68Ga-nitroimidazole PET/CT imaging of hypoxia in tuberculosis : a case series

This manuscript forms part of a Chapter in a thesis prepared by the corresponding author as part of the requirements to fulfil the degree PhD in Medical Nuclear Science at the University of Pretoria, South Africa.Tuberculosis (TB) lesions in humans have been proven to be severely hypoxic with hypoxia leading to latency and dormancy of disease. Dormant TB lesions become less susceptible to standard TB treatment regimens with varying responses to treatment but may have increased susceptibility to nitroimidazole drugs. This in turn implies that positron emission tomography / computed tomography (PET/CT) imaging with radiolabelled nitroimidazoles may identify patients who will benefit from treatment with antimicrobial agents that are active against anaerobic bacteria. This case series aims to highlight the hypoxic uptake and retention of a novel 68Ga-labelled hypoxia-seeking agent in TB lesions at different time points during anti-TB therapy using PET/CT imaging. Patients with confirmed TB underwent whole-body PET/CT after administration of a 68Ga-nitroimidazole derivative at baseline and follow-up. Images were analysed both qualitatively and semi-quantitatively. Hypoxic uptake and change in uptake over time were analysed using lesion-to-muscle ratio (LMR) and lesion-to-blood ratio (LBR). 68Ga-nitroimidazole avid lesions were demonstrated most frequently in the upper lobes of the lung. Low-grade hypoxic uptake was visualised in areas of consolidation, cavitation, nodules and lymph nodes. From baseline to follow-up imaging, the LMR increased with persistent hypoxic load despite morphologic improvement. This case series highlights the dynamic hypoxic microenvironment in TB lesions. From these initial data, it appears that 68Ga-nitroimidazole is a promising candidate for monitoring hypoxic load in patients diagnosed with TB. Such imaging could identify patients who would benefit from individualised therapy targeting other mechanisms in the TB microenvironment with the intention to predict or improve treatment response.https://onlinelibrary.wiley.com/journal/20513909hj2023Nuclear Medicin

A new scale to measure family members' perception of community health care services for persons with Huntington disease

Huntington Disease (HD) is a progressive genetic brain disease leading to disruptive cognitive, behavioral, and physical impairments. Persons with the condition and their caregivers need appropriate and accessible health care services to help them manage the disease adequately. The purpose of this study was to evaluate the psychometric properties of a new scale that measures family members' perception of community health care services (CHCS) for persons with HD

Detection of endometrial cancer in cervico-vaginal fluid and blood plasma:leveraging proteomics and machine learning for biomarker discovery

BACKGROUND: The anatomical continuity between the uterine cavity and the lower genital tract allows for the exploitation of uterine-derived biomaterial in cervico-vaginal fluid for endometrial cancer detection based on non-invasive sampling methodologies. Plasma is an attractive biofluid for cancer detection due to its simplicity and ease of collection. In this biomarker discovery study, we aimed to identify proteomic signatures that accurately discriminate endometrial cancer from controls in cervico-vaginal fluid and blood plasma.METHODS: Blood plasma and Delphi Screener-collected cervico-vaginal fluid samples were acquired from symptomatic post-menopausal women with (n = 53) and without (n = 65) endometrial cancer. Digitised proteomic maps were derived for each sample using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning was employed to identify the most discriminatory proteins. The best diagnostic model was determined based on accuracy and model parsimony.FINDINGS: A protein signature derived from cervico-vaginal fluid more accurately discriminated cancer from control samples than one derived from plasma. A 5-biomarker panel of cervico-vaginal fluid derived proteins (HPT, LG3BP, FGA, LY6D and IGHM) predicted endometrial cancer with an AUC of 0.95 (0.91-0.98), sensitivity of 91% (83%-98%), and specificity of 86% (78%-95%). By contrast, a 3-marker panel of plasma proteins (APOD, PSMA7 and HPT) predicted endometrial cancer with an AUC of 0.87 (0.81-0.93), sensitivity of 75% (64%-86%), and specificity of 84% (75%-93%). The parsimonious model AUC values for detection of stage I endometrial cancer in cervico-vaginal fluid and blood plasma were 0.92 (0.87-0.97) and 0.88 (0.82-0.95) respectively.INTERPRETATION: Here, we leveraged the natural shed of endometrial tumours to potentially develop an innovative approach to endometrial cancer detection. We show proof of principle that endometrial cancers secrete unique protein signatures that can enable cancer detection via cervico-vaginal fluid assays. Confirmation in a larger independent cohort is warranted.FUNDING: Cancer Research UK, Blood Cancer UK, National Institute for Health Research.</p

Detection of endometrial cancer in cervico-vaginal fluid and blood plasma:leveraging proteomics and machine learning for biomarker discovery

BACKGROUND: The anatomical continuity between the uterine cavity and the lower genital tract allows for the exploitation of uterine-derived biomaterial in cervico-vaginal fluid for endometrial cancer detection based on non-invasive sampling methodologies. Plasma is an attractive biofluid for cancer detection due to its simplicity and ease of collection. In this biomarker discovery study, we aimed to identify proteomic signatures that accurately discriminate endometrial cancer from controls in cervico-vaginal fluid and blood plasma.METHODS: Blood plasma and Delphi Screener-collected cervico-vaginal fluid samples were acquired from symptomatic post-menopausal women with (n = 53) and without (n = 65) endometrial cancer. Digitised proteomic maps were derived for each sample using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning was employed to identify the most discriminatory proteins. The best diagnostic model was determined based on accuracy and model parsimony.FINDINGS: A protein signature derived from cervico-vaginal fluid more accurately discriminated cancer from control samples than one derived from plasma. A 5-biomarker panel of cervico-vaginal fluid derived proteins (HPT, LG3BP, FGA, LY6D and IGHM) predicted endometrial cancer with an AUC of 0.95 (0.91-0.98), sensitivity of 91% (83%-98%), and specificity of 86% (78%-95%). By contrast, a 3-marker panel of plasma proteins (APOD, PSMA7 and HPT) predicted endometrial cancer with an AUC of 0.87 (0.81-0.93), sensitivity of 75% (64%-86%), and specificity of 84% (75%-93%). The parsimonious model AUC values for detection of stage I endometrial cancer in cervico-vaginal fluid and blood plasma were 0.92 (0.87-0.97) and 0.88 (0.82-0.95) respectively.INTERPRETATION: Here, we leveraged the natural shed of endometrial tumours to potentially develop an innovative approach to endometrial cancer detection. We show proof of principle that endometrial cancers secrete unique protein signatures that can enable cancer detection via cervico-vaginal fluid assays. Confirmation in a larger independent cohort is warranted.FUNDING: Cancer Research UK, Blood Cancer UK, National Institute for Health Research.</p

MsFLASH Participants’ Priorities for Alleviating Menopausal Symptoms

Objective To describe self-reported menopausal symptom priorities and their association with demographics and other symptoms among participants in an intervention trial for vasomotor symptoms (VMS). Methods Cross-sectional study embedded in the MsFLASH 02 trial, a three-by-two factorial design of yoga vs. exercise vs. usual activity and omega-3-fatty acid vs. placebo. At baseline, women (n = 354) completed hot flush diaries, a card sort task to prioritize symptoms they would most like to alleviate, and standardized questionnaires. Results The most common symptom priorities were: VMS (n = 322), sleep (n = 191), concentration (n = 140), and fatigue (n = 116). In multivariate models, women who chose VMS as their top priority symptom (n = 210) reported significantly greater VMS severity (p = 0.004) and never smoking (p = 0.012), and women who chose sleep as their top priority symptom (n = 100) were more educated (p ≤ 0.001) and had worse sleep quality (p < 0.001). ROC curves identified sleep scale scores that were highly predictive of ranking sleep as a top priority symptom. Conclusions Among women entering an intervention trial for VMS and with relatively low prevalence of depression and anxiety, VMS was the priority symptom for treatment. A card sort may be a valid tool for quickly assessing symptom priorities in clinical practice and research

Quantitative SWATH-based proteomic profiling of urine for the identification of endometrial cancer biomarkers in symptomatic women

BackgroundA non-invasive endometrial cancer detection tool that can accurately triage symptomatic women for definitive testing would improve patient care. Urine is an attractive biofluid for cancer detection due to its simplicity and ease of collection. The aim of this study was to identify urine-based proteomic signatures that can discriminate endometrial cancer patients from symptomatic controls.MethodsThis was a prospective case–control study of symptomatic post-menopausal women (50 cancers, 54 controls). Voided self-collected urine samples were processed for mass spectrometry and run using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning techniques were used to identify important discriminatory proteins, which were subsequently combined in multi-marker panels using logistic regression.ResultsThe top discriminatory proteins individually showed moderate accuracy (AUC &gt; 0.70) for endometrial cancer detection. However, algorithms combining the most discriminatory proteins performed well with AUCs &gt; 0.90. The best performing diagnostic model was a 10-marker panel combining SPRR1B, CRNN, CALML3, TXN, FABP5, C1RL, MMP9, ECM1, S100A7 and CFI and predicted endometrial cancer with an AUC of 0.92 (0.96–0.97). Urine-based protein signatures showed good accuracy for the detection of early-stage cancers (AUC 0.92 (0.86–0.9)).ConclusionA patient-friendly, urine-based test could offer a non-invasive endometrial cancer detection tool in symptomatic women. Validation in a larger independent cohort is warranted

The utility of metabolic parameters on baseline F-18 FDG PET/CT in predicting treatment response and survival in paediatric and adolescent Hodgkin lymphoma

Lymphoma is the third most common paediatric cancer. Early detection of high-risk patients is necessary to anticipate those who require intensive therapy and follow-up. Current literature shows that residual tumor avidity on PET (Positron Emission Tomography) following chemotherapy corresponds with decreased survival. However, the value of metabolic parameters has not been adequately investigated. In this retrospective study, we aimed to evaluate the prognostic value of metabolic and other parameters in paediatric and adolescent Hodgkin lymphoma. We recorded tMTV (total Metabolic Tumor Volume), TLG (Total Lesion Glycolysis), and SUVmax (maximum Standard Uptake Value) on baseline PET, as well the presence of bone marrow or visceral involvement. HIV (human immunodeficiency virus) status and baseline biochemistry from clinical records were noted. All patients received stage-specific standard of care therapy. Response assessment on end-of-treatment PET was evaluated according to the Deauville criteria. We found that bone marrow involvement (p = 0.028), effusion (p < 0.001), and treatment response (p < 0.001) on baseline PET, as well as HIV status (p = 0.036) and baseline haemoglobin (p = 0.039), were significantly related to progression-free survival (PFS), whereas only effusion (p = 0.017) and treatment response (p = 0.050) were predictive of overall survival (OS). Only baseline tMTV predicted treatment response (p = 0.017). This confirms the value of F-18 FDG PET/CT (Fluoro-deoxy-glucose Positron Emission Tomography/ Computed Tomography) in prognostication in paediatric and adolescent Hodgkin lymphoma; however, further studies are required to define the significance of metabolic parameters.https://www.mdpi.com/journal/jcmam2022Medical OncologyNuclear MedicineStatistic

Female Sexual Function Index Short Version: A MsFLASH Item Response Analysis

The Female Sexual Function Index (FSFI) is a psychometrically sound and popular 19-item self-report measure, but its length may preclude its use in studies with multiple outcome measures, especially when sexual function is not a primary endpoint. Only one attempt has been made to create a shorter scale, resulting in the Italian FSFI-6, later translated into Spanish and Korean without further psychometric analysis. Our study evaluated whether a subset of items on the 19-item English-language FSFI would perform as well as the full-length FSFI in peri- and post-menopausal women. We used baseline data from 898 peri- and post-menopausal women recruited from multiple communities, ages 42–62 years, and enrolled in randomized controlled trials for vasomotor symptom management. Goals were to (1) create a psychometrically sound, shorter version of the FSFI for use in peri- and post-menopausal women as a continuous measure and (2) compare it to the Italian FSFI-6. Results indicated that a 9-item scale provided more information than the FSFI-6 across a spectrum of sexual functioning, was able to capture sample variability, and showed sufficient range without floor or ceiling effects. All but one of the items from the Italian 6-item version were included in the 9-item version. Most omitted FSFI items focused on frequency of events or experiences. When assessment of sexual function is a secondary endpoint and subject burden related to questionnaire length is a priority, the 9-item FSFI may provide important information about sexual function in English-speaking peri- and post-menopausal women

Efficacy of yoga for vasomotor symptoms: a randomized controlled trial

OBJECTIVE: This study aims to determine the efficacy of yoga in alleviating vasomotor symptoms (VMS) frequency and bother. METHODS: This study was a three-by-two factorial, randomized controlled trial. Eligible women were randomized to yoga (n = 107), exercise (n = 106), or usual activity (n = 142), and were simultaneously randomized to a double-blind comparison of ω-3 fatty acid (n = 177) or placebo (n = 178) capsules. Yoga intervention consisted of 12 weekly 90-minute yoga classes with daily home practice. Primary outcomes were VMS frequency and bother assessed by daily diaries at baseline, 6 weeks, and 12 weeks. Secondary outcomes included insomnia symptoms (Insomnia Severity Index) at baseline and 12 weeks. RESULTS: Among 249 randomized women, 237 (95%) completed 12-week assessments. The mean baseline VMS frequency was 7.4 per day (95% CI, 6.6 to 8.1) in the yoga group and 8.0 per day (95% CI, 7.3 to 8.7) in the usual activity group. Intent-to-treat analyses included all participants with response data (n = 237). There was no difference between intervention groups in the change in VMS frequency from baseline to 6 and 12 weeks (mean difference [yoga--usual activity] from baseline at 6 wk, -0.3 [95% CI, -1.1 to 0.5]; mean difference [yoga--usual activity] from baseline at 12 wk, -0.3 [95% CI, -1.2 to 0.6]; P = 0.119 across both time points). Results were similar for VMS bother. At week 12, yoga was associated with an improvement in insomnia symptoms (mean difference [yoga - usual activity] in the change in Insomnia Severity Index, 1.3 [95% CI, -2.5 to -0.1]; P = 0.007). CONCLUSIONS: Among healthy women, 12 weeks of yoga class plus home practice, compared with usual activity, do not improve VMS frequency or bother but reduce insomnia symptoms