The T1-dark-rim: A novel imaging sign for detecting smoldering inflammation in multiple sclerosis

doi:10.21203/rs.3.rs-3582841/v1

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Research Article

The T1-dark-rim: A novel imaging sign for detecting smoldering inflammation in multiple sclerosis

https://doi.org/10.21203/rs.3.rs-3582841/v1

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published 04 Feb, 2024

Read the published version in European Journal of Radiology →

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Objectives:

Paramagnetic rim lesions (PRLs), usually identified in susceptibility-weighted imaging (SWI), are a promising prognostic biomarker of disability progression in multiple sclerosis (MS). However, SWI is not always available in clinical practice. The objective of this study is to define a novel imaging sign, the T1-dark rim, identifiable in a standard 3DT1 gradient-echo sequence, such as 3D T1 turbo field echo (3DT1FE) and explore its performance as a SWI surrogate to define PRLs.

Materials & Methods:

This observational cross-sectional study analyzed MS patients who underwent 3T magnetic resonance imaging (MRI) including 3DT1TFE and SWI. Rim lesions were evaluated in 3DT1TFE, processed SWI, and SWI phase and categorized as true positive, false positive, or false negative based on the value of the T1-dark rim in predicting SWI phase PRLs. Sensitivity and positive predictive values of the T1-dark rim for detecting PRLs were calculated.

Results:

Overall, 80 rim lesions were identified in 63 patients (60 in the SWI phase and 78 in 3DT1TFE; 58 true positives, 20 false positives, and two false negatives). The T1-dark rim demonstrated 97% sensitivity and 74% PPV for detecting PRLs. More PRLs were detected in the SWI phase than in processed SWI (60 and 57, respectively).

Conclusion:

The T1-dark rim sign is a promising and accessible novel imaging marker to detect PRLs whose high sensitivity may enable earlier detection of smoldering inflammation to guide MS treatment escalation. The relevance of T1-dark rim lesions that are negative on SWI opens up a new field for analysis.

Nuclear Medicine & Medical Imaging

Neurology

Immunology

Multiple sclerosis

Susceptibility-weighted imaging

T1-weighted imaging

Magnetic resonance imaging

Rim lesion

The T1-dark rim is a promising imaging marker for the early detection of smoldering inflammation in multiple sclerosis. It is clinically transferable and may have a high impact on patient management.

PRLs defined in SWI correlate with progressive forms of MS.
Deeply T1-hypointense lesions are characteristic of PRLs in MS.
The T1-dark rim sign is visible in a widely used 3DT1 gradient-echo imaging, is highly sensitive to PRLs and may be a new and easily accessible marker of smoldering inflammation.

Background

Multiple sclerosis (MS) is a neurodegenerative disease characterized by inflammation, demyelination, and central nervous system atrophy. MS is a primary source of disability in young adults, and its clinical trajectory varies significantly, from benign variants with negligible lasting effects to severely progressive variants that rapidly lead to disability [1].

Numerous potent disease-modifying medications have been formulated for the management of relapsing-remitting MS (RRMS) [2]. Recently, there is mounting evidence that prompt administration of high-efficiency disease modifying treatments may delay permanent disability progression in patients with high inflammatory activity [3, 4]. Furthermore, newly sanctioned therapies have demonstrated efficacy in decelerating the progression of disability in patients with non-active progressive MS (SPMS) [2, 5]. Given the effectiveness of these treatments in managing SPMS, it is becoming increasingly important to promptly predict disability progression and conversion to progressive disease forms [6].

A subset of lesions, termed “chronic active” or “smoldering” lesions, fail to undergo efficient repair and continue to spread into the surrounding normal-appearing white matter [7]. High-field MRI has been used to detect paramagnetic rims around smoldering lesions on processed susceptibility weighted imaging (SWI) and phase imaging [8–11]. These paramagnetic rim lesions (PRLs), also termed “iron rim” or “phase rim” lesions, are thus considered an MRI representation of smoldering inflammation. PRLs have been associated with higher levels of disability and more destructive pathological features [10, 12–14]. In this research, we use SWI with phase enhancement (SWIp), which is the Philips implementation of SWI.

While PRLs offer promising insights into MS characteristics, their detection in standard MRI follow-ups for MS is not straightforward [15]. Furthermore, PRL visualization requires SWI in imaging protocols, but this technique is not a standard recommendation in routine MRI follow-ups for MS patients [16, 17].

On the other hand, PRLs exhibit characteristic hypointensity on T1-weighted imaging (T1WI) [10, 13, 18–20]. Indeed, in a recent study using intensity-normalized 3DT1TFE, it was found that PRLs have distinguishing and semi-quantifiable deep hypointensity that is practically non-existent in other white matter lesions [21]. Moreover, building on this insight and our clinical experience, we observed that these deeply hypointense voxels were aligned in a peripheral pattern, manifesting as a “T1-dark rim” sign on 3DT1TFE imaging. Based on this observation, we hypothesized that this novel imaging sign could simplify the detection of PRLs without the need for SWI.

Objectives

The primary goal is to present a novel imaging sign observed in 3D gradient echo T1WI, the “T1-dark rim.” We aim to evaluate the sensitivity and positive predictive value of this imaging sign in detecting PRLs.

Study approval

This study was approved by our center’s Research Ethics Committee. All patients provided informed consent for the use of their medical data. Only de-identified data were used for analysis.

Study design, Participants, and Clinical Data Collection

We designed a retrospective cross-sectional study including patients diagnosed with remitting-relapsing multiple sclerosis (RRMS) or primary progressive multiple sclerosis (PPMS) according to McDonald criteria of 2017 [22] who were systematically followed up in the multiple sclerosis unit of a Hospital Universitari de Bellvitge. This cohort was followed from the time of diagnosis, with visits every 6 months and an annual brain MRI. In addition, supplementary visits and MRIs were conducted as needed in case of relapses.

The inclusion criteria for the study were defined as follows: 1) diagnosis of RRMS or PPMS and systematic follow-up in our MS unit; 2) available MRI scan that includes at least 3DT1TFE and SWIp sequences, both available without intravenous contrast administration, conducted between December 5, 2022 and December 22, 2022. The only exclusion criterion was distortion or limited quality in either of the two imaging sequences.

The European Database for Multiple Sclerosis software was used for a protocolized and validated collection of clinical data [23]. Among the variables collected, the ones used in this study include sex, date of birth, date of MS symptoms, EDSS at the time of MRI, disease subtype at the time of the MRI, disease modifying treatment (DMT) on course at the time of MRI and its initiation date. The following variables were calculated: age at the time of the MRI, age at disease onset, years since disease onset and duration of DMT up to the time of the MRI. The diagnosis criteria for SPMS used during follow-up are those previously defined and widely used [24]. DMT were categorized as: “no DMT”; “moderate efficacy DMT” (interferon beta 1a, interferon beta 1b, peginterferon beta 1a, glatiramer acetate, teriflunomide, dimethyl fumarate) and “high efficacy DMT” (fingolimod, natalizumab, alemtuzumab, ocrelizumab, cladribine, rituximab, mitoxantrone).

The STROBE guidelines for observational studies were used to conduct this study.

Imaging

The brain MRIs of the patients who met the inclusion criteria, conducted within the specified date range, were included and analyzed. MRI examinations were performed using the same Achieva 3T scanner (Philips) with a 32-channel head coil. The sequence parameters were identical for all the patients. The specifics of the sequence acquisition parameters are detailed below.

The 3DT1TFE sequence had the following parameters: echo time (TE) was set at 4.9ms and the repetition time (TR) at 10ms, with a flip angle of 8°; the slice thickness was 1mm, with in-plane resolution dimensions set at 0.46x0.46mm². The SWIp sequence parameters were as follows: the double TE was set at 7.2ms and 13.4ms, the TR was 31ms, and the flip angle was 17°; the slice thickness was 1.2mm, with an in-plane resolution of 0.3x0.3mm².

Image interpretation

The MRI images were jointly reviewed by two neuroradiologists with 5 years and 9 years of sub-specialty experience in MS neuroimaging, respectively […BLINDED…], and discrepancies were resolved by consensus. The data visualization and labeling process was conducted using the RadiAnt DICOM Viewer software (https://www.radiantviewer.com). The images analyzed encompassed three imaging modalities: 3DT1TFE, processed SWIp (from now on only “SWIp”), and SWIp phase. All images for each patient were initially reviewed sequentially in a single session. The review sequence order was randomly assigned in each case. Finally, after the sequential review, any rim lesions identified in any of the three modalities were analyzed and compared simultaneously in the three modalities to retrospectively include lesions that were patent but might have been missed due to human error. This process was carried out to as closely as possible reach the “ground truth” of rim presence.

Lesion classification

SWIp phase imaging was used as the reference standard for “true” PRLs in this study, as prior work has shown that this is more sensitive in terms of visualizing paramagnetic rims than SWIp images [8, 25].

Lesions with both a T1-dark rim and a phase rim were considered true positives for a PRL. Lesions with no T1-dark rim but with a phase rim were considered false negatives. Lesions with a T1-dark rim but with no phase rim were categorized as false positives. These false positive lesions were further subclassified based on their appearance on the SWIp images. Specifically, lesions with a T1-dark rim and a hypointense rim on SWIp images were designated “T1-shine-through rims,” as we hypothesized that the presence of a rim in these lesions may be justified by a certain T1-shine-through effect [26]. Lesions with a T1-dark rim but with no rim visible on either the SWIp or phase images were designated “isolated T1-dark rims.”

Data analysis

The collected data underwent descriptive and inferential statistical analyses using R software version v4.3.1.

Data are described as mean ± standard deviation (SD) or as median and interquartile range (IQR) according to their distribution. Categorical variables are described using frequencies.

For each imaging volume, the rim lesion frequencies were calculated. For the detection of SWIp phase PRL presence using T1-rim as predictor; sensitivity and positive predictive value (PPV), with exact binomial confidence intervals for each were computed using the “binom” package in R. Furthermore, sensitivity and PPV pairs for rims for each combination of modalities were calculated and presented on a matrix. As the study focused on rim-positive lesions only, the specificity and negative predictive value (NPV) were not considered, as the calculation of these metrics requires the inclusion of true negative cases (i.e., rim-negative lesions), which were not comprehensively included.

Participant characteristics

Overall, 63 patients met the inclusion criteria. The patient selection process is shown in Figure 1. Detailed demographic and clinical characteristics of the participants, including the gender distribution, age, disease status, disease duration, and disability levels as measured by the EDSS score, are summarized in Table 1.

A total of 80 lesions with a hypointense rim in at least one of the three imaging modalities were detected. Screen captures of all 80 lesions comparing their appearances in the three imaging modalities are presented in the electronic supplementary material. The highest number of rim lesions was found in 3DT1TFE (78 rims), followed by the SWIp phase (60 rims), and the fewest were found in SWIp (57 rims).

The T1-dark rim, when used to predict the presence of a paramagnetic rim on SWIp phase images, exhibited a sensitivity of 58/60 (96.67%; exact 95% confidence interval: 88.47% to 99.59%). The positive predictive value was determined to be 58/78 (74.36%; exact 95% confidence interval: 63.21% to 83.58%). Heatmaps representing the sensitivity and specificity of each combination of imaging modalities included in the study are shown in Figure 2.

The lesions were classified into true positive, false positive, and false negative categories according to the capacity of 3DT1TFE to predict the presence of a paramagnetic rim on SWIp phase images. False positives (lesions with a T1-dark rim but without an SWIp phase rim) were subclassified as “T1-shine-through rims” if they had a rim on SWIp or were subclassified “isolated T1-dark rims” if they did not. Table 2 summarizes the definition and number of lesions identified in each category.

Notably, after further review of the cases of hypointense rims in other modalities that were not present on 3DT1TFE, we identified that in both of these cases, the lesions were globally markedly T1-hypointense in their core. Figures 3–6 show examples of the four different types of lesions.

In this study, we have defined the T1-dark rim sign in the MRI exam of patients with MS. This sign, found in 3D T1 gradient-echo imaging, is highly sensitive and can detect nearly all (97%) PRLs observed in SWIp phase. However, with a 74% PPV, over a quarter the of lesions with a T1-dark rim did not have identifiable PRLs on SWIp phase. The clinical significance of these T1-dark rim lesions with no identifiable paramagnetic rim and their possible histopathological relationship with smoldering lesions remain unexplored.

The recent shift in MS patient management underscores the importance of accurate prognostic biomarkers. Early high-efficiency disease-modifying treatments can delay disability in patients with high inflammatory activity [3, 4]. Additionally, new treatments are effective in non-active progressive MS forms, which previously had no treatment [5]. Therefore, markers aiding the early identification of suitable patients are essential [2].

PRLs, visible in SWI, indicate smoldering inflammation and have been proposed as disability progression biomarkers [14, 15]. However, SWI is not routinely used in MS MRI follow-up [16]. Furthermore, these lesions have been primarily characterized using high-field scanners, and lower-field scanners have been less commonly used [11, 12, 27, 28]. Lastly, the identification of PRLs is complex and requires a detailed examination of images, which presents a challenge for their quantification in clinical practice [21].

However, previous studies have described the characteristic T1-hypointensity of PRLs [10, 18–20]. Recently, in one study, normalized-intensity 3DT1TFE was used to compare the intensity profiles of PRLs versus non-PRL white-matter lesions, and it was found that a semi-quantifiable deep hypointensity was highly specific to PRLs and, thus, could be studied as a surrogate marker of smoldering inflammation [21]. In the current study, we validated that these pronounced hypointense foci are a PRL hallmark and are that they have a characteristic organization as peripheral rims, easily spotted on 3D gradient echo T1-weighted imaging like 3DT1TFE.

Building on these observations, we postulated that these intensely hypointense voxels might signify active inflammation, unlike "shadow" and "chronic inactive" lesions which are not as hypointense [21]. So, while in acute active lesions, the whole lesion appears hypointense on T1WI [29], our study demonstrates that in smoldering lesions, it is the lesion rim that is hypointense, possibly indicating the location of the inflammatory front or active inflammation zone.

While 74% of T1-dark rim lesions matched with true positive phase-rim lesions, the clinical significance of the remaining 26% is intriguing. Are they indicative of smoldering inflammation, and do they share the prognostic value of PRLs on SWI? The high sensitivity of T1-dark rims suggests they could be a more sensitive measure for smoldering inflammation than SWI's paramagnetic rims. Contemplating the broader picture of PRLs, it could be suggested that we are witnessing the “tip of the iceberg” regarding smoldering inflammation. For example, slowly-expanding lesions defined on consecutive MRIs are also considered smoldering inflammatory lesions, and they do not always have an accompanying paramagnetic rim on SWI [30, 31]. Also, as MRI field strength escalates, PRL detection sensitivity on SWI increases; more lesions surface on 7T than on 3T or 1.5T [11, 12, 27, 28]. This situation leaves us in the dark about the amount of unseen inflammation based on different imaging parameters.

Our research has several inherent strengths, foremost of which is the introduction of the T1-dark rim sign. Indeed, this novel imaging sign serves as a practical alternative to the more advanced SWI techniques for detecting PRLs. Secondly, the image review performed by two neuroradiologists with substantial experience in MS neuroimaging ensured a robust interpretation of the findings. Thirdly, by viewing multiple imaging modalities concurrently in a lesion-centric approach, we ensured a comprehensive and nuanced understanding of the lesion morphologies to enhance the accuracy of our classifications. Finally, the transparent sharing of our imaging data not only solidifies the robustness of our findings but also invites collaboration and scrutiny within the scientific community.

However, the study has limitations. Although we incorporated a second imaging reviewer, we did not execute inter-reviewer correlation. This decision was driven by the aim to be as comprehensive and precise as possible across all sequences, ensuring proximity to the ground truth. Secondly, SWI is not a standardized sequence, and the characteristics of SWI vary between vendors. This may particularly affect aspects such as the presence of the T1-shine-through effect, which might not necessarily occur when using scanners from other vendors. Lastly, the relatively small size of our subject sample, which was not balanced in terms of disease, prognosis, or demographic characteristics, is another limitation, which prevented us from conducting more comprehensive subject-wise analyses.

Overall, our study introduces the T1-dark rim sign as a highly sensitive and accessible imaging marker for the detection of iron-rim lesions. As SWI is not part of standard clinical MS imaging protocols, the T1-dark rim could serve as an alternative marker to identify these lesions, thus potentially enhancing early detection and treatment adjustments for patients with MS at higher risk of disease progression. The findings of this study pave the way for further research to validate the clinical significance and prognostic value of T1-dark rims, which could substantially influence clinical decision-making and patient outcomes in MS.

Multiple sclerosis (MS); magnetic resonance imaging (MRI); positive predictive value (PPV); negative predicting value (NPV); relapsing-remitting MS (RRMS); secondary progressive MS (SPMS); susceptibility-weighted imaging (SWI); 3D T1 turbo field echo (3DT1TFE); SWI with phase enhancement (SWIp); paramagnetic rim lesions (PRLs)

Acknowledgements

We extend our gratitude to Ms. Isabel León for her work in extracting clinical data from electronic medical records. Her precise and meticulous efforts have been instrumental to the integrity of our data, thereby contributing significantly to this study.

This work was supported by an aid from the Institut de Diagnòstic per la Imatge (IDI), under the reference PREDOC IDI 22, dated October 3, 2022. The funding was specifically utilized for the proofreading of the manuscript.

Conflicts of interest

The authors declare that there are no conflicts of interest regarding the publication of this paper. Neither financial nor personal relationships have influenced the outcomes of this research, and there have been no benefits of any kind, during the study, that could be construed as constituting a potential conflict of interest.

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Table 1. Demographics and clinical characteristics of the study population. Continuous variables are expressed as median values with the interquartile range in parentheses. Categorical variables are shown as patient count integers with the percentage in parenthesis. Abbreviations: Expanded Disability Status Scale (EDSS); relapsing-remitting multiple sclerosis (RRMS); secondary progressive multiple sclerosis (SPMS); primary progressive multiple sclerosis (PPMS).

Characteristic	Value
Number of subjects	63
Gender (female)	43 (68%)
Age at MRI [years (IQR)]	49 (43–54.5)
Age at onset [years (IQR)]	30 (23.5–39)
Disease duration [years (IQR)]	14 (6.5–23.5)
Disease status at MRI
RRMS	52 (83%)
SPMS	6 (10%)
PPMS	5 (8%)
EDSS at MRI (IQR)	2.5 (1.5–5)
Treatment at MRI
ME-DMT	25 (40%)
HE-DMT	36 (57%)
None	2 (3%)
Years of first-line treatment (IQR)	4.83 (0.17–12.61)
Years of second-line treatment (IQR)	0.48 (0–3.52)

Table 2. Summary of the classification of paramagnetic rim lesions based on their appearance in the three imaging modalities, taking the susceptibility-weighted imaging phase as ground truth.

Classification	Definition	Appearance	Number of Lesions
True Positive	True paramagnetic rim	T1-rim: Yes Phase-rim: Yes SWIp-rim: Regardless	58
False Positive	T1-shine-through rim	T1-rim: Yes Phase-rim: No SWIp-rim: Yes	5
False Positive	Isolated T1-dark rim	T1-rim: Yes Phase-rim: No SWIp-rim: No	15
False Negative	Globally T1-hypointense lesion	T1-rim: No Phase-rim: Yes SWIp-rim: Regardless	2

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The T1-dark-rim: A novel imaging sign for detecting smoldering inflammation in multiple sclerosis

Status:

Journal Publication

Version 1

Abstract

Objectives:

Materials & Methods:

Results:

Conclusion:

Figures

CLINICAL RELEVANCE STATEMENT

KEY POINTS

INTRODUCTION

METHODS

Study approval

Study design, Participants, and Clinical Data Collection

Imaging

Image interpretation

Lesion classification

Data analysis

RESULTS

DISCUSSION

Abbreviations

Declarations

References

Tables

Supplementary Files

Status:

Journal Publication

Version 1