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Identifying patients with neuronal intranuclear inclusion disease in Singapore using characteristic diffusion-weighted MR images

  • Diagnostic Neuroradiology
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Abstract

Purpose

Adult-onset neuronal intranuclear inclusion disease (NIID) is a rare neurodegenerative disorder described mainly in the Japanese population, with characteristic DWI abnormalities at the junction between gray and white matter. We identify possible cases of NIID in the picture archive and communication system (PACS) of a tertiary neurological referral hospital in Singapore and describe their radiological features.

Methods

The neuroradiology imaging database was reviewed using keyword search of radiological reports to identify patients who had “subcortical U fibre” abnormalities on DWI. MRI were retrospectively reviewed, and those fulfilling inclusion criteria were invited for skin biopsy to detect nuclear inclusions by light and electron microscopy.

Results

Twelve Chinese patients (nine female; median age 70.5 years) were enrolled. Seven patients were being assessed for dementia and five for other neurological indications. In all patients, DWI showed distinctive subcortical high signal with increased average apparent diffusion coefficient (ADC), involving frontal, parietal, and temporal more than occipital lobes; the corpus callosum and external capsule were affected in some patients. On T2-weighted images, cerebral and cerebellar atrophy and white matter hyperintensity of Fazekas grade 2 and above were seen in all patients. Three patients underwent skin biopsy; all were positive for intranuclear hyaline inclusion bodies on either p62 staining or electron microscopy, which are pathognomonic for NIID.

Conclusion

Previously undiagnosed patients with NIID can be identified by searching for abnormalities at the junction between gray and white matter on DWI in PACS and subsequently confirmed by skin biopsy. Radiologists should recognize the distinctive neuroimaging pattern of this dementing disease.

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References

  1. Takahashi-Fujigasaki J (2003) Neuronal intranuclear hyaline inclusion disease. Neuropathology. 23:351–359

    Article  PubMed  Google Scholar 

  2. Woulfe JM (2007) Abnormalities of the nucleus and nuclear inclusions in neurodegenerative disease: a work in progress. Neuropathol Appl Neurobiol 33:2–42. https://doi.org/10.1111/j.1365-2990.2006.00819.x

    Article  CAS  PubMed  Google Scholar 

  3. Takahashi-Fujigasaki J (2015) Neuronal intranuclear hyaline inclusion disease (NIHID): an update. Brain and Nerve 67:199–204

    PubMed  Google Scholar 

  4. Sasaki T, Hideyama T, Saito Y, Shimizu J, Maekawa R, Shiio Y (2015) Neuronal intranuclear inclusion disease presenting with recurrent cerebral infarct-like lesions. Neurol Clin Neurosci 3:185–187. https://doi.org/10.1111/ncn3.178

    Article  Google Scholar 

  5. Toyota T, Huang Z, Nohara S, Okada K, Kakeda S, Korogi Y, Nakayama T, Sone J, Sobue G, Adachi H (2015) Neuronal intranuclear inclusion disease manifesting with new-onset epilepsy in the elderly. Neurol Clin Neurosci 3:238–240. https://doi.org/10.1111/ncn3.12016

    Article  Google Scholar 

  6. Sone J, Mori K, Inagaki T, Katsumata R, Takagi S, Yokoi S, Araki K, Kato T, Nakamura T, Koike H, Takashima H, Hashiguchi A, Kohno Y, Kurashige T, Kuriyama M, Takiyama Y, Tsuchiya M, Kitagawa N, Kawamoto M, Yoshimura H, Suto Y, Nakayasu H, Uehara N, Sugiyama H, Takahashi M, Kokubun N, Konno T, Katsuno M, Tanaka F, Iwasaki Y, Yoshida M, Sobue G (2016) Clinicopathological features of adult-onset neuronal intranuclear inclusion disease. Brain 139:3170–3186. https://doi.org/10.1093/brain/aww249

    Article  PubMed  PubMed Central  Google Scholar 

  7. Araki K, Sone J, Fujioka Y, Masuda M, Ohdake R, Tanaka Y, Nakamura T, Watanabe H, Sobue G (2016) Memory loss and frontal cognitive dysfunction in a patient with adult-onset neuronal Intranuclear inclusion disease. Intern Med 55:2281–2284. https://doi.org/10.2169/internalmedicine.55.5544

    Article  PubMed  Google Scholar 

  8. Yokoi S, Yasui K, Hasegawa Y, Niwa K, Noguchi Y, Tsuzuki T, Mimuro M, Sone J, Watanabe H, Katsuno M, Yoshida M, Sobue G (2016) Pathological background of subcortical hyperintensities on diffusion-weighted images in a case of neuronal intranuclear inclusion disease. Clin Neuropathol 35:375–380. https://doi.org/10.5414/NP300961

    Article  PubMed  Google Scholar 

  9. Yoshimoto T, Takamatsu K, Kurashige T et al (2017) Adult-onset neuronal intranuclear inclusion disease in two female siblings. Brain Nerve 69:267–274. https://doi.org/10.11477/mf.1416200737

    Article  PubMed  Google Scholar 

  10. Aiba Y, Sakakibara R, Abe F, Higuchi T, Tokuyama W, Hiruta N, Tateno F, Tsuyusaki Y, Kishi M, Tateno H, Ogata T (2016) Neuronal intranuclear inclusion disease with leukoencephalopathy and light motor-sensory and autonomic neuropathy diagnosed by skin biopsy. J Neurol Sci 368:263–265. https://doi.org/10.1016/j.jns.2016.07.042

    Article  PubMed  Google Scholar 

  11. Takahashi-Fujigasaki J, Nakano Y, Uchino A, Murayama S (2016) Adult-onset neuronal intranuclear hyaline inclusion disease is not rare in older adults. Geriatr Gerontol Int 16:51–56. https://doi.org/10.1111/ggi.12725

    Article  PubMed  Google Scholar 

  12. Morimoto S, Hatsuta H, Komiya T, Kanemaru K, Tokumaru AM, Murayama S (2017) Simultaneous skin-nerve-muscle biopsy and abnormal mitochondrial inclusions in intranuclear hyaline inclusion body disease. J Neurol Sci 372:447–449. https://doi.org/10.1016/j.jns.2016.10.042

    Article  CAS  PubMed  Google Scholar 

  13. Yokoi S, Yasui K (2011) An autopsy case of intranuclear inclusion body disease with leukoencephalopathy. Japanese Soc Neuropathol - Abstr 52nd Annu Meet 31:333

    Google Scholar 

  14. Sugiyama A, Sato N, Kimura Y, Maekawa T, Enokizono M, Saito Y, Takahashi Y, Matsuda H, Kuwabara S (2017) MR imaging features of the cerebellum in adult-onset neuronal intranuclear inclusion disease: 8 cases. AJNR Am J Neuroradiol 38:2100–2104. https://doi.org/10.3174/ajnr.A5336

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Abe K, Fujita M (2017) Over 10 years MRI observation of a patient with neuronal intranuclear inclusion disease. BMJ Case Rep 2017. https://doi.org/10.1136/bcr-2016-218790

  16. Matsuda H, Asada T, Midori Tokumaru A (2017) Neuroimaging diagnosis for Alzheimer’s disease and other dementias. Springer Japan, Tokyo

    Book  Google Scholar 

  17. Sone J, Tanaka F, Koike H, Inukai A, Katsuno M, Yoshida M, Watanabe H, Sobue G (2011) Skin biopsy is useful for the antemortem diagnosis of neuronal intranuclear inclusion disease. Neurology 76:1372–1376. https://doi.org/10.1212/WNL.0b013e3182166e13

    Article  CAS  PubMed  Google Scholar 

  18. Sone J, Kitagawa N, Sugawara E, Iguchi M, Nakamura R, Koike H, Iwasaki Y, Yoshida M, Takahashi T, Chiba S, Katsuno M, Tanaka F, Sobue G (2013) Neuronal intranuclear inclusion disease cases with leukoencephalopathy diagnosed via skin biopsy. J Neurol Neurosurg Psychiatry 85:3–6. https://doi.org/10.1136/jnnp-2013-306084

    Article  Google Scholar 

  19. Kohno Y, Ishii A, Terada M, Kobayahi M, Hiroki M, Tamaoka A NH (2013) A case of neuronal intranuclear hyaline inclusion disease presenting polyneuropathy, episodic vomitting, neurogenic bladder dysfunction and leukoencephalopathy. In: The Japanese Society of Neuropathology. p 369

  20. Osaki Y, Shimatani Y, Fujita K, Murakami N, Sato K, Terasawa Y, Izumi Y, Kaji R, Sumikura H MS (2013) A case of neuronal intranuclear hyaline inclusion disease suggested by diffusion-weighted MRI and confirmed by skin biopsy. In: The Japanese Society of Neuropathology. p 370

  21. Sone J, Kitagawa N, Iwasaki Y, Yoshida M, Tanaka F SG (2013) Diagnosis of neuronal intranuclear inclusion disease with skin biopsy. In: The Japanese Society of Neuropathology. p 370

  22. Tokumaru A, Sakurai K, Imabayashi E, Hasegawa S, Murayama S TM (2013) MRI findings of neuronal intranuclear hyaline inclusion disease (NIHID)- histopathologic correlation. In: The Japanese Society of Neuropathology. p 368

  23. Kitagawa N, Sone J, Sobue G, Kuroda M, Sakurai M (2014) Neuronal intranuclear inclusion disease presenting with resting tremor. Case Rep Neurol 6:176–180. https://doi.org/10.1159/000363687

    Article  PubMed  PubMed Central  Google Scholar 

  24. Tokumaru AM (2011) Usefulness of MRI for diagnosing dementia. Nihon Rinsho 69(Suppl 8):494–508

    PubMed  Google Scholar 

  25. Martin-Macintosh EL, Broski SM, Johnson GB, Hunt CH, Cullen EL, Peller PJ (2016) Multimodality imaging of neurodegenerative processes: part 1, the basics and common dementias. AJR Am J Roentgenol 207:871–882. https://doi.org/10.2214/AJR.14.12842

    Article  PubMed  Google Scholar 

  26. Patro SN, Glikstein R, Hanagandi P, Chakraborty S (2015) Role of neuroimaging in multidisciplinary approach towards non-Alzheimer’s dementia. Insights Imaging 6:531–544. https://doi.org/10.1007/s13244-015-0421-1

    Article  PubMed  PubMed Central  Google Scholar 

  27. Kansagra AP, Yu JPJ, Chatterjee AR, Lenchik L, Chow DS, Prater AB, Yeh J, Doshi AM, Hawkins CM, Heilbrun ME, Smith SE, Oselkin M, Gupta P, Ali S (2016) Big data and the future of radiology informatics. Acad Radiol 23:30–42. https://doi.org/10.1016/j.acra.2015.10.004

    Article  PubMed  Google Scholar 

  28. Yang GL, Tan YF, Loh SC, Lim TCC (2007) Neuroradiology imaging database: using picture archive and communication systems for brain tumour research. Singap Med J 48:342–346

    CAS  Google Scholar 

  29. Morris JC (1997) Clinical dementia rating: a reliable and valid diagnostic and staging measure for dementia of the Alzheimer type. Int Psychogeriatrics 9:173–176. https://doi.org/10.1017/s1041610297004870

    Article  Google Scholar 

  30. Fazekas F, Chawluk JB, Alavi A, Hurtig HI, Zimmerman RA (1987) MR signal abnormalities at 1.5 T in Alzheimer’s dementia and normal aging. AJR Am J Roentgenol 149:351–356. https://doi.org/10.2214/ajr.149.2.351

    Article  CAS  PubMed  Google Scholar 

  31. Maddalena A, Richards CS, McGinniss MJ et al (2001) Technical standards and guidelines for fragile X: the first of a series of disease-specific supplements to the Standards and Guidelines for Clinical Genetics Laboratories of the American College of Medical Genetics. Quality Assurance Subcommittee of the L. Genet Med 3:200–205. https://doi.org/10.1097/00125817-200105000-00010

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Yadav N, Raja P, Shetty SS, Jitender S, Prasad C, Kamble NL, Mahadevan A, M N (2019) Neuronal intranuclear inclusion disease: a rare etiology for rapidly progressive dementia. Alzheimer Dis Assoc Disord 00:1–3. https://doi.org/10.1097/WAD.0000000000000312

    Article  Google Scholar 

  33. Suthiphosuwan S, Sasikumar S, Munoz DG (2019) MRI diagnosis of neuronal intranuclear inclusion disease leukoencephalopathy. Neurol Clin Pract. https://doi.org/10.1212/CPJ.0000000000000664

    Google Scholar 

  34. Liu Y, Lu J, Li K, Zhao H, Feng Y, Zhang Z, Hu L, Li G, Shao Y, Wang Y (2019) A multimodal imaging features of the brain in adult-onset neuronal intranuclear inclusion disease. Neurol Sci 40:1495–1497. https://doi.org/10.1007/s10072-019-03742-5

    Article  PubMed  Google Scholar 

  35. Chen L, Wu L, Li S, Huang Q, Xiong J, Hong D, Zeng X (2018) A long time radiological follow-up of neuronal intranuclear inclusion disease: two case reports. Medicine (Baltimore) 97:e13544. https://doi.org/10.1097/MD.0000000000013544

    Article  Google Scholar 

  36. Cupidi C, Dijkstra AA, Melhem S, Vernooij MW, Severijnen LA, Hukema RK, Rozemuller AJM, Neumann M, van Swieten JC, Seelaar H (2019) Refining the spectrum of neuronal intranuclear inclusion disease: a case report. J Neuropathol Exp Neurol 78:665–670. https://doi.org/10.1093/jnen/nlz043

    Article  PubMed  Google Scholar 

  37. Valdés Hernández MDC, Chappell FM, Muñoz Maniega S, Dickie DA, Royle NA, Morris Z, Anblagan D, Sakka E, Armitage PA, Bastin ME, Deary IJ, Wardlaw JM (2017) Metric to quantify white matter damage on brain magnetic resonance images. Neuroradiology 59:951–962. https://doi.org/10.1007/s00234-017-1892-1

    Article  PubMed  PubMed Central  Google Scholar 

  38. Patay Z (2005) Diffusion-weighted MR imaging in leukodystrophies. Eur Radiol 15:2284–2303. https://doi.org/10.1007/s00330-005-2846-2

    Article  PubMed  Google Scholar 

  39. Sacher M, Fatterpekar GM, Edelstein S, Sansaricq C, Naidich TP (2005) MRI findings in an atypical case of Kearns-Sayre syndrome: a case report. Neuroradiology 47:241–244. https://doi.org/10.1007/s00234-004-1314-z

    Article  PubMed  Google Scholar 

  40. Yang E, Prabhu SP (2014) Imaging manifestations of the leukodystrophies, inherited disorders of white matter. Radiol Clin N Am 52:279–319. https://doi.org/10.1016/j.rcl.2013.11.008

    Article  PubMed  Google Scholar 

  41. Sedel F, Tourbah A, Fontaine B, Lubetzki C, Baumann N, Saudubray JM, Lyon-Caen O (2008) Leukoencephalopathies associated with inborn errors of metabolism in adults. J Inherit Metab Dis 31:295–307. https://doi.org/10.1007/s10545-008-0778-0

    Article  CAS  PubMed  Google Scholar 

  42. van der Lei HDW, Steenweg ME, Bugiani M, Pouwels PJW, Vent IM, Barkhof F, van Wieringen WN, van der Knaap MS (2012) Restricted diffusion in vanishing white matter. JAMA Neurol 69:723–727. https://doi.org/10.1001/archneurol.2011.1658

    Article  Google Scholar 

  43. Gelpi E, Botta-Orfila T, Bodi L, Marti S, Kovacs G, Grau-Rivera O, Lozano M, Sánchez-Valle R, Muñoz E, Valldeoriola F, Pagonabarraga J, Tartaglia GG, Milà M (2017) Neuronal intranuclear (hyaline) inclusion disease and fragile X-associated tremor/ataxia syndrome: a morphological and molecular dilemma. Brain 140:e51. https://doi.org/10.1093/brain/awx156

    Article  PubMed  Google Scholar 

  44. Sone J, Nakamura T, Koike H, Katsuno M, Tanaka F, Iwasaki Y, Yoshida M, Sobue G (2017) Reply: neuronal intranuclear (hyaline) inclusion disease and fragile X-associated tremor/ataxia syndrome: a morphological and molecular dilemma. Brain 140:e52. https://doi.org/10.1093/brain/awx158

    Article  PubMed  Google Scholar 

  45. Padilha IG, Nunes RH, Scortegagna FA, Pedroso JL, Marussi VH, Rodrigues Gonçalves MR, Barsottini OGP, da Rocha AJ (2018) MR imaging features of adult-onset neuronal intranuclear inclusion disease may be indistinguishable from fragile X-associated tremor/ataxia syndrome. AJNR Am J Neuroradiol 39:E100–E101. https://doi.org/10.3174/ajnr.A5729

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Sugiyama A, Sato N (2018) Reply. AJNR Am J Neuroradiol 39:E102. https://doi.org/10.3174/ajnr.A5757

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Leehey MA (2009) Fragile X-associated tremor/ataxia syndrome: clinical phenotype, diagnosis, and treatment. J Investig Med 57:830–836. https://doi.org/10.2310/JIM.0b013e3181af59c4

    Article  PubMed  PubMed Central  Google Scholar 

  48. Brown SSG, Stanfield AC (2015) Fragile X premutation carriers: a systematic review of neuroimaging findings. J Neurol Sci 352:19–28. https://doi.org/10.1016/j.jns.2015.03.031

    Article  PubMed  Google Scholar 

  49. Brunberg JA, Jacquemont S, Hagerman RJ, Berry-Kravis EM, Grigsby J, Leehey MA, Tassone F, Brown WT, Greco CM, Hagerman PJ (2002) Fragile X premutation carriers: characteristic MR imaging findings of adult male patients with progressive cerebellar and cognitive dysfunction. AJNR Am J Neuroradiol 23:1757–1766

    PubMed  PubMed Central  Google Scholar 

  50. Dmytriw AA, Sawlani V, Shankar J (2017) Diffusion-weighted imaging of the brain: beyond stroke. Can Assoc Radiol J 68:131–146. https://doi.org/10.1016/j.carj.2016.10.001

    Article  PubMed  Google Scholar 

  51. Demaerel P, Heiner L, Robberecht W, Sciot R, Wilms G (1999) Diffusion-weighted MRI in sporadic Creutzfeldt-Jakob disease. Neurology 52:205 LP–205205. https://doi.org/10.1212/WNL.52.1.205

    Article  Google Scholar 

  52. Kandiah N, Tan K, Pan a BS et al (2008) Creutzfeldt-Jakob disease: which diffusion-weighted imaging abnormality is associated with periodic EEG complexes? J Neurol 255:1411–1414. https://doi.org/10.1007/s00415-008-0934-3

    Article  CAS  PubMed  Google Scholar 

  53. Zerr I, Kallenberg K, Summers DM, Romero C, Taratuto A, Heinemann U, Breithaupt M, Varges D, Meissner B, Ladogana A, Schuur M, Haik S, Collins SJ, Jansen GH, Stokin GB, Pimentel J, Hewer E, Collie D, Smith P, Roberts H, Brandel JP, van Duijn C, Pocchiari M, Begue C, Cras P, Will RG, Sanchez-Juan P (2009) Updated clinical diagnostic criteria for sporadic Creutzfeldt-Jakob disease. Brain 132:2659–2668. https://doi.org/10.1093/brain/awp191

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Chandrasekhar V, Lin J, Morère O, et al (2015) A practical guide to CNNs and Fisher vectors for image instance retrieval

    Google Scholar 

  55. Faria AV, Oishi K, Yoshida S, Hillis A, Miller MI, Mori S (2015) Content-based image retrieval for brain MRI: an image-searching engine and population-based analysis to utilize past clinical data for future diagnosis. NeuroImage Clin 7:367–376. https://doi.org/10.1016/j.nicl.2015.01.008

    Article  PubMed  PubMed Central  Google Scholar 

  56. Dinh TA, Silander T, Su B, Gong T, Pang BC, Lim CC, Lee CK, Tan CL, Leong TY (2013) Unsupervised medical image classification by combining case-based classifiers. Stud Health Technol Inform 192:739–743

    PubMed  Google Scholar 

  57. Cheng LTE, Zheng J, Savova GK, Erickson BJ (2010) Discerning tumor status from unstructured MRI reports-completeness of information in existing reports and utility of automated natural language processing. J Digit Imaging 23:119–132. https://doi.org/10.1007/s10278-009-9215-7

    Article  PubMed  Google Scholar 

  58. Shrot S, Salhov M, Dvorski N, Konen E, Averbuch A, Hoffmann C (2019) Application of MR morphologic, diffusion tensor, and perfusion imaging in the classification of brain tumors using machine learning scheme. Neuroradiology 61:757–765. https://doi.org/10.1007/s00234-019-02195-z

    Article  PubMed  Google Scholar 

  59. Zeynalova A, Kocak B, Durmaz ES, Comunoglu N, Ozcan K, Ozcan G, Turk O, Tanriover N, Kocer N, Kizilkilic O, Islak C (2019) Preoperative evaluation of tumour consistency in pituitary macroadenomas: a machine learning-based histogram analysis on conventional T2-weighted MRI. Neuroradiology 61:767–774. https://doi.org/10.1007/s00234-019-02211-2

    Article  PubMed  Google Scholar 

  60. Ker J, Wang L, Rao J, Lim T (2018) Deep learning applications in medical image analysis. IEEE Access 3536:1. https://doi.org/10.1109/ACCESS.2017.2788044

    Article  Google Scholar 

  61. Liew CJY, Krishnaswamy P, Cheng LT-E, Tan CH, Poh ACC, Lim TCC (2019) Artificial Intelligence and Radiology in Singapore: championing a new age of augmented imaging for unsurpassed patient care. Ann Acad Med Singapore 48:16–24

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Acknowledgments

The authors wish to thank Junko Takahashi-Fujikasaki for invaluable help with slide preparation and Qianhui Cheng for administrative support.

Funding

This work was supported by the NNI Health Research Endowment Fund, which has no involvement in study design, data collection/analysis/interpretation, report writing, or publication decisions.

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Correspondence to C. C. Tchoyoson Lim.

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Yu, WY., Xu, Z., Lee, HY. et al. Identifying patients with neuronal intranuclear inclusion disease in Singapore using characteristic diffusion-weighted MR images. Neuroradiology 61, 1281–1290 (2019). https://doi.org/10.1007/s00234-019-02257-2

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