Multimodal analysis to predict shunt surgery outcome of 284 patients with suspected idiopathic normal pressure hydrocephalus

Antti J. Luikku, Anette Hall, Ossi Nerg, Anne M. Koivisto, Mikko Hiltunen, Seppo Helisalmi, Sanna-Kaisa Herukka, Anna Sutela, Maria Kojoukhova, Jussi Mattila, Jyrki Lötjönen, Jaana Rummukainen, Irina Alafuzoff, Juha E. Jääskeläinen, Anne M. Remes, Hilkka Soininen, Ville Leinonen

Research output: Contribution to journalArticleScientificpeer-review

8 Citations (Scopus)

Abstract

Objectives: Optimal selection of idiopathic normal pressure hydrocephalus (iNPH) patients for shunt surgery is challenging. Disease State Index (DSI) is a statistical method that merges multimodal data to assist clinical decision-making. It has previously been shown to be useful in predicting progression in mild cognitive impairment and differentiating Alzheimer's disease (AD) and frontotemporal dementia. In this study, we use the DSI method to predict shunt surgery response for patients with iNPH. Methods: In this retrospective cohort study, a total of 284 patients (230 shunt responders and 54 non-responders) from the Kuopio NPH registry were analyzed with the DSI. Analysis included data from patients' memory disorder assessments, age, clinical symptoms, comorbidities, medications, frontal cortical biopsy, CT/MRI imaging (visual scoring of disproportion between Sylvian and suprasylvian subarachnoid spaces, atrophy of medial temporal lobe, superior medial subarachnoid spaces), APOE genotyping, CSF AD biomarkers, and intracranial pressure. Results: Our analysis showed that shunt responders cannot be differentiated from non-responders reliably even with the large dataset available (AUC?=?0.58). Conclusions: Prediction of the treatment response in iNPH is challenging even with our extensive dataset and refined analysis. Further research of biomarkers and indicators predicting shunt responsiveness is still needed.
Original languageEnglish
Pages (from-to)2311-2319
JournalActa Neurochirurgica
Volume158
Issue number12
DOIs
Publication statusPublished - 2016
MoE publication typeA1 Journal article-refereed

Fingerprint

Normal Pressure Hydrocephalus
Alzheimer Disease
Subarachnoid Space
Biomarkers
Frontotemporal Dementia
Memory Disorders
Intracranial Pressure
Temporal Lobe
Area Under Curve
Atrophy
Registries
Comorbidity
Cohort Studies
Retrospective Studies
Biopsy
Research
Datasets

Keywords

  • Idiopathic normal pressure hydrocephalus
  • Shunt response
  • Computer-assisted diagnosis
  • Prognosis
  • Cognitive decline

Cite this

Luikku, A. J., Hall, A., Nerg, O., Koivisto, A. M., Hiltunen, M., Helisalmi, S., ... Leinonen, V. (2016). Multimodal analysis to predict shunt surgery outcome of 284 patients with suspected idiopathic normal pressure hydrocephalus. Acta Neurochirurgica, 158(12), 2311-2319. https://doi.org/10.1007/s00701-016-2980-4
Luikku, Antti J. ; Hall, Anette ; Nerg, Ossi ; Koivisto, Anne M. ; Hiltunen, Mikko ; Helisalmi, Seppo ; Herukka, Sanna-Kaisa ; Sutela, Anna ; Kojoukhova, Maria ; Mattila, Jussi ; Lötjönen, Jyrki ; Rummukainen, Jaana ; Alafuzoff, Irina ; Jääskeläinen, Juha E. ; Remes, Anne M. ; Soininen, Hilkka ; Leinonen, Ville. / Multimodal analysis to predict shunt surgery outcome of 284 patients with suspected idiopathic normal pressure hydrocephalus. In: Acta Neurochirurgica. 2016 ; Vol. 158, No. 12. pp. 2311-2319.
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abstract = "Objectives: Optimal selection of idiopathic normal pressure hydrocephalus (iNPH) patients for shunt surgery is challenging. Disease State Index (DSI) is a statistical method that merges multimodal data to assist clinical decision-making. It has previously been shown to be useful in predicting progression in mild cognitive impairment and differentiating Alzheimer's disease (AD) and frontotemporal dementia. In this study, we use the DSI method to predict shunt surgery response for patients with iNPH. Methods: In this retrospective cohort study, a total of 284 patients (230 shunt responders and 54 non-responders) from the Kuopio NPH registry were analyzed with the DSI. Analysis included data from patients' memory disorder assessments, age, clinical symptoms, comorbidities, medications, frontal cortical biopsy, CT/MRI imaging (visual scoring of disproportion between Sylvian and suprasylvian subarachnoid spaces, atrophy of medial temporal lobe, superior medial subarachnoid spaces), APOE genotyping, CSF AD biomarkers, and intracranial pressure. Results: Our analysis showed that shunt responders cannot be differentiated from non-responders reliably even with the large dataset available (AUC?=?0.58). Conclusions: Prediction of the treatment response in iNPH is challenging even with our extensive dataset and refined analysis. Further research of biomarkers and indicators predicting shunt responsiveness is still needed.",
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Luikku, AJ, Hall, A, Nerg, O, Koivisto, AM, Hiltunen, M, Helisalmi, S, Herukka, S-K, Sutela, A, Kojoukhova, M, Mattila, J, Lötjönen, J, Rummukainen, J, Alafuzoff, I, Jääskeläinen, JE, Remes, AM, Soininen, H & Leinonen, V 2016, 'Multimodal analysis to predict shunt surgery outcome of 284 patients with suspected idiopathic normal pressure hydrocephalus', Acta Neurochirurgica, vol. 158, no. 12, pp. 2311-2319. https://doi.org/10.1007/s00701-016-2980-4

Multimodal analysis to predict shunt surgery outcome of 284 patients with suspected idiopathic normal pressure hydrocephalus. / Luikku, Antti J.; Hall, Anette; Nerg, Ossi; Koivisto, Anne M.; Hiltunen, Mikko; Helisalmi, Seppo; Herukka, Sanna-Kaisa; Sutela, Anna; Kojoukhova, Maria; Mattila, Jussi; Lötjönen, Jyrki; Rummukainen, Jaana; Alafuzoff, Irina; Jääskeläinen, Juha E.; Remes, Anne M.; Soininen, Hilkka; Leinonen, Ville.

In: Acta Neurochirurgica, Vol. 158, No. 12, 2016, p. 2311-2319.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Multimodal analysis to predict shunt surgery outcome of 284 patients with suspected idiopathic normal pressure hydrocephalus

AU - Luikku, Antti J.

AU - Hall, Anette

AU - Nerg, Ossi

AU - Koivisto, Anne M.

AU - Hiltunen, Mikko

AU - Helisalmi, Seppo

AU - Herukka, Sanna-Kaisa

AU - Sutela, Anna

AU - Kojoukhova, Maria

AU - Mattila, Jussi

AU - Lötjönen, Jyrki

AU - Rummukainen, Jaana

AU - Alafuzoff, Irina

AU - Jääskeläinen, Juha E.

AU - Remes, Anne M.

AU - Soininen, Hilkka

AU - Leinonen, Ville

PY - 2016

Y1 - 2016

N2 - Objectives: Optimal selection of idiopathic normal pressure hydrocephalus (iNPH) patients for shunt surgery is challenging. Disease State Index (DSI) is a statistical method that merges multimodal data to assist clinical decision-making. It has previously been shown to be useful in predicting progression in mild cognitive impairment and differentiating Alzheimer's disease (AD) and frontotemporal dementia. In this study, we use the DSI method to predict shunt surgery response for patients with iNPH. Methods: In this retrospective cohort study, a total of 284 patients (230 shunt responders and 54 non-responders) from the Kuopio NPH registry were analyzed with the DSI. Analysis included data from patients' memory disorder assessments, age, clinical symptoms, comorbidities, medications, frontal cortical biopsy, CT/MRI imaging (visual scoring of disproportion between Sylvian and suprasylvian subarachnoid spaces, atrophy of medial temporal lobe, superior medial subarachnoid spaces), APOE genotyping, CSF AD biomarkers, and intracranial pressure. Results: Our analysis showed that shunt responders cannot be differentiated from non-responders reliably even with the large dataset available (AUC?=?0.58). Conclusions: Prediction of the treatment response in iNPH is challenging even with our extensive dataset and refined analysis. Further research of biomarkers and indicators predicting shunt responsiveness is still needed.

AB - Objectives: Optimal selection of idiopathic normal pressure hydrocephalus (iNPH) patients for shunt surgery is challenging. Disease State Index (DSI) is a statistical method that merges multimodal data to assist clinical decision-making. It has previously been shown to be useful in predicting progression in mild cognitive impairment and differentiating Alzheimer's disease (AD) and frontotemporal dementia. In this study, we use the DSI method to predict shunt surgery response for patients with iNPH. Methods: In this retrospective cohort study, a total of 284 patients (230 shunt responders and 54 non-responders) from the Kuopio NPH registry were analyzed with the DSI. Analysis included data from patients' memory disorder assessments, age, clinical symptoms, comorbidities, medications, frontal cortical biopsy, CT/MRI imaging (visual scoring of disproportion between Sylvian and suprasylvian subarachnoid spaces, atrophy of medial temporal lobe, superior medial subarachnoid spaces), APOE genotyping, CSF AD biomarkers, and intracranial pressure. Results: Our analysis showed that shunt responders cannot be differentiated from non-responders reliably even with the large dataset available (AUC?=?0.58). Conclusions: Prediction of the treatment response in iNPH is challenging even with our extensive dataset and refined analysis. Further research of biomarkers and indicators predicting shunt responsiveness is still needed.

KW - Idiopathic normal pressure hydrocephalus

KW - Shunt response

KW - Computer-assisted diagnosis

KW - Prognosis

KW - Cognitive decline

U2 - 10.1007/s00701-016-2980-4

DO - 10.1007/s00701-016-2980-4

M3 - Article

VL - 158

SP - 2311

EP - 2319

JO - Acta Neurochirurgica

JF - Acta Neurochirurgica

SN - 0001-6268

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