Post-treatment FDG PET-CT in head and neck carcinoma: comparative analysis of 4 qualitative interpretative criteria in a large patient cohort

There is no consensus regarding optimal interpretative criteria (IC) for Fluorine-18 fluorodeoxyglucose (FDG) Positron Emission Tomography – Computed Tomography (PET-CT) response assessment following (chemo)radiotherapy (CRT) for head and neck squamous cell carcinoma (HNSCC). The aim was to compare accuracy of IC (NI-RADS, Porceddu, Hopkins, Deauville) for predicting loco-regional control and progression free survival (PFS). All patients with histologically confirmed HNSCC treated at a specialist cancer centre with curative-intent non-surgical treatment who underwent baseline and response assessment FDG PET-CT between August 2008 and May 2017 were included. Metabolic response was assessed using 4 different IC harmonised into 4-point scales (complete response, indeterminate, partial response, progressive disease). IC performance metrics (sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy) were compared. Kaplan-Meier and Cox proportional hazards regression analyses were performed for survival analysis. 562 patients were included (397 oropharynx, 53 hypopharynx, 48 larynx, 64 other/unknown primary). 420 patients (75%) received CRT and 142 (25%) had radiotherapy alone. Median follow-up was 26 months (range 3–148). 156 patients (28%) progressed during follow-up. All IC were accurate for prediction of primary tumour (mean NPV 85.0% (84.6–85.3), PPV 85.0% (82.5–92.3), accuracy 84.9% (84.2–86.0)) and nodal outcome (mean NPV 85.6% (84.1–86.6), PPV 94.7% (93.8–95.1), accuracy 86.8% (85.6–88.0)). Number of indeterminate scores for NI-RADS, Porceddu, Deauville and Hopkins were 91, 25, 20, 13 and 55, 70, 18 and 3 for primary tumour and nodes respectively. PPV was significantly reduced for indeterminate uptake across all IC (mean PPV primary tumour 36%, nodes 48%). Survival analyses showed significant differences in PFS between response categories classified by each of the four IC (p <0.001). All four IC have similar diagnostic performance characteristics although Porceddu and Deauville scores offered the best trade off of minimising indeterminate outcomes whilst maintaining a high NPV

The Impact of 18F-FDG PET CT Prior to Chemoradiotherapy for Stage III/IV Head and Neck Squamous Cell Carcinoma

Introduction. To determine the value of a FDG-PET-CT scan in patients with locally advanced head and neck squamous cell carcinoma (HNSCC) prior to chemoradiotherapy. Materials and Methods. Consecutive patients with stage III or IV HNSCC who had undergone a staging FDG-PET-CT scan prior to chemoradiotherapy between August 2008 and April 2011 were included. Clinical details and conventional imaging (CT and/or MRI) were, retrospectively, reviewed, a TNM stage was assigned, and levels of cervical lymph node involvement were documented. This process was repeated with the addition of FDG-PET-CT. Radiotherapy plans were reviewed for patients with an alteration identified on TNM staging and/or nodal level identification with FDG-PET-CT and potential alterations in radiotherapy planning were documented. Results. 55 patients were included in the analysis. FDG-PET-CT altered the TNM stage in 17/55 (31%) of patients, upstaging disease in 11 (20%) and downstaging in 6 (11%); distant metastases were identified by FDG-PET-CT in 1 (2%) patient. FDG-PET-CT altered the lymph node levels identified in 22 patients (40%), upclassifying disease in 16 (29%) and downclassifying in 6 (11%). Radiotherapy plans were judged retrospectively to have been altered by FDG-PET-CT in 10 patients (18%). Conclusions. The use of FDG-PET-CT potentially impacts upon both treatment decisions and radiotherapy planning

Diagnostic performance of a streamlined 18 F-choline PET-CT protocol for the detection of prostate carcinoma recurrence in combination with appropriate-use criteria

Aim To evaluate the efficacy of single time-point half-body (skull base to thighs) fluorine-18 choline positron emission tomography-computed tomography (PET-CT) compared to a triple-phase acquisition protocol in the detection of prostate carcinoma recurrence. Materials and methods Consecutive choline PET-CT studies performed at a single tertiary referral centre in patients with biochemical recurrence of prostate carcinoma between September 2012 and March 2017 were reviewed retrospectively. The indication for the study, imaging protocol used, imaging findings, whether management was influenced by the PET-CT, and subsequent patient outcome were recorded. Results Ninety-one examinations were performed during the study period; 42 were carried out using a triple-phase protocol (dynamic pelvic imaging for 20 minutes after tracer injection, half-body acquisition at 60 minutes and delayed pelvic scan at 90 minutes) between 2012 and August 2015. Subsequently following interim review of diagnostic performance, a streamlined protocol and appropriate-use criteria were introduced. Forty-nine examinations were carried out using the single-phase protocol between 2015 and 2017. Twenty-nine (69%) of the triple-phase studies were positive for recurrence compared to 38 (78%) of the single-phase studies. Only one patient who had a single-phase study would have benefited from a dynamic acquisition, they have required no further treatment or imaging and are currently under prostate-specific antigen (PSA) surveillance. Conclusion Choline PET-CT remains a useful tool for the detection of prostate recurrence when used in combination with appropriate-use criteria. Removal of dynamic and delayed acquisition phases reduces study time without adversely affecting accuracy. Benefits include shorter imaging time which improves patient comfort, reduced cost, and improved scanner efficiency

Multimodality imaging with CT, MR and FDG-PET for radiotherapy target volume delineation in oropharyngeal squamous cell carcinoma

Background: This study aimed to quantify the variation in oropharyngeal squamous cell carcinoma gross tumour volume (GTV) delineation between CT, MR and FDG PET-CT imaging. Methods: A prospective, single centre, pilot study was undertaken where 11 patients with locally advanced oropharyngeal cancers (2 tonsil, 9 base of tongue primaries) underwent pre-treatment, contrast enhanced, FDG PET-CT and MR imaging, all performed in a radiotherapy treatment mask. CT, MR and CT-MR GTVs were contoured by 5 clinicians (2 radiologists and 3 radiation oncologists). A semi-automated segmentation algorithm was used to contour PET GTVs. Volume and positional analyses were undertaken, accounting for inter-observer variation, using linear mixed effects models and contour comparison metrics respectively. Results: Significant differences in mean GTV volume were found between CT (11.9 cm³) and CT-MR (14.1 cm³), p < 0.006, CT-MR and PET (9.5 cm³), p < 0.0009, and MR (12.7 cm³) and PET, p < 0.016. Substantial differences in GTV position were found between all modalities with the exception of CT-MR and MR GTVs. A mean of 64 %, 74 % and 77 % of the PET GTVs were included within the CT, MR and CT-MR GTVs respectively. A mean of 57 % of the MR GTVs were included within the CT GTV; conversely a mean of 63 % of the CT GTVs were included within the MR GTV. CT inter-observer variability was found to be significantly higher in terms of position and/or volume than both MR and CT-MR (p < 0.05). Significant differences in GTV volume were found between GTV volumes delineated by radiologists (9.7 cm³) and oncologists (14.6 cm³) for all modalities (p = 0.001). Conclusions: The use of different imaging modalities produced significantly different GTVs, with no single imaging technique encompassing all potential GTV regions. The use of MR reduced inter-observer variability. These data suggest delineation based on multimodality imaging has the potential to improve accuracy of GTV definition. Trial registration: ISRCTN Registry: ISRCTN34165059. Registered 2nd February 2015

Intensity standardization of MRI prior to radiomic feature extraction for artificial intelligence research in glioma-a systematic review

Objectives Radiomics is a promising avenue in non-invasive characterisation of diffuse glioma. Clinical translation is hampered by lack of reproducibility across centres and difficulty in standardising image intensity in MRI datasets. The study aim was to perform a systematic review of different methods of MRI intensity standardisation prior to radiomic feature extraction. Methods MEDLINE, EMBASE, and SCOPUS were searched for articles meeting the following eligibility criteria: MRI radiomic studies where one method of intensity normalisation was compared with another or no normalisation, and original research concerning patients diagnosed with diffuse gliomas. Using PRISMA criteria, data were extracted from short-listed studies including number of patients, MRI sequences, validation status, radiomics software, method of segmentation, and intensity standardisation. QUADAS-2 was used for quality appraisal. Results After duplicate removal, 741 results were returned from database and reference searches and, from these, 12 papers were eligible. Due to a lack of common pre-processing and different analyses, a narrative synthesis was sought. Three different intensity standardisation techniques have been studied: histogram matching (5/12), limiting or rescaling signal intensity (8/12), and deep learning (1/12)—only two papers compared different methods. From these studies, histogram matching produced the more reliable features compared to other methods of altering MRI signal intensity. Conclusion Multiple methods of intensity standardisation have been described in the literature without clear consensus. Further research that directly compares different methods of intensity standardisation on glioma MRI datasets is required. Key Points • Intensity standardisation is a key pre-processing step in the development of robust radiomic signatures to evaluate diffuse glioma. • A minority of studies compared the impact of two or more methods. • Further research is required to directly compare multiple methods of MRI intensity standardisation on glioma datasets

Artificial intelligence in ovarian cancer histopathology: a systematic review

This study evaluates the quality of published research using artificial intelligence (AI) for ovarian cancer diagnosis or prognosis using histopathology data. A systematic search of PubMed, Scopus, Web of Science, Cochrane CENTRAL, and WHO-ICTRP was conducted up to May 19, 2023. Inclusion criteria required that AI was used for prognostic or diagnostic inferences in human ovarian cancer histopathology images. Risk of bias was assessed using PROBAST. Information about each model was tabulated and summary statistics were reported. The study was registered on PROSPERO (CRD42022334730) and PRISMA 2020 reporting guidelines were followed. Searches identified 1573 records, of which 45 were eligible for inclusion. These studies contained 80 models of interest, including 37 diagnostic models, 22 prognostic models, and 21 other diagnostically relevant models. Common tasks included treatment response prediction (11/80), malignancy status classification (10/80), stain quantification (9/80), and histological subtyping (7/80). Models were developed using 1–1375 histopathology slides from 1–776 ovarian cancer patients. A high or unclear risk of bias was found in all studies, most frequently due to limited analysis and incomplete reporting regarding participant recruitment. Limited research has been conducted on the application of AI to histopathology images for diagnostic or prognostic purposes in ovarian cancer, and none of the models have been demonstrated to be ready for real-world implementation. Key aspects to accelerate clinical translation include transparent and comprehensive reporting of data provenance and modelling approaches, and improved quantitative evaluation using cross-validation and external validations. This work was funded by the Engineering and Physical Sciences Research Council

Salvage Reirradiation Options for Locally Recurrent Prostate Cancer: A Systematic Review.

Background: Reirradiation using brachytherapy (BT) and external beam radiation therapy (EBRT) are salvage strategies with locally radiorecurrent prostate cancer. This systematic review describes the oncologic and toxicity outcomes for salvage BT and EBRT [including Stereotactic Body Radiation Therapy (SBRT)]. Methods: An International Prospective Register of Systematic Reviews (PROSPERO) registered (#211875) study was conducted using Preferred Reporting Items for Systematic reviews and Meta-analyses (PRISMA) guidelines. EMBASE and MEDLINE databases were searched from inception to December 2020. For BT, both low dose rate (LDR) and high dose rate (HDR) BT techniques were included. Two authors independently assessed study quality using the 18-item Modified Delphi technique. Results: A total of 39 eligible studies comprising 1967 patients were included (28 BT and 11 SBRT). In 35 studies (90%), the design was single centre and/or retrospective and no randomised prospective studies were found. Twelve BT studies used LDR only, 11 HDR only, 4 LDR or HDR and 1 pulsed-dose rate only. All EBRT studies used SBRT exclusively, four with Cyberknife alone and 7 using both Cyberknife and conventional linear accelerator treatments. Median (range) modified Delphi quality score was 15 (6-18). Median (range) follow-up was 47.5 months (13-108) (BT) and 25.4 months (21-44) (SBRT). For the LDR-BT studies, the median (range) 2-year and 5-year bRFS rates were 71% (48-89.5) and 52.5% (20-79). For the HDR-BT studies, the median (range) 2-year and 5-year bRFS rates were 74% (63-89) and 51% (45-65). For the SBRT studies, the median (range) 2-year bRFS for the SBRT group was 54.9% (40-80). Mean (range) acute and late grade≥3 GU toxicity rates for LDR-BT/HDR-BT/SBRT were 7.4%(0-14)/2%(0-14)/2.7%(0-8.7) and 13.6%(0-30)/7.9%(0-21.3%)/2.7%(0-8%). Mean (range) acute and late grade≥3 GI toxicity rates for LDR-BT/HDR-BT/SBRT were 6.5%(0-19)/0%/0.5%(0-4%) and 6.4%(0-20)/0.1%(0-0.9)/0.2%(0-1.5). One third of studies included Patient Reported Outcome Measures (PROMs). Conclusions: Salvage reirradiation of radiorecurrent prostate cancer using HDR-BT or SBRT provides similar biochemical control and acceptable late toxicity. Salvage LDR-BT is associated with higher late GU/GI toxicity. Challenges exist in comparing BT and SBRT from inconsistencies in reporting with missing data, and prospective randomised trials are needed

Prediction of outcome in anal squamous cell carcinoma using radiomic feature analysis of pre-treatment FDG PET-CT

Purpose: Incidence of anal squamous cell carcinoma (ASCC) is increasing, with curative chemoradiotherapy (CRT) as the primary treatment of non-metastatic disease. A significant proportion of patients have locoregional treatment failure (LRF), but distant relapse is uncommon. Accurate prognostication of progression-free survival (PFS) would help personalisation of CRT regimens. The study aim was to evaluate novel imaging pre-treatment features, to prognosticate for PFS in ASCC. Methods: Consecutive patients with ASCC treated with curative intent at a large tertiary referral centre who underwent pre-treatment FDG-PET/CT were included. Radiomic feature extraction was performed using LIFEx software on baseline FDG-PET/CT. Outcome data (PFS) was collated from electronic patient records. Elastic net regularisation and feature selection were used for logistic regression model generation on a randomly selected training cohort and applied to a validation cohort using TRIPOD guidelines. ROC-AUC analysis was used to compare performance of a regression model encompassing standard clinical prognostic factors (age, sex, tumour and nodal stage—model A), a radiomic feature model (model B) and a combined radiomic/clinical model (model C). Results: A total of 189 patients were included in the study, with 145 in the training cohort and 44 in the validation cohort. Median follow-up was 35.1 and 37. 9 months, respectively for each cohort, with 70.3% and 68.2% reaching this time-point with PFS. GLCM entropy (a measure of randomness of distribution of co-occurring pixel grey-levels), NGLDM busyness (a measure of spatial frequency of changes in intensity between nearby voxels of different grey-level), minimum CT value (lowest HU within the lesion) and SMTV (a standardized version of MTV) were selected for inclusion in the prognostic model, alongside tumour and nodal stage. AUCs for performance of model A (clinical), B (radiomic) and C (radiomic/clinical) were 0.6355, 0.7403, 0.7412 in the training cohort and 0.6024, 0.6595, 0.7381 in the validation cohort. Conclusion: Radiomic features extracted from pre-treatment FDG-PET/CT in patients with ASCC may provide better PFS prognosis than conventional staging parameters. With external validation, this might be useful to help personalise CRT regimens in the future