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OBJECTIVES: To investigate the potential of T1rho, a new quantitative imaging sequence for cancer, for pre and early intra-treatment prediction of treatment response in nasopharyngeal carcinoma (NPC) and compare the results with those of diffusion-weighted imaging (DWI). MATERIALS AND METHODS: T1rho and DWI imaging of primary NPCs were performed pre- and early intra-treatment in 41 prospectively recruited patients. The mean preT1rho, preADC, intraT1rho, intraADC, and % changes in T1rho (ΔT1rho%) and ADC (ΔADC%) were compared between residual and non-residual groups based on biopsy in all patients after chemoradiotherapy (CRT) with (n = 29) or without (n = 12) induction chemotherapy (IC), and between responders and non-responders to IC in the subgroup who received IC, using Mann-Whitney U-test. A p-value of < 0.05 indicated statistical significance. RESULTS: Significant early intra-treatment changes in mean T1rho (p = 0.049) and mean ADC (p < 0.01) were detected (using paired t-test), most showing a decrease in T1rho (63.4%) and an increase in ADC (95.1%). Responders to IC (n = 17), compared to non-responders (n = 12), showed higher preT1rho (64.0 ms vs 66.5 ms) and a greater decrease in ΔT1rho% (- 7.5% vs 1.3%) (p < 0.05). The non-residual group after CRT (n = 35), compared to the residual group (n = 6), showed higher intraADC (0.96 vs 1.09 × 10-3 mm2/s) and greater increase in ΔADC% (11.7% vs 27.0%) (p = 0.02). CONCLUSION: Early intra-treatment changes are detectable on T1rho and show potential to predict tumour shrinkage after IC. T1rho may be complementary to DWI, which, unlike T1rho, did not predict response to IC but did predict non-residual disease after CRT. CLINICAL RELEVANCE STATEMENT: T1rho has the potential to complement DWI in the prediction of treatment response. Unlike DWI, it predicted shrinkage of the primary NPC after IC but not residual disease after CRT. KEY POINTS: Changes in T1rho were detected early during cancer treatment for NPC. Pre-treatment and early intra-treatment change in T1rho predicted response to IC, but not residual disease after CRT. T1rho can be used to complement DWI with DWI predicting residual disease after CRT.
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Radiomics analysis can potentially characterize salivary gland tumors (SGTs) on magnetic resonance imaging (MRI). The procedures for radiomics analysis were various, and no consistent performances were reported. This review evaluated the methodologies and performances of studies using radiomics analysis to characterize SGTs on MRI. We systematically reviewed studies published until July 2023, which employed radiomics analysis to characterize SGTs on MRI. In total, 14 of 98 studies were eligible. Each study examined 23-334 benign and 8-56 malignant SGTs. Least absolute shrinkage and selection operator (LASSO) was the most common feature selection method (in eight studies). Eleven studies confirmed the stability of selected features using cross-validation or bootstrap. Nine classifiers were used to build models that achieved area under the curves (AUCs) of 0.74 to 1.00 for characterizing benign and malignant SGTs and 0.80 to 0.96 for characterizing pleomorphic adenomas and Warthin's tumors. Performances were validated using cross-validation, internal, and external datasets in four, six, and two studies, respectively. No single feature consistently appeared in the final models across the studies. No standardized procedure was used for radiomics analysis in characterizing SGTs on MRIs, and various models were proposed. The need for a standard procedure for radiomics analysis is emphasized.
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OBJECTIVES AND METHODS: With 432 513 samples from UK Biobank dataset, multivariable linear/logistic regression were used to estimate the relationship between psoriasis/psoriatic arthritis (PsA) and estimated bone mineral density (eBMD)/osteoporosis, controlling for potential confounders. Here, confounders were set in three ways: model0 (including age, height, weight, smoking and drinking), model1 (model0 +regular physical activity) and model2 (model1 +medication treatments). The eBMD was derived from heel ultrasound measurement. And 4904 patients with psoriasis and 847 patients with PsA were included in final analysis. Mendelian randomisation (MR) approach was used to evaluate the causal effect between them. RESULTS: Lower eBMD were observed in patients with PsA than in controls in both model0 (ß-coefficient=-0.014, p=0.0006) and model1 (ß-coefficient=-0.013, p=0.002); however, the association disappeared when conditioning on treatment with methotrexate or ciclosporin (model2) (ß-coefficient=-0.005, p=0.28), mediation analysis showed that 63% of the intermediary effect on eBMD was mediated by medication treatment (p<2E-16). Patients with psoriasis without arthritis showed no difference of eBMD compared with controls. Similarly, the significance of higher risk of osteopenia in patients with PsA (OR=1.27, p=0.002 in model0) could be eliminated by conditioning on medication treatment (p=0.244 in model2). Psoriasis without arthritis was not related to osteopenia and osteoporosis. The weighted Genetic Risk Score analysis found that genetically determined psoriasis/PsA were not associated with eBMD (p=0.24 and p=0.88). Finally, MR analysis showed that psoriasis/PsA had no causal effect on eBMD, osteoporosis and fracture. CONCLUSIONS: The effect of PsA on osteoporosis was secondary (eg, medication) but not causal. Under this hypothesis, psoriasis without arthritis was not a risk factor for osteoporosis.