumor recurrence in cervical cancer.