Discussion
This review aimed to summarize the diagnostic accuracy and validity of TMS techniques to aid in the diagnosis of MS. Across all TMS techniques studied, there was modest sensitivity for MS at best. Of the few studies that evaluated specificity, only CMCT and MEP size (amplitude or area) were represented in enough studies to comment on overall diagnostic performance. Most studies had a high risk of bias and did not demonstrate validity for TMS biomarker use.

Recent reviews have discussed the role of TMS as a biomarker in MS ( Alsharidah et al., 2022 ; Simpson & Macdonell, 2015 ; Snow et al., 2019 ; Ziemann et al., 2011 ). While there is optimism for using TMS to diagnose, monitor natural history, or assess treatment response in MS ( Alsharidah et al., 2022 ), there is also hesitancy towards widespread clinical use of TMS due to lack of sufficient evidence and high risk of bias ( Simpson & Macdonell, 2015 ; Snow et al., 2019 ). In the current review, studies failed to justify the validity of TMS techniques as biomarkers for MS diagnosis; however, some outcomes could help characterize corticospinal conduction loss throughout the disease course.

TMS elicits corticospinal motor responses partly by stimulating axon terminals or axonal bends in superficial presynaptic layer II/III/V myelinated neurons at the gyral crown of the precentral gyrus ( Siebner et al., 2022 ). Given MS is characterized by attacks of inflammatory demyelination and axonal damage (in the context of ongoing axonal degeneration) ( Pachner, 2021 ; Reich, Lucchinetti & Calabresi, 2018 ), these processes can intuitively be characterized using TMS measures of CNS conduction ( Vucic et al., 2023 ; Ziemann et al., 2011 ). For example, CMCT, MEPs, and triple stimulation technique (TST) could theoretically serve this role ( Alsharidah et al., 2022 ; Simpson & Macdonell, 2015 ; Snow et al., 2019 ; Vucic et al., 2023 ; Ziemann et al., 2011 ). In the present review, only CMCT and MEP size had sufficient evidence to evaluate their diagnostic performance.

Only CMCT was sensitive for MS (median 75%), when combining findings from upper plus lower extremities. Both CMCT and MEP amplitude had high specificity for MS (median 100%). DOR was greatest and most consistent for CMCT of the lower extremities (median DOR 25.15). Both techniques were generally correlated with pyramidal function, cerebellar function, and EDSS; however, their associations with MRI findings (lesions, atrophy) were inconsistent. Both techniques had poor sensitivity for subclinical lesions, whereas CMCT was 96% specific for subclinical disease. CMCT was 75% sensitive for recovery from active disease but had negligible sensitivity for new disease activity. Lastly, CMCT was highly sensitive for SPMS and PPMS.

Overall, CMCT had the greatest diagnostic performance of the TMS outcomes reviewed ( Figure 3 ). Two of the eight CMCT studies had low risk of bias ( Beer, Rösler & Hess, 1995 ; Ravnborg et al., 1992 ), two had unclear risk of bias ( Cruz-Martínez et al., 2000 ; Magistris et al., 1999 ), and four had high risk of bias ( Hess et al., 1987 ; Mayr et al., 1991 ; Schmierer et al., 2000 ; Tataroglu et al., 2003 ). Risk of bias was primarily attributable to inappropriate exclusions and using case-control designs. No study could demonstrate biomarker validity, due to not providing detailed data, demonstrating poor sensitivity, or failing to justify use in epidemiologic studies. However, in the high-quality studies, estimated DOR was 6–14, suggesting abnormal CMCT was associated with a large, 6 to 14 times, increased odds of MS ( Figure 3 ) ( Chen, Cohen & Chen, 2010 ).

A major strength of the 2017 McDonald criteria ( Thompson et al., 2018 ) is its high sensitivity, owed to using MRI for evidence of lesion dissemination in space and time in persons following a clinical demyelinating episode. In one study, the sensitivity of the 2017 McDonald criteria was as high as 100% ( Gobbin et al., 2019 ). CMCT therefore has little additive value to enhance the sensitivity of MS diagnostic criteria. However, the greatest strength of CMCT would be its high specificity (median 100%), where the 2017 McDonald criteria was as low as 14% specific in one study ( Gobbin et al., 2019 ). CMCT could reduce false-positive diagnoses ( Schwenkenbecher et al., 2019 ), by “ruling-in” persons with corticospinal conduction loss who were identified as having MS as per the 2017 McDonald criteria.

The current review also found a compelling role for TMS in characterizing MS natural history. For example, CMCT was highly sensitivity for both progressive MS and higher disability status. Given most of the evidence herein is cross-sectional, the authors cannot assign any causal relationship between corticospinal conduction deficits and disease progression or disability accumulation ( Pachner, 2021 ). Nevertheless, CMCT could identify early neurodegeneration to help diagnose a transition to SPMS or revise the diagnosis of RMS to PPMS. The potential role of CMCT in identifying occult neurodegeneration would be especially important, given there are limited treatment options for progressive MS and the diagnosis of PPMS or conversion of RMS to SPMS requires evidence of chronic and irreversible disability accumulation ( Hamdy et al., 2022 ; Thompson et al., 2018 ). To better establish whether CMCT could expedite the diagnosis of progressive MS subtypes will require more evidence from prospective longitudinal studies.

Despite the novelty of this review in terms of addressing the diagnostic performance of TMS and critically appraising the TMS biomarker literature, several limitations should be noted. First, the 2017 McDonald criteria ( Thompson et al., 2018 ) currently represents the gold standard of MS diagnosis. None of the articles reviewed used these criteria, and most used the Poser criteria ( Poser et al., 1983 ). While the authors could not identify any past research that directly compared Poser and 2017 McDonald criteria, successive iterations of the McDonald criteria have generally been shown to diagnose MS earlier and more frequently than the Poser criteria ( i.e ., enhanced sensitivity) ( Brownlee et al., 2015 ), but with compromised specificity and a higher rate of misdiagnosis ( Tintoré et al., 2003 ). Sensitivity and specificity of the Poser criteria have been estimated at 87% and 94%, respectively ( Engell, 1988 ; Izquierdo et al., 1985 ), whereas sensitivity and specificity of the 2017 McDonald criteria range between 68–100% and 14–61%, respectively ( Filippi et al., 2018 , 2022 ; Gobbin et al., 2019 ; van der Vuurst de Vries et al., 2018 ). In past work, the addition of CMCT did not enhance the sensitivity of the Poser criteria to increase MS diagnoses, but increased specificity and reduced MS misdiagnoses ( Beer, Rösler & Hess, 1995 ). It presently is unclear how TMS techniques would perform in the context of the 2017 McDonald criteria, and this question should be addressed in future research.

Next, this critical review is based on only 17 studies of a select few TMS techniques. Methods like paired-pulse and dual-coil TMS, or TMS-EEG, offer unique ways to explore intracortical excitability in excitatory, inhibitory, and neuromodulatory interneurons; other regions important to sensorimotor function ( e.g ., premotor cortex, supplementary motor area, cerebellum, somatosensory cortices); and distant non-motor regions ( Rossini et al., 2015 ). Such techniques could characterize biologically plausible disease mechanisms not reviewed here, such as acute excitotoxicity or chronic neurodegeneration, linked to disease activity and progression, respectively ( Chaves et al., 2019 ; Snow et al., 2019 ).

Lastly, given this is a critical narrative review, the results must be interpreted more carefully compared to a systematic review or meta-analysis. The studies included in the review are heterogeneous in terms of study design, sample size, participant characteristics, and TMS methods. The current approach to data synthesis and interpretation does not take study heterogeneity into account. Moreover, because the authors did not produce a single estimate for the diagnostic performance of each TMS technique, there is greater onus on the reader to interpret the findings. Nonetheless, the authors provide a protocol-driven review, following evidence-based methods for data extraction and critical appraisal.