Giovanni Foti

Background: Whipple disease (WD) is a rare, potentially fatal infection caused by Tropheryma whipplei (TW). Central Nervous System involvement (CNS‐WD) is a severe complication of WD with a challenging diagnosis, due to limited data integrating neurological features, imaging, cerebrospinal fluid analysis, PCR, and intestinal histopathology. Prompt recognition and treatment are essential to improve patient outcomes. Methods: A scoping review of the literature from 2000 to 2025 was conducted, including all CNS‐WD case reports and series, to outline its clinical spectrum and diagnostic workup. Results: Included studies were 89, accounting for 111 CNS‐WD cases. Most patients were male (79.8%), with a mean age of 53.6 years. Notably, 13.2% presented with CNS involvement in the absence of systemic WD. Pathognomonic signs were rare (13/111, 11.7%). Most patients (82.9%, 92/111) presented with two or more neurological symptoms, the most frequently reported being altered mentation, followed by ataxia, eye movement abnormalities, and other movement disorders. CSF was abnormal in 74.7% (56/75) of patients and TW PCR was positive in 75% (48/64); 64% (55/86) of cases showed intestinal histopathology consistent with WD. TW PCR on gastrointestinal biopsies was positive in 67.9% (19/28) cases. CNS imaging revealed abnormalities in 85.4% (82/96) of patients, with no distinctive pattern. Conclusions: CNS‐WD diagnosis remains challenging due to nonspecific symptoms, variable imaging, and occasional discordance among CSF, TW PCR or biopsy findings. Our review suggests that CNS‐WD should be considered in the differential diagnosis of unexplained neurological syndromes, even in patients with atypical clinical or radiological profiles, supporting broader indications for TW testing.

Healthcare accounts for 4.4–4.5% of global greenhouse gas emissions, with computed tomography (CT) representing one of the most resource-intensive and energy-demanding diagnostic modalities. Sustainability should be integrated as a core component of quality in CT practice, achieving the perfect balance between diagnostic excellence and environmental responsibility. Several key intervention areas can be identified. CT scanners consume substantial amounts of energy, with 44–72% used during nonproductive idle periods. Potential mitigation strategies include protocol optimization, automated power-down systems, and infrastructure improvements. The current “store-everything” approach to CT datasets generates a considerable carbon footprint; adopting “digital temperance” by retaining only clinically relevant images can reduce storage-related emissions. Although workstations consume less energy than scanners, their cumulative impact can be reduced through automated policies and optimized hardware lifecycle management. Iodinated contrast media persist in aquatic ecosystems and may generate toxic by-products. Sustainable strategies include personalized weight-based dosing, multi-energy CT to reduce contrast volume, and recovery or recycling programs. Single-use consumables and the environmental costs of artificial intelligence were also addressed. A 17-item action list was developed to translate the evidence-informed recommendations into practical actions for sustainable CT practice. The transition toward environmentally responsible CT practice is an ethical and professional necessity that can no longer be delayed. This position paper identifies the key challenges and proposes practical, evidence-informed strategies to transform resource-consuming CT practices into actionable and sustainable workflows, while maintaining clinical effectiveness.

Background: Differentiating adrenal adenomas from non-adenomatous lesions remains a critical challenge in the management of adrenal incidentalomas. Conventional unenhanced CT relies on attenuation thresholds of 10 HU and 20 HU, which present trade-offs between sensitivity and specificity. Objectives: To evaluate the diagnostic performance of unenhanced Spectral CT using the attenuation difference between 40 keV and 140 keV virtual monoenergetic images for differentiating adrenal adenomas from non-adenomatous lesions. Methods: In this retrospective single-center study, 60 patients with adrenal lesions who underwent unenhanced dual-energy CT were included. Mean attenuation values were measured on conventional images and on virtual monoenergetic images at 40 keV and 140 keV. The spectral attenuation difference (Δ40–140 keV) was calculated. ROC analysis was performed to determine the optimal threshold and diagnostic performance. Additional analyses included DeLong comparison of correlated ROC curves and bootstrap resampling to estimate 95% confidence intervals for the area under the curve. Results: Forty-nine lesions were adenomas and eleven were non-adenomatous. The optimal threshold for Δ40–140 keV was −17 HU. When evaluated as a continuous variable, Δ40–140 keV yielded an area under the curve of 0.940 (95% confidence interval: 0.851–1.000), compared with 0.939 (95% confidence interval: 0.870–0.992) for conventional unenhanced attenuation. DeLong comparison showed no statistically significant difference between the two curves (p = 0.980). Diagnostic performance was as follows: HU ≤ 10 (AUC 0.816, diagnostic accuracy 0.70), HU ≤ 20 (AUC 0.883, diagnostic accuracy 0.87), and Δ40–140 keV ≤ −17 HU (AUC 0.940, diagnostic accuracy 0.90). The spectral attenuation difference demonstrated the highest overall diagnostic accuracy. Conclusions: Unenhanced Spectral CT using Δ40–140 keV improves discrimination between adrenal adenomas and non-adenomatous lesions compared with conventional attenuation thresholds. This technique may reduce indeterminate findings and limit the need for additional imaging.

Background: Differentiating adrenal adenomas from non-adenomatous lesions remains a critical challenge in the management of adrenal incidentalomas. Conventional unenhanced CT relies on attenuation thresholds of 10 HU and 20 HU, which present trade-offs between sensitivity and specificity. Objectives: To evaluate the diagnostic performance of unenhanced Spectral CT using the attenuation difference between 40 keV and 140 keV virtual monoenergetic images for differentiating adrenal adenomas from non-adenomatous lesions. Methods: In this retrospective single-center study, 60 patients with adrenal lesions who underwent unenhanced dual-energy CT were included. Mean attenuation values were measured on conventional images and on virtual monoenergetic images at 40 keV and 140 keV. The spectral attenuation difference (Δ40–140 keV) was calculated. ROC analysis was performed to determine optimal thresholds and diagnostic performance. Results: Forty-nine lesions were adenomas and eleven were non-adenomatous. The optimal threshold for Δ40–140 keV was −17 HU. Diagnostic performance was as follows: HU ≤10 (AUC 0.816, diagnostic accuracy 0.70), HU ≤20 (AUC 0.883, diagnostic accuracy 0.87), and Δ40–140 keV ≤ −17 HU (AUC 0.940, diagnostic accuracy 0.90). The spectral attenuation difference demonstrated the highest overall diagnostic accuracy. Conclusions: Unenhanced Spectral CT using Δ40–140 keV improves discrimination between adrenal adenomas and non-adenomatous lesions compared with conventional attenuation thresholds. This technique may reduce indeterminate findings and limit the need for additional imaging.

Background/Objectives: Magnetic resonance arthrography is the reference standard for evaluating glenoid labral lesions. Deep learning (DL) reconstruction algorithms may accelerate 3D acquisitions while maintaining image quality. This study assesses the diagnostic accuracy of DL-based isotropic 3D MR imaging for detecting glenoid labral lesions. Methods: This prospective study included 128 consecutive patients (79 men, 49 women; mean age 38.4 years) undergoing shoulder MR arthrography between June 2023 and April 2025. DL-based 3D sequences (acquisition time: 3:26) were compared with conventional multiplanar TSE and PD-FS sequences (acquisition time: 24–28 min). Two independent radiologists assessed glenoid labral lesions, bone marrow edema, and rotator cuff abnormalities using a four-point Likert scale. Sensitivity, specificity, and interobserver agreement were calculated. Results: DL-based 3D sequences demonstrated 94.7–95.1% sensitivity and 100% specificity for glenoid labral lesions, with excellent interobserver agreement (κ = 0.812). The area under the ROC curve was 0.894. Combined 3D protocols (T1 + PD-FS) showed superior accuracy (97.8%) compared to single sequences (90.5%, p = 0.012). For bone marrow edema, sensitivity was 82.9% with 100% specificity. Rotator cuff evaluation achieved 75% sensitivity with 100% specificity. Conclusions: DL-based isotropic 3D sequences provide high diagnostic accuracy for glenoid labral pathology while reducing scan time by 75%. Combined T1 and PD-FS protocols optimize performance. These findings support selective implementation of DL-accelerated 3D protocols in shoulder MR arthrography, particularly for labral assessment, while acknowledging that conventional protocols may remain preferable in specific clinical scenarios.

Dual-energy CT (DECT) has emerged as a valuable imaging modality in musculoskeletal radiology, offering unique capabilities through virtual non-calcium reconstructions and spectral analysis. This narrative review examines the current evidence and clinical applications of DECT as an alternative to MRI in acute knee trauma evaluation. We discussed the technical principles of DECT, including virtual non-calcium imaging for bone marrow edema detection, metal artifact reduction techniques, and soft tissue assessment capabilities. The review covers six key clinical applications: complex fractures with articular involvement, subtle impacted fractures, stress fractures and healing assessment, imaging around metallic implants, osteochondritis dissecans evaluation, fracture assessment in specific knee locations. Current evidence indicates that DECT can detect bone marrow edema with sensitivity and specificity comparable to MRI, while providing distinct advantages in availability, acquisition speed, and compatibility with metallic implants. The advent of photon-counting CT technology is expected to further enhance both spatial resolution and spectral differentiation. Although MRI remains the gold standard for comprehensive assessment of knee trauma, DECT offers a practical alternative in selected clinical scenarios—particularly in emergency settings and in patients with contraindications to MRI. Future studies should aim to standardize acquisition protocols and establish evidence-based guidelines to support its optimal clinical application.

Background: Lumbar disk herniation is a common cause of low back pain and radiculopathy, significantly impacting patients’ life quality and functional capacity. Magnetic Resonance Imaging (MRI) remains the gold standard for its assessment due to its superior soft tissue contrast and multiplanar imaging capabilities. However, recent advances in spectral computed tomography (CT), particularly dual-energy CT (DECT), have introduced new diagnostic opportunities, offering improved soft tissue characterization. Objective: To evaluate the diagnostic performance of DECT in detecting and grading lumbar disk herniations using dedicated color-coded fat maps. Materials and Methods: A total of 205 intervertebral levels from 41 consecutive patients with lumbar symptoms were prospectively analyzed. All patients underwent both DECT and MRI within 3 days. Three radiologists with varying years of experience independently assessed DECT images using color-coded reconstructions. A five-point grading score was attributed to each lumbar level: 1 = normal disk, 2 = bulging/protrusion, 3 = focal herniation, 4 = extruded herniation, and 5 = migrated fragment. The statistical analysis included Pearson’s correlation for score consistency, Cohen’s Kappa for interobserver agreement, generalized estimating equations for a cluster-robust analysis, and an ROC curve analysis. The DECT diagnostic accuracy was assessed in a dichotomized model (grades 1–2 = no herniation; 3–5 = herniation), using MRI as reference. Results: A strong correlation was observed between DECT and MRI scores across all readers (mean Pearson’s r = 0.826, p < 0.001). The average exact agreement between DECT and MRI was 79.4%, with the highest concordance at L1–L2 (86.7%) and L5–S1 (80.4%). The interobserver agreement was substantial (mean Cohen’s κ = 0.765), with a near-perfect agreement between the two most experienced readers (κ = 0.822). The intraclass correlation coefficient was 0.906 (95% CI: 0.893–0.918). The ROC analysis showed excellent performance (AUC range: 0.953–0.986). In the dichotomous model, DECT demonstrated a markedly higher sensitivity than conventional CT (95.1% vs. 57.2%), with a comparable specificity (DECT: 99.0%; CT: 96.5%) and improved overall accuracy (98.4% vs. 90.0%). Subgroup analyses by age and disk location revealed no statistically significant differences. Conclusions: The use of DECT dedicated color-coded fat map reconstructions showed high diagnostic performance in the assessment of lumbar disk herniations compared to MRI. These findings support the development of dedicated post-processing tools, facilitating the broader clinical adoption of spectral CT, especially in cases where MRI is contraindicated or less accessible.

Background Deep learning (DL) reconstruction shows potential in reducing MRI acquisition times while preserving image quality, but the impact of varying acceleration factors on knee MRI diagnostic accuracy remains undefined. Purpose Evaluate diagnostic performance of twofold, fourfold, and sixfold DL-accelerated knee MRI protocols versus standard protocols. Materials/methods In this prospective study, 71 consecutive patients underwent knee MRI with standard, DL2, DL4, and DL6 accelerated protocols. Four radiologists assessed ligament tears, meniscal lesions, bone marrow edema, chondropathy, and extensor abnormalities. Sensitivity, specificity, and interobserver agreement were calculated. Results DL2 and DL4 demonstrated high diagnostic accuracy. For ACL tears, DL2/DL4 achieved 98–100% sensitivity/specificity, while DL6 showed reduced sensitivity (91–96%). In meniscal evaluation, DL2 maintained 96–100% sensitivity and 98–100% specificity; DL4 showed 94–98% sensitivity and 97–99% specificity. DL6 exhibited decreased sensitivity (82–92%) for subtle lesions. Bone marrow edema detection remained excellent across acceleration factors. Interobserver agreement was excellent for DL2/DL4 (W = 0.91–0.97) and good for DL6 (W = 0.78–0.89). Conclusion DL2 protocols demonstrate performance nearly identical to standard protocols, while DL4 maintains acceptable diagnostic accuracy for most pathologies. DL6 shows reduced sensitivity for subtle abnormalities, particularly among less experienced readers. DL2 and DL4 protocols represent optimal balance between acquisition time reduction (50–75%) and diagnostic confidence.