Smartphone-based imaging systems for medical applications: a critical review

Abstract

Significance: Smartphones come with an enormous array of functionality and are being more widely utilized with specialized attachments in a range of healthcare applications. A review of key developments and uses, with an assessment of strengths/limitations in various clinical workflows, was completed.

Aim: Our review studies how smartphone-based imaging (SBI) systems are designed and tested for specialized applications in medicine and healthcare. An evaluation of current research studies is used to provide guidelines for improving the impact of these research advances.

Approach: First, the established and emerging smartphone capabilities that can be leveraged for biomedical imaging are detailed. Then, methods and materials for fabrication of optical, mechanical, and electrical interface components are summarized. Recent systems were categorized into four groups based on their intended application and clinical workflow: ex vivo diagnostic, in vivo diagnostic, monitoring, and treatment guidance. Lastly, strengths and limitations of current SBI systems within these various applications are discussed.

Results: The native smartphone capabilities for biomedical imaging applications include cameras, touchscreens, networking, computation, 3D sensing, audio, and motion, in addition to commercial wearable peripheral devices. Through user-centered design of custom hardware and software interfaces, these capabilities have the potential to enable portable, easy-to-use, point-of-care biomedical imaging systems. However, due to barriers in programming of custom software and on-board image analysis pipelines, many research prototypes fail to achieve a prospective clinical evaluation as intended. Effective clinical use cases appear to be those in which handheld, noninvasive image guidance is needed and accommodated by the clinical workflow. Handheld systems for in vivo, multispectral, and quantitative fluorescence imaging are a promising development for diagnostic and treatment guidance applications.

Conclusions: A holistic assessment of SBI systems must include interpretation of their value for intended clinical settings and how their implementations enable better workflow. A set of six guidelines are proposed to evaluate appropriateness of smartphone utilization in terms of clinical context, completeness, compactness, connectivity, cost, and claims. Ongoing work should prioritize realistic clinical assessments with quantitative and qualitative comparison to non-smartphone systems to clearly demonstrate the value of smartphone-based systems. Improved hardware design to accommodate the rapidly changing smartphone ecosystem, creation of open-source image acquisition and analysis pipelines, and adoption of robust calibration techniques to address phone-to-phone variability are three high priority areas to move SBI research forward.

Keywords: handheld; mobile; point-of-care; smartphone; smartphone imaging; smartphone systems.

Fig. 1

SBI for various biomedical imaging applications grouped into four clinical workflows.

Fig. 2

Established and emerging smartphone capabilities for biomedical imaging applications.

Fig. 3

Smartphone-based optical interface design spectrum. The spectrum of optical interfaces for smartphone-based biomedical imaging spans from use of the native device only to fully external optical systems that interface with the phone via wired/wireless communication. Attachment designs vary along mechanical and optoelectronical axes from minimal/passive attachments to more complex and actively controlled attachments. Examples of commercial and research prototype systems are plotted within the spectrum for reference. Visuals adapted from the following sources: assay imaging box, foot imaging box, droplet lens, microscopy clip, retinal imaging module,^, dermatology clip, photosensitizer fluorescence module, endoscope, and multispectral imaging module.

Fig. 4

Smartphone-based software design spectrum. Approaches and core functionalities supported by SBI systems in unrealistic and realistic deployments with increasing degrees of customization are highlighted. Unfortunately, the vast majority of SBI systems reported in the current literature use unrealistic acquisition and analysis pipelines.

Fig. 5

Six guidelines for evaluating appropriateness of smartphone utilization in biomedical imaging applications.