Amsterdam UMC, VUmc
Anatomy & Neurosciences

Author Of 3 Presentations

Imaging Poster Presentation

P0539 - Artificial double inversion recovery images for cortical lesion visualization in multiple sclerosis (ID 817)

Speakers
Presentation Number
P0539
Presentation Topic
Imaging

Abstract

Background

Cortical lesions (CLs) in multiple sclerosis (MS) are clinically important, but highly inconspicuous on conventional clinical MRI. Double inversion recovery (DIR) is sensitive to CL detection, but difficult to implement in clinical practice and research settings, as it is difficult to set up and proper acquisition may take significant time due to the required inversion times (i.e.,~8 to 10 minutes). This work examines whether artificial intelligence can mitigate this dilemma through generation of artificial DIR images from –readily available– conventional clinical MR sequences.

Objectives

To determine whether artificially generated DIR (aDIR) images can be used for CL detection in MS and assess how this compares to conventionally acquired DIR (cDIR) images.

Methods

In this retrospective study, aDIR images were generated from conventional 1.5 Tesla 3D-T1 and 2D-proton density/T2 images in 73 patients with MS (49 RRMS, 20 SPMS, 4 PPMS) and 42 controls. A fully convolutional 3D conditional adversarial network following an adapted U-Net design with skip-connections was trained, using images of 58 patients and 34 controls. The remaining subjects were assigned to the test set for which artificial 3D-DIR images were generated. To determine detection reliability, precision and recall, the aDIR and cDIR images of subjects in the test set were blindly scored for CLs.

Results

A total of 626 CLs were detected on 15 aDIR images versus 696 on cDIR images (ICC=0.92, 95% confidence interval 0.68-0.98 (F(32.755)). Compared to cDIR images, CLs were detected on aDIR images with an average precision and recall of 0.84±0.06 and 0.76±0.09, respectively. The largest difference in CL discernibility was observed in frontal and temporal regions.

Conclusions

Artificially generated DIR images showed excellent reliability, precision and recall in detected cortical lesions when compared to conventionally acquired DIR images. The technique has the potential to broaden DIR availability and to enable retrospective implementation of cortical lesion detection with DIR. Histopathological and multi-center validation are necessary to formally compare sensitivity and specificity and cross-scanner robustness.

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Imaging Poster Presentation

P0611 - Neurite density explains cortical T1-/T2-weighted ratio in multiple sclerosis (ID 1090)

Speakers
Presentation Number
P0611
Presentation Topic
Imaging

Abstract

Background

Cortical damage is clinically relevant in multiple sclerosis (MS), however reliable MRI markers for its monitoring are still an unmet need. Ratio of T1-weighted (T1w) and T2-weighted (T2w) sequences (i.e., T1w/T2w-ratio) has been suggested as a feasible MRI measure to assess cortical abnormalities in patients with MS (PwMS), but its histopathological substrate has yet to be definitively elucidated.

Objectives

To define the histopathological substrate of T1w/T2w-ratio in normal-appearing and demyelinated cortices of PwMS by performing a combined post-mortem MRI/histopathology study.

Methods

Fifteen PwMS and ten age- and sex-matched non-neurological controls (nNC) underwent post-mortem in situ 3T MRI with 3D T1w and T2w sequences, followed by brain dissection.

One hundred and five paraffin embedded tissue blocks (49 from PwMS, 56 from nNC) were collected. Tissue regions were matched to T1w/T2w-ratio maps to obtain regional cortical T1w/T2w-ratio. Using immunohistochemistry and silver staining, cortical density of myelin, microglia, neurons, glial cells and neurites were evaluated. Correlates of T1w/T2w-ratio alterations with histological markers were assessed through linear mixed-effects models.

Results

Twenty-six cortical lesions (85% subpial) were found in 24/49 (51%) cortical regions from PwMS. Compared to nNC’s cortex, both PwMS’ normal-appearing and demyelinated cortices had a significantly lower T1w/T2w-ratio (p=0.045 and 0.001). In PwMS, demyelinated cortex showed a significant lower T1w/T2w-ratio compared to normal-appearing cortex (p=0.007). In PwMS, neurite density was significantly lower in both normal-appearing and demyelinated cortices compared to nNC (p=0.041 and 0.001), and in demyelinated vs. normal-appearing cortex (p=0.048). Demyelinated cortex showed also significant lower myelin density compared to normal-appearing cortex in both nNC and PwMS (p<0.001). Regarding the pathological substrate, T1w/T2w-ratio was positively associated with neurite density (β=3.464×10-2, p=0.004), whereas only a trend for myelin density was found (p=0.082).

Conclusions

Both demyelination and neurite loss were found in the cortex of PwMS. By evaluating several histopathological markers in nNC and PwMS (in normal-appearing and demyelinated cortices), T1w/T2w-ratio was found to be sensitive to MS cortical damage and more specific to neurite than myelin density. T1w/T2w-ratio could be useful to investigate cortical damage in MS.

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Imaging Poster Presentation

P0642 - Spatial distribution of cortical lesions in multiple sclerosis correlates to clinical and cognitive decline (ID 818)

Speakers
Presentation Number
P0642
Presentation Topic
Imaging

Abstract

Background

Cortical lesions are of eminent clinical relevance in patients with multiple sclerosis (MS), since they have been associated with clinical decline and disease progression. Heretofore, cortical lesions were commonly assessed at a whole-brain level, and were found to correlate with EDSS. However, there is no evidence on correlations between the spatial distribution of cortical lesions and cognition. We hypothesize that the distribution of cortical lesions contributes to explaining the variance of both clinical and cognitive decline.

Objectives

To further elucidate the spatial distribution of cortical lesions and assess their association with clinical and cognitive decline.

Methods

One-hundred-fourteen patients (59 RRMS, 37 SPMS, 16 PPMS, mean age 54.49 ±8.99, 76 female) underwent MRI (double inversion recovery (DIR) and 3D-T1), and neuropsychological assessment (BRB-N, Stroop, Memory comparison task). Raw cognition data were converted to Z-scores based on the control scores, and averaged over the domains. For each patient, cortical lesions were identified and delineated on DIR. The extent of lesioned cortex was measured and cortical lesion maps were generated to enable vertex-wise cortical lesion probability maps and correlations using FreeSurfer.

Results

Cortical lesions were preponderantly situated in frontal and temporal lobes, as well as in the motor and anterior cingulate cortex. Significant clusters of vertex-wise correlations between cortical lesions and EDSS were primarily found for the motor cortex. Significant clusters of vertex-wise correlations between cortical lesions and cognition were primarily found for the frontal and temporal lobe.

Conclusions

The presence of frontal and temporal cortical lesions specifically predicted cognitive decline, while cortical lesions in the motor cortex were related to physical functioning. This confirms the hypothesis that the spatial distribution of cortical lesions contributes to explaining the variance of both clinical and cognitive decline. Further studies should investigate whether the location of cortical lesions is relevant to specific cognitive functions (e.g., memory or executive functioning).

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Presenter Of 2 Presentations

Imaging Poster Presentation

P0539 - Artificial double inversion recovery images for cortical lesion visualization in multiple sclerosis (ID 817)

Speakers
Presentation Number
P0539
Presentation Topic
Imaging

Abstract

Background

Cortical lesions (CLs) in multiple sclerosis (MS) are clinically important, but highly inconspicuous on conventional clinical MRI. Double inversion recovery (DIR) is sensitive to CL detection, but difficult to implement in clinical practice and research settings, as it is difficult to set up and proper acquisition may take significant time due to the required inversion times (i.e.,~8 to 10 minutes). This work examines whether artificial intelligence can mitigate this dilemma through generation of artificial DIR images from –readily available– conventional clinical MR sequences.

Objectives

To determine whether artificially generated DIR (aDIR) images can be used for CL detection in MS and assess how this compares to conventionally acquired DIR (cDIR) images.

Methods

In this retrospective study, aDIR images were generated from conventional 1.5 Tesla 3D-T1 and 2D-proton density/T2 images in 73 patients with MS (49 RRMS, 20 SPMS, 4 PPMS) and 42 controls. A fully convolutional 3D conditional adversarial network following an adapted U-Net design with skip-connections was trained, using images of 58 patients and 34 controls. The remaining subjects were assigned to the test set for which artificial 3D-DIR images were generated. To determine detection reliability, precision and recall, the aDIR and cDIR images of subjects in the test set were blindly scored for CLs.

Results

A total of 626 CLs were detected on 15 aDIR images versus 696 on cDIR images (ICC=0.92, 95% confidence interval 0.68-0.98 (F(32.755)). Compared to cDIR images, CLs were detected on aDIR images with an average precision and recall of 0.84±0.06 and 0.76±0.09, respectively. The largest difference in CL discernibility was observed in frontal and temporal regions.

Conclusions

Artificially generated DIR images showed excellent reliability, precision and recall in detected cortical lesions when compared to conventionally acquired DIR images. The technique has the potential to broaden DIR availability and to enable retrospective implementation of cortical lesion detection with DIR. Histopathological and multi-center validation are necessary to formally compare sensitivity and specificity and cross-scanner robustness.

Collapse
Imaging Poster Presentation

P0642 - Spatial distribution of cortical lesions in multiple sclerosis correlates to clinical and cognitive decline (ID 818)

Speakers
Presentation Number
P0642
Presentation Topic
Imaging

Abstract

Background

Cortical lesions are of eminent clinical relevance in patients with multiple sclerosis (MS), since they have been associated with clinical decline and disease progression. Heretofore, cortical lesions were commonly assessed at a whole-brain level, and were found to correlate with EDSS. However, there is no evidence on correlations between the spatial distribution of cortical lesions and cognition. We hypothesize that the distribution of cortical lesions contributes to explaining the variance of both clinical and cognitive decline.

Objectives

To further elucidate the spatial distribution of cortical lesions and assess their association with clinical and cognitive decline.

Methods

One-hundred-fourteen patients (59 RRMS, 37 SPMS, 16 PPMS, mean age 54.49 ±8.99, 76 female) underwent MRI (double inversion recovery (DIR) and 3D-T1), and neuropsychological assessment (BRB-N, Stroop, Memory comparison task). Raw cognition data were converted to Z-scores based on the control scores, and averaged over the domains. For each patient, cortical lesions were identified and delineated on DIR. The extent of lesioned cortex was measured and cortical lesion maps were generated to enable vertex-wise cortical lesion probability maps and correlations using FreeSurfer.

Results

Cortical lesions were preponderantly situated in frontal and temporal lobes, as well as in the motor and anterior cingulate cortex. Significant clusters of vertex-wise correlations between cortical lesions and EDSS were primarily found for the motor cortex. Significant clusters of vertex-wise correlations between cortical lesions and cognition were primarily found for the frontal and temporal lobe.

Conclusions

The presence of frontal and temporal cortical lesions specifically predicted cognitive decline, while cortical lesions in the motor cortex were related to physical functioning. This confirms the hypothesis that the spatial distribution of cortical lesions contributes to explaining the variance of both clinical and cognitive decline. Further studies should investigate whether the location of cortical lesions is relevant to specific cognitive functions (e.g., memory or executive functioning).

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