Early Evaluation of an Ultra-Portable X-ray System for Tuberculosis Active Case Finding

Vo, Luan Nguyen Quang; Codlin, Andrew James; Ngo, Thuc Doan; Dao, Thang Phuoc; Dong, Thuy Thi Thu; Mo, Huong Thi Lan; Forse, Rachel Jeanette; Nguyen, Thao; Cung, Cong Van; Nguyen, Hoa B.; Nguyen, Nhung Viet; Nguyen, Van Van; Tran, Ngan; Nguyen, Giang Hoai; Qin, Zhi Zhen; Creswell, Jacob

doi:10.3390/tropicalmed6030163

Cited by 26 publications

(17 citation statements)

References 26 publications

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“…Image quality was described as comparable to stationary machines, which can potentially facilitate adoption of UP DXR for case detection. A recent publication from the site in Vietnam showed slightly inferior image quality compared to stationary X-ray, but no effect on CAD interpretation or screening yields [18]. One clinician reported their preference for UP DXR over stationary devices in terms of image quality:…”

Section: Resultsmentioning

confidence: 99%

Early user experience and lessons learned using ultra-portable digital X-ray with computer-aided detection (DXR-CAD) products: A qualitative study from the perspective of healthcare providers

Qin

Barrett²,

Castro

et al. 2022

Preprint

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Background: Recent technological and radiological advances have renewed interest in using X-rays to screen and triage people with tuberculosis (TB). The miniaturization of digital X-ray (DXR), combined with automatic interpretation using computer-aided detection (CAD) software can extend the reach of DXR screening interventions for TB. This qualitative study assessed early implementers’ experiences and lessons learned when using ultra-portable (UP) DXR systems integrated with CAD software to screen and triage TB. Methods: Semi-structured interviews were conducted with project staff and healthcare workers at six pilot sites. Transcripts were coded and analyzed using a framework approach. The themes that emerged were subsequently organized and presented using the Consolidated Framework for Implementation Research (CFIR). Results: There were 26 interviewees with varying roles: supervisory, clinicians, radiographers, and radiologists. Participants recognized the portability as the main advantage, but criticize that it involves several compromises on throughput, internet dependence, manoeuvrability and stability, as well as suitability for patients with larger body sizes. Furthermore, compared to use the hardware and software from the same supplier without digital health information system, complexity increases with interoperability between hardware and software and between different electronic health information systems. Currently, there is a limited capacity to implement these technologies, especially due to need for threshold selection, and lack of guidance on radiation protection suitable for UP DXR machines. Finally, the respondents stressed the importance of having protected means of sharing patient medical data, as well as comprehensive support and warranty plans. Conclusion: Study findings suggest that UP DXR with CAD were overall well received to decentralize radiological assessment for TB, however, the improved portability involved programmatic compromises. Main barriers to the uptake included the insufficient capacity and lack of guidance on radiation protection suitable for UP DXR.

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Section: Resultsmentioning

confidence: 99%

Early user experience and lessons learned using ultra-portable digital X-ray with computer-aided detection (DXR-CAD) products: A qualitative study from the perspective of healthcare providers

Qin

Barrett²,

Castro

et al. 2022

Preprint

Self Cite

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“…Digitalization and development of multi-layer detectors have enabled increased availability of radiography and enhanced the development of portable systems for POCT use. The newest portable systems, called ultra-portable or handheld x-ray systems, come with compacted technology that allows safe TB screening in remote locations or home-based environments [ 94 ]. At least three ultra-portable radiography systems are commercially available: MINE 2 (HDT; Gwangju, Korea), Xair (FDR XD2000; Fujifilm Corporation; Tokyo, Japan) and Delft Ultra (Delft Imaging Systems, JD’s-Hertogenbosch, The Netherlands).…”

Section: Potentially Available Point-of-care Tests In the More Distan...mentioning

confidence: 99%

“…At least three ultra-portable radiography systems are commercially available: MINE 2 (HDT; Gwangju, Korea), Xair (FDR XD2000; Fujifilm Corporation; Tokyo, Japan) and Delft Ultra (Delft Imaging Systems, JD’s-Hertogenbosch, The Netherlands). In addition, two of these include platforms include AI-supported interpretation of images [ 94 ]. However, results from a performance and implementation evaluation of such a system, in community-based active TB case finding campaigns, found shortcomings in capture capacity per charge and image quality compared to a stationary radiographic system, but abnormality scores using the AI software did not differ between images by the ultra-portable versus reference system [ 94 ].…”

Section: Potentially Available Point-of-care Tests In the More Distan...mentioning

confidence: 99%

“…In addition, two of these include platforms include AI-supported interpretation of images [ 94 ]. However, results from a performance and implementation evaluation of such a system, in community-based active TB case finding campaigns, found shortcomings in capture capacity per charge and image quality compared to a stationary radiographic system, but abnormality scores using the AI software did not differ between images by the ultra-portable versus reference system [ 94 ].…”

Section: Potentially Available Point-of-care Tests In the More Distan...mentioning

confidence: 99%

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Towards Accurate Point-of-Care Tests for Tuberculosis in Children

et al. 2022

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In childhood tuberculosis (TB), with an estimated 69% of missed cases in children under 5 years of age, the case detection gap is larger than in other age groups, mainly due to its paucibacillary nature and children’s difficulties in delivering sputum specimens. Accurate and accessible point-of-care tests (POCTs) are needed to detect TB disease in children and, in turn, reduce TB-related morbidity and mortality in this vulnerable population. In recent years, several POCTs for TB have been developed. These include new tools to improve the detection of TB in respiratory and gastric samples, such as molecular detection of Mycobacterium tuberculosis using loop-mediated isothermal amplification (LAMP) and portable polymerase chain reaction (PCR)-based GeneXpert. In addition, the urine-based detection of lipoarabinomannan (LAM), as well as imaging modalities through point-of-care ultrasonography (POCUS), are currently the POCTs in use. Further to this, artificial intelligence-based interpretation of ultrasound imaging and radiography is now integrated into computer-aided detection products. In the future, portable radiography may become more widely available, and robotics-supported ultrasound imaging is currently being trialed. Finally, novel blood-based tests evaluating the immune response using “omic-“techniques are underway. This approach, including transcriptomics, metabolomic, proteomics, lipidomics and genomics, is still distant from being translated into POCT formats, but the digital development may rapidly enhance innovation in this field. Despite these significant advances, TB-POCT development and implementation remains challenged by the lack of standard ways to access non-sputum-based samples, the need to differentiate TB infection from disease and to gain acceptance for novel testing strategies specific to the conditions and settings of use.

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“…Now, AI techniques have been applied to various medical domains; for example, pulmonary diseases [46,47], cardiology [48,49], and brain surgery [50,51]. In Table 1 [52][53][54][55][56][57][58][59][60], we summarize various models built using AI. For instance, the CAD4COVID-CT tool is used to quantify the pulmonary parenchyma in CT scans (Manufacturers-Thirona, Nijmegen, the Netherlands).…”

Section: Introductionmentioning

confidence: 99%