Respiratory-gated PET/CT for pulmonary lesion characterisation—promises and problems

2-deoxy-2-(¹⁸Fluorine)-fluoro-D-glucose (FDG) PET/CT is an integral part of lung carcinoma staging and frequently used in the assessment of solitary pulmonary nodules. However, a limitation of conventional three-dimensional PET/CT when imaging the thorax is its susceptibility to motion artefact, which blurs the signal from the lesion resulting in inaccurate representation of size and metabolic activity. Respiratory gated (four-dimensional) PET/CT aims to negate the effects of motion artefact and provide a more accurate interpretation of pulmonary nodules and lymphadenopathy. There have been recent advances in technology and a shift from traditional hardware to more streamlined software methods for respiratory gating which should allow more widespread use of respiratory-gating in the future. The purpose of this article is to review the evidence surrounding four-dimensional PET/CT in pulmonary lesion characterisation

Clinical impact and diagnostic accuracy of 2-[18F]-fluoro-2-deoxy-d-glucose positron-emission tomography/computed tomography (PET/CT) brain imaging in patients with cognitive impairment: a tertiary centre experience in the UK

Aim To evaluate the clinical impact of combined 2-[18F]-fluoro-2-deoxy-D-glucose (FDG) positron-emission tomography/computed tomography (PET/CT) brain imaging performed in selected patients with cognitive impairment at a tertiary referral centre in the UK, and to assess the accuracy of FDG PET/CT to correctly establish the diagnosis of Alzheimer's dementia (AD) in “real-world” clinical practice. Methods and materials Using an institutional radiology database, 136 patients were identified for inclusion in the study. FDG PET/CT was performed using a standard technique and interpreted by dual-trained radiologists and nuclear medicine physicians. Standardised questionnaires were sent to the referring clinicians to establish the final clinical diagnosis and to obtain information about the clinical impact of FDG PET/CT. Results There was a 72% questionnaire return (98/136), with mean patient follow-up of 471 (standard deviation 205) days. FDG PET/CT had an impact on patient management in 81%, adding confidence to the pre-test diagnosis in 43%, changing the pre-test diagnosis in 35%, reducing the need for further investigations in 42%, and resulting in a change in therapy in 32%. There was substantial correlation between the PET/CT diagnosis and final clinical diagnosis with a correlation (k) coefficient of 0.78 (p<0.0001). The accuracy of FDG PET/CT in diagnosis of AD was 94% (95% confidence interval [CI]: 87–99), with a sensitivity of 87% (95% CI: 75–92) and a specificity of 97% (95% CI: 87–99). Conclusion FDG PET/CT brain imaging has a significant clinical impact when performed selectively in patients with cognitive impairment and shows high accuracy in the diagnosis of AD in “real-world” clinical practice

Radiomics in the evaluation of ovarian masses — a systematic review

Objectives The study aim was to conduct a systematic review of the literature reporting the application of radiomics to imaging techniques in patients with ovarian lesions. Methods MEDLINE/PubMed, Web of Science, Scopus, EMBASE, Ovid and ClinicalTrials.gov were searched for relevant articles. Using PRISMA criteria, data were extracted from short-listed studies. Validity and bias were assessed independently by 2 researchers in consensus using the Quality in Prognosis Studies (QUIPS) tool. Radiomic Quality Score (RQS) was utilised to assess radiomic methodology. Results After duplicate removal, 63 articles were identified, of which 33 were eligible. Fifteen assessed lesion classifications, 10 treatment outcomes, 5 outcome predictions, 2 metastatic disease predictions and 1 classification/outcome prediction. The sample size ranged from 28 to 501 patients. Twelve studies investigated CT, 11 MRI, 4 ultrasound and 1 FDG PET-CT. Twenty-three studies (70%) incorporated 3D segmentation. Various modelling methods were used, most commonly LASSO (least absolute shrinkage and selection operator) (10/33). Five studies (15%) compared radiomic models to radiologist interpretation, all demonstrating superior performance. Only 6 studies (18%) included external validation. Five studies (15%) had a low overall risk of bias, 9 (27%) moderate, and 19 (58%) high risk of bias. The highest RQS achieved was 61.1%, and the lowest was − 16.7%. Conclusion Radiomics has the potential as a clinical diagnostic tool in patients with ovarian masses and may allow better lesion stratification, guiding more personalised patient care in the future. Standardisation of the feature extraction methodology, larger and more diverse patient cohorts and real-world evaluation is required before clinical translation. Clinical relevance statement Radiomics shows promising results in improving lesion stratification, treatment selection and outcome prediction. Modelling with larger cohorts and real-world evaluation is required before clinical translation. Key points • Radiomics is emerging as a tool for enhancing clinical decisions in patients with ovarian masses. • Radiomics shows promising results in improving lesion stratification, treatment selection and outcome prediction. • Modelling with larger cohorts and real-world evaluation is required before clinical translation

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

Automated extraction of body composition metrics from abdominal CT or MR imaging: A scoping review

Purpose To review methodological approaches for automated segmentation of subcutaneous adipose tissue, visceral adipose tissue, and skeletal muscle from abdominal cross-sectional imaging for body composition analysis. Method Four databases were searched for publications describing automated segmentation of subcutaneous adipose tissue, visceral adipose tissue, and/or skeletal muscle from abdominal CT or MR imaging between 2019 and 2023. Included reports were evaluated to assess how imaging modality, cohort size, vertebral level, model dimensionality, and use of a volume or single slice affected segmentation accuracy and/or clinical utility. Exclusion criteria included reports not in English language, manual or semi-automated segmentation methods, reports prior to 2019 or solely of paediatric patients, and those not describing the use of abdominal CT or MR. Results After exclusions, 172 reports were included in the review. CT imaging was utilised approximately four times as often as MRI, and segmentation accuracy did not significantly differ between the two modalities. Cohort size had no significant effect on segmentation accuracy. There was little evidence to refute the current practice of extracting body composition metrics from the third lumbar vertebral level. There was no clear benefit of using a 3D model to perform segmentation over a 2D approach. Conclusion Automated segmentation of intra-abdominal soft tissues for body composition analysis is an intense area of research activity. Segmentation accuracy is not affected by cross-sectional imaging modality. Extracting metrics from a single slice at the third lumbar vertebral level is a common approach, however, extracting metrics from a volumetric slab surrounding this level may increase the resilience of the technique, which is important for clinical translation. A paucity of publicly available datasets led to most reports using different data sources, preventing direct comparison of segmentation techniques. Future efforts should prioritise creating a standardised dataset to facilitate benchmarking of different algorithms and subsequent clinical adoption

Superiority of deformable image co-registration in the integration of diagnostic positron emission tomography-computed tomography to the radiotherapy treatment planning pathway for oesophageal carcinoma

Aims To investigate the use of image co-registration in incorporating diagnostic positron emission tomography-computed tomography (PET-CT) directly into the radiotherapy treatment planning pathway, and to describe the pattern of local recurrence relative to the PET-avid volume. Materials and methods Fourteen patients were retrospectively identified, six of whom had local recurrence. The accuracy of deformable image registration (DIR) and rigid registration of the diagnostic PET-CT and recurrence CT, to the planning CT, were quantitatively assessed by comparing co-registration of oesophagus, trachea and aorta contours. DIR was used to examine the correlation between PET-avid volumes, dosimetry and site of recurrence. Results Positional metrics including the dice similarity coefficient (DSC) and conformity index (CI), showed DIR to be superior to rigid registration in the co-registration of diagnostic and recurrence imaging to the planning CT. For diagnostic PET-CT, DIR was superior to rigid registration in the transfer of oesophagus (DSC = 0.75 versus 0.65, P < 0.009 and CI = 0.59 versus 0.48, P < 0.003), trachea (DSC = 0.88 versus 0.65, P < 0.004 and CI = 0.78 versus 0.51, P < 0.0001) and aorta structures (DSC = 0.93 versus 0.86, P < 0.006 and CI = 0.86 versus 0.76, P < 0.006). For recurrence imaging, DIR was superior to rigid registration in the transfer of trachea (DSC = 0.91 versus 0.66, P < 0.03 and CI = 0.83 versus 0.51, P < 0.02) and oesophagus structures (DSC = 0.74 versus 0.51, P < 0.004 and CI = 0.61 versus 0.37, P < 0.006) with a non-significant trend for the aorta (DSC = 0.91 versus 0.75, P < 0.08 and CI = 0.83 versus 0.63, P < 0.06) structure. A mean inclusivity index of 0.93 (range 0.79–1) showed that the relapse volume was within the planning target volume (PTVPET-CT); all relapses occurred within the high dose region. Conclusion DIR is superior to rigid registration in the co-registration of PET-CT and recurrence CT to the planning CT, and can be considered in the direct integration of PET-CT to the treatment planning process. Local recurrences occur within the PTVPET-CT, suggesting that this is a suitable target for dose-escalation strategies

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

Impact of solitary pulmonary nodule size on qualitative and quantitative assessment using 18F-fluorodeoxyglucose PET/CT: the SPUTNIK trial

Purpose: To compare qualitative and semi-quantitative PET/CT criteria, and the impact of nodule size on the diagnosis of solitary pulmonary nodules in a prospective multicentre trial. / Methods: Patients with an SPN on CT ≥ 8 and ≤ 30 mm were recruited to the SPUTNIK trial at 16 sites accredited by the UK PET Core Lab. Qualitative assessment used a five-point ordinal PET-grade compared to the mediastinal blood pool, and a combined PET/CT grade using the CT features. Semi-quantitative measures included SUVmax of the nodule, and as an uptake ratio to the mediastinal blood pool (SURBLOOD) or liver (SURLIVER). The endpoints were diagnosis of lung cancer via biopsy/histology or completion of 2-year follow-up. Impact of nodule size was analysed by comparison between nodule size tertiles. / Results: Three hundred fifty-five participants completed PET/CT and 2-year follow-up, with 59% (209/355) malignant nodules. The AUCs of the three techniques were SUVmax 0.87 (95% CI 0.83;0.91); SURBLOOD 0.87 (95% CI 0.83; 0.91, p = 0.30 versus SUVmax); and SURLIVER 0.87 (95% CI 0.83; 0.91, p = 0.09 vs. SUVmax). The AUCs for all techniques remained stable across size tertiles (p > 0.1 for difference), although the optimal diagnostic threshold varied by size. For nodules  16 mm, an SUVmax ≥ 3.6 or visual PET uptake greater than the mediastinum was the most accurate. / Conclusion: In this multicentre trial, SUVmax was the most accurate technique for the diagnosis of solitary pulmonary nodules. Diagnostic thresholds should be altered according to nodule size. / Trial registration: ISRCTN - ISRCTN30784948. ClinicalTrials.gov - NCT0201306

Rapid radiation of Southern Ocean shags in response to receding sea ice

Understanding how natural populations respond to climatic shifts is a fundamental goal of biological research in a fast-changing world. The Southern Ocean represents a fascinating system for assessing large-scale climate-driven biological change, as it contains extremely isolated island groups within a predominantly westerly, circumpolar wind and current system. Blue-eyed shags represent a paradoxical seabird radiation—a circumpolar distribution implies strong dispersal capacity yet their species-rich nature suggests local adaptation and isolation. Here we attempt to resolve this paradox in light of the history of repeated cycles of climate change in the Southern Ocean