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Purpose: In this systematic review and individual patient data (IPD) meta-analysis, we analysed the diagnostic performance of [ 18 F]FDG PET/CT in detecting primary tumours in patients with CUP and evaluated whether the location of the predominant metastatic site influences the diagnostic performance., Methods: A systematic literature search from January 2005 to February 2024 was performed to identify articles describing the diagnostic performance of [ 18 F]FDG PET/CT for primary tumour detection in CUP. Individual patient data retrieved from original articles or obtained from corresponding authors were grouped by the predominant metastatic site. The diagnostic performance of [ 18 F]FDG PET/CT in detecting the underlying primary tumour was compared between predominant metastatic sites., Results: A total of 1865 patients from 32 studies were included. The largest subgroup included patients with predominant bone metastases (n = 622), followed by liver (n = 369), lymph node (n = 358), brain (n = 316), peritoneal (n = 70), lung (n = 67), and soft tissue (n = 23) metastases, leaving a small group of other/undefined metastases (n = 40). [ 18 F]FDG PET/CT resulted in pooled detection rates to identify the primary tumour of 0.74 (for patients with predominant brain metastases), 0.54 (liver-predominant), 0.49 (bone-predominant), 0.46 (lung-predominant), 0.38 (peritoneal-predominant), 0.37 (lymph node-predominant), and 0.35 (soft-tissue-predominant)., Conclusion: This individual patient data meta-analysis suggests that the ability of [ 18 F]FDG PET/CT to identify the primary tumour in CUP depends on the distribution of metastatic sites. This finding emphasises the need for more tailored diagnostic approaches in different patient populations. In addition, alternative diagnostic tools, such as new PET tracers or whole-body (PET/)MRI, should be investigated., Competing Interests: Declarations. Ethical approval: This is a systematic review and individual patient data meta-analysis, for which ethical approval is not required. Consent to participate: Not applicable. Consent to publish: Not applicable. Competing interests: The authors have no relevant financial or non-financial interests to disclose., (© 2024. The Author(s).)

Objective: To investigate whether quantifying local tumour heterogeneity has added benefit compared to global tumour features to predict response to chemoradiotherapy using pre-treatment multiparametric PET and MRI data., Methods: Sixty-one locally advanced rectal cancer patients treated with chemoradiotherapy and staged at baseline with MRI and FDG-PET/CT were retrospectively analyzed. Whole-tumour volumes were segmented on the MRI and PET/CT scans from which global tumour features (T2W volume /T2W entropy /ADC mean /SUV mean /TLG/CT mean-HU ) and local texture features (histogram features derived from local entropy/mean/standard deviation maps) were calculated. These respective feature sets were combined with clinical baseline parameters (e.g. age/gender/TN-stage) to build multivariable prediction models to predict a good (Mandard TRG1-2) versus poor (Mandard TRG3-5) response to chemoradiotherapy. Leave-one-out cross-validation (LOOCV) with bootstrapping was performed to estimate performance in an 'independent' dataset., Results: When using only imaging features, local texture features showed an AUC = 0.81 versus AUC = 0.74 for global tumour features. After internal cross-validation (LOOCV), AUC to predict a good response was the highest for the combination of clinical baseline variables + global tumour features (AUC = 0.83), compared to AUC = 0.79 for baseline + local texture and AUC = 0.76 for all combined (baseline + global + local texture)., Conclusion: In imaging-based prediction models, local texture analysis has potential added value compared to global tumour features to predict response. However, when combined with clinical baseline parameters such as cTN-stage, the added value of local texture analysis appears to be limited. The overall performance to predict response when combining baseline variables with quantitative imaging parameters is promising and warrants further research., Key Points: • Quantification of local tumour texture on pre-therapy FDG-PET/CT and MRI has potential added value compared to global tumour features to predict response to chemoradiotherapy in rectal cancer. • However, when combined with clinical baseline parameters such as cTN-stage, the added value of local texture over global tumour features is limited. • Predictive performance of our optimal model-combining clinical baseline variables with global quantitative tumour features-was encouraging (AUC 0.83), warranting further research in this direction on a larger scale., (© 2021. European Society of Radiology.)

Objectives: To explore the value of multiparametric MRI combined with FDG-PET/CT to identify well-responding rectal cancer patients before the start of neoadjuvant chemoradiation., Methods: Sixty-one locally advanced rectal cancer patients who underwent a baseline FDG-PET/CT and MRI (T2W + DWI) and received long-course neoadjuvant chemoradiotherapy were retrospectively analysed. Tumours were delineated on MRI and PET/CT from which the following quantitative parameters were calculated: T2W volume and entropy, ADC mean and entropy, CT density (mean-HU), SUV maximum and mean, metabolic tumour volume (MTV 42% ) and total lesion glycolysis (TLG). These features, together with sex, age, mrTN-stage ("baseline parameters") and the CRT-surgery interval were analysed using multivariable stepwise logistic regression. Outcome was a good (TRG 1-2) versus poor histopathological response. Performance (AUC) to predict response was compared for different combinations of baseline ± quantitative imaging parameters and performance in an 'independent' dataset was estimated using bootstrapped leave-one-out cross-validation (LOOCV)., Results: The optimal multivariable prediction model consisted of a combination of baseline + quantitative imaging parameters and included mrT-stage (OR 0.004, p < 0.001), T2W-signal entropy (OR 7.81, p = 0.0079) and T2W volume (OR 1.028, p = 0.0389) as the selected predictors. AUC in the study dataset was 0.88 and 0.83 after LOOCV. No PET/CT features were selected as predictors., Conclusions: A multivariable model incorporating mrT-stage and quantitative parameters from baseline MRI can aid in identifying well-responding patients before the start of treatment. Addition of FDG-PET/CT is not beneficial., Key Points: • A multivariable model incorporating the mrT-stage and quantitative features derived from baseline MRI can aid in identifying well-responding patients before the start of neoadjuvant chemoradiotherapy. • mrT-stage was the strongest predictor in the model and was complemented by the tumour volume and signal entropy calculated from T2W-MRI. • Adding quantitative features derived from pre-treatment PET/CT or DWI did not contribute to the model's predictive performance.

Purpose: In this systematic review and individual patient data (IPD) meta-analysis, we analysed the diagnostic performance of [18F]FDG PET/CT in detecting primary tumours in patients with CUP and evaluated whether the location of the predominant metastatic site influences the diagnostic performance. Methods: A systematic literature search from January 2005 to February 2024 was performed to identify articles describing the diagnostic performance of [18F]FDG PET/CT for primary tumour detection in CUP. Individual patient data retrieved from original articles or obtained from corresponding authors were grouped by the predominant metastatic site. The diagnostic performance of [18F]FDG PET/CT in detecting the underlying primary tumour was compared between predominant metastatic sites. Results: A total of 1865 patients from 32 studies were included. The largest subgroup included patients with predominant bone metastases (n = 622), followed by liver (n = 369), lymph node (n = 358), brain (n = 316), peritoneal (n = 70), lung (n = 67), and soft tissue (n = 23) metastases, leaving a small group of other/undefined metastases (n = 40). [18F]FDG PET/CT resulted in pooled detection rates to identify the primary tumour of 0.74 (for patients with predominant brain metastases), 0.54 (liver-predominant), 0.49 (bone-predominant), 0.46 (lung-predominant), 0.38 (peritoneal-predominant), 0.37 (lymph node-predominant), and 0.35 (soft-tissue-predominant). Conclusion: This individual patient data meta-analysis suggests that the ability of [18F]FDG PET/CT to identify the primary tumour in CUP depends on the distribution of metastatic sites. This finding emphasises the need for more tailored diagnostic approaches in different patient populations. In addition, alternative diagnostic tools, such as new PET tracers or whole-body (PET/)MRI, should be investigated. [ABSTRACT FROM AUTHOR]

Aim: The aim was to explore how findings of whole‐body MRI including diffusion‐weighted imaging (DW‐MRI) compared to the routine diagnostic workup with CT and/or 18F‐fluorodeoxyglucose (FDG) positron emission tomography (PET)/CT in patients with suspected recurrent colorectal cancer (CRC). Method: This was an exploratory retrospective analysis of 55 patients with a clinical suspicion of recurrent CRC who underwent DW‐MRI following CT and/or FDG‐PET/CT. Two readers in consensus interpreted all clinical imaging reports and converted each described lesion into a confidence score (1 = definitely benign to 5 = definitely malignant). DW‐MRI findings were compared to the most recent previous CT or PET/CT. Any discrepant or additional DW‐MRI findings were documented and compared with histology and/or clinical follow‐up (if available). Results: Whole‐body MRI including diffusion‐weighted imaging (DW‐MRI) resulted in discrepant/additional findings in 26/55 (47%) cases; 23/37 (62%) compared to previous CT and 3/18 (17%) compared to previous PET/CT. These included 10 cases where DW‐MRI converted previously inconclusive CT (n = 8) or PET/CT (n = 2) findings into a conclusive diagnosis, one where it contradicted a previous CT diagnosis of recurrence, five where DW‐MRI diagnosed recurrent disease not previously reported on CT and 10 cases where DW‐MRI detected additional lesions compared to CT (n = 9) or PET/CT (n = 1). Eighty‐eight per cent of cases with discrepant/additional findings concerned patients with recurrent/metachronous peritoneal metastases. In total, DW‐MRI resulted in 42 discrepant/additional lesions; the DW‐MRI diagnosis was correct in 76% of these lesions and incorrect (false positive) in 7%. In the remaining 17%, no standard of reference was available. Conclusions: This explorative study suggests that DW‐MRI may be of added value to patients with a clinical suspicion for recurrent CRC, in particular to identify patients with peritoneal metastases. DW‐MRI mainly has potential as a 'problem‐solver' in patients with inconclusive or negative findings on previous imaging (in particular CT) and to detect additional disease sites in patients already diagnosed with recurrent disease. [ABSTRACT FROM AUTHOR]