Background: Artificial intelligence (AI) is gaining increasing importance in many medical specialties, yet data on patients’ opinions on the use of AI in medicine are scarce. Objective: This study aimed to investigate patients’ opinions on the use of AI in different aspects of the medical workflow and the level of control and supervision under which they would deem the application of AI in medicine acceptable. Methods: Patients scheduled for computed tomography or magnetic resonance imaging voluntarily participated in an anonymized questionnaire between February 10, 2020, and May 24, 2020. Patient information, confidence in physicians vs AI in different clinical tasks, opinions on the control of AI, preference in cases of disagreement between AI and physicians, and acceptance of the use of AI for diagnosing and treating diseases of different severity were recorded. Results: In total, 229 patients participated. Patients favored physicians over AI for all clinical tasks except for treatment planning based on current scientific evidence. In case of disagreement between physicians and AI regarding diagnosis and treatment planning, most patients preferred the physician’s opinion to AI (96.2% [153/159] vs 3.8% [6/159] and 94.8% [146/154] vs 5.2% [8/154], respectively; P=.001). AI supervised by a physician was considered more acceptable than AI without physician supervision at diagnosis (confidence rating 3.90 [SD 1.20] vs 1.64 [SD 1.03], respectively; P=.001) and therapy (3.77 [SD 1.18] vs 1.57 [SD 0.96], respectively; P=.001). Conclusions: Patients favored physicians over AI in most clinical tasks and strongly preferred an application of AI with physician supervision. However, patients acknowledged that AI could help physicians integrate the most recent scientific evidence into medical care. Application of AI in medicine should be disclosed and controlled to protect patient interests and meet ethical standards.

Dual-energy information in computed tomography can be obtained through different technical approaches. Most available scanner designs acquire examination with two different X-ray spectra. Recently, the first detector-based approach became clinically available. Upfront, physical principles of dual-energy CT are reviewed, including the interaction of photons with matter in terms of the Photoelectric effect and Compton scattering. In addition, available concepts to dual energy computed tomography are described. Afterwards, the spectral detector CT system is described in detail. The design of the of the stacked detector design and its inherent technical advantages and disadvantages are discussed. Further, the principles of image reconstruction, their possibilities and limitations are referred. The increase in reconstructions and data pose some challenges to both, clinical and technological workflow which are hereafter addressed. Finally, the detector-based approach is discussed in light of other, emission-based DECT approaches.

Iodine maps acquired with spectral CT improve subjective assessment of pleural carcinomatosis and facilitate quantitative differentiation from benign pleural lesions. Purpose To evaluate the use of spectral CT for differentiation between noncalcified benign pleural lesions and pleural carcinomatosis. Materials and Methods In this retrospective study, patients who underwent contrast agent–enhanced late venous phase spectral CT of the chest between June 1, 2016, and July 1, 2018 with histopathologic and/or imaging confirmation of noncalcified pleural lesions were evaluated. Conventional images, iodine overlay (IO) images, and virtual monoenergetic images at 40 keV (hereafter, VMI40keV) were reconstructed from contrast-enhanced spectral chest CT. Four blinded radiologists determined lesion presence and indicated lesion conspicuity and diagnostic certainty. Hounsfield unit attenuation from conventional images and iodine concentration (IC) (in milligrams per milliliter) from IO images were determined. Area under the receiver operating characteristics curve determined thresholds for quantitative lesion differentiation and cutoff values were validated in an independent data s...