Chiari type 1 deformity classification

Chiari type 1 deformity classification

Nishikawa et al. classified Chiari malformation type I (CM-I) according to the mechanism of ptosis of the brain stem and cerebellum, based on a morphometric study of the posterior cranial fossa (PCF) and craniovertebral junction (CVJ). Surgery was performed to manage the mechanism of the hindbrain ptosis. They calculated the volume of the PCF (VPCF) and the area surrounding the foramen magnum (VSFM) and measured the axial length of the enchondral parts of the occipital bone (occipital bone size) and the hindbrain. According to these measures, they classified CM-I into type A (normal VPCF, normal VSFM, and normal occipital bone size), type B (normal VPCF, small VSFM, and small occipital bone size), and type C (small VPCF, small VSFM, and small occipital bone size). Foramen magnum decompression (FMD) (280 cases) was performed on CM-I types A and B. Expansive suboccipital cranioplasty (ESCP) was performed on CM-I type C. Posterior craniocervical fixation (CCF) was performed in cases with CVJ instability. Lysis of the adhesion and/or sectioning of the filum terminale was performed on cases with tethered cord syndrome. Both ESCP and FMD had a high rate of improvement of neurological symptoms (87%) and recovery rate. There was only a small number of complications. CCF had a high rate of improvement of neurological symptoms (88%) and joint stabilization. In the management of Chiari malformation, appropriate surgical methods that address ptosis of the hindbrain should be chosen. Each surgical approach resulted in a good improvement of neurological symptoms 1).


Valentini et al. suggested defining an association of Chiari type 1 deformity plus untreated sagittal synostosis, a new subtype of complex CM1. For the high percentage of complications and multiple procedures needed to solve the CM1, they advise identifying by 3D-CT scan these children before performing craniovertebral decompression (CVD). They suggest also that if left untreated, sagittal synostosis may lead to the delayed occurrence of a challenging subset of CM1 2).


Chiari malformation Type 1.5 (CM 1.5) was defined as the association of Chiari malformation Type I (CM I) and brainstem herniation.

Although CM 1.5 patients presented with brainstem herniation and more severe tonsillar herniation, other clinical and imaging features and surgical outcomes were similar to CM I patients. Liu et al. think CM 1.5 is just a subtype of CM I, rather than a unique type of Chiari malformations 3).


Taylor et al. identify two subtypes, crowded and spacious, that can be distinguished by MRI appearance without volumetric analysis. Earlier age at surgery and the presence of syringomyelia are more common in the crowded subtype. The presence of the spacious subtype suggests that crowdedness alone cannot explain the pathogenesis of Chiari I malformation in many patients, supporting the need for further investigation 4).

see Pediatric Chiari type 1 deformity.

see Chiari type 1 deformity and syringomyelia.


1)

Nishikawa M, Bolognese PA, Kula RW, Ikuno H, Takami T, Ohata K. Surgical Management of Chiari Malformations: Preliminary Results of Surgery According to the Mechanisms of Ptosis of the Brain Stem and Cerebellum. J Neurol Surg B Skull Base. 2021 Apr;82(2):264-272. doi: 10.1055/s-0039-1697977. Epub 2019 Sep 30. PMID: 33816049; PMCID: PMC8009696.
2)

Valentini LG, Saletti V, Erbetta A, Chiapparini L, Furlanetto M. Chiari 1 malformation and untreated sagittal synostosis: a new subset of complex Chiari? Childs Nerv Syst. 2019 Jul 21. doi: 10.1007/s00381-019-04283-0. [Epub ahead of print] PubMed PMID: 31327038.
3)

Liu W, Wu H, Aikebaier Y, Wulabieke M, Paerhati R, Yang X. No significant difference between Chiari malformation type 1.5 and type I. Clin Neurol Neurosurg. 2017 Mar 30;157:34-39. doi: 10.1016/j.clineuro.2017.03.024. [Epub ahead of print] PubMed PMID: 28384597.
4)

Taylor DG, Mastorakos P, Jane JA Jr, Oldfield EH. Two distinct populations of Chiari I malformation based on presence or absence of posterior fossa crowdedness on magnetic resonance imaging. J Neurosurg. 2017 Jun;126(6):1934-1940. doi: 10.3171/2016.6.JNS152998. Epub 2016 Sep 2. PubMed PMID: 27588590.

Moyamoya disease classification

Moyamoya disease classification

The ischemic and hemorrhagic subtypes are difficult to diagnose prior to disease onset.

The intralateral and perilateral ventricular arteries on the original axial Time of flight magnetic resonance angiography images might suggest the hemorrhagic type of moyamoya disease prior to onset 1).

Unilateral and bilateral moyamoya disease (MMD).

Quasi Moyamoya disease

Asymptomatic Moyamoya Disease

Ischemic-type Moyamoya Disease

Suzuki and Kodoma classified the severity of moyamoya disease by progression of an occlusive process and the eventual appearance of collaterals based on serial cerebral angiographic evaluations and staged them, known as ‘Suzuki stages of Moyamoya disease’ which are mentioned under staging.

see Suzuki staging.


Traditional moyamoya disease (MMD) classification relies on morphological digital subtraction angiography (DSA) assessment, which do not reflect hemodynamic status, clinical symptoms, or surgical treatment outcome.

The Berlin MMD grading system is able to stratify preoperative hemispheric symptomatology. Furthermore, it correlated with postoperative new ischemic changes on MRI, and showed a strong trend in predicting clinical postoperative stroke. 2)


Ladner et al performed digital subtraction angiography and noninvasive structural and hemodynamic MRI, and they outline a new classification system for patients with moyamoya that they have named Prior Infarcts, Reactivity, and Angiography in Moyamoya Disease (PIRAMD).

Healthy control volunteers (n = 11; age 46 ± 12 years [mean ± SD]) and patients (n = 25; 42 ± 13.5 years) with angiographically confirmed moyamoya provided informed consent and underwent structural (T1-weighted, T2-weighted, FLAIR, MR angiography) and hemodynamic (T2*- and cerebral blood flow-weighted) 3-T MRI. Cerebrovascular reactivity (CVR) in the internal carotid artery territory was assessed using susceptibility-weighted MRI during a hypercapnic stimulus. Only hemispheres without prior revascularization were assessed. Each hemisphere was considered symptomatic if localizing signs were present on neurological examination and/or there was a history of transient ischemic attack with symptoms referable to that hemisphere. The PIRAMD factor weighting versus symptomatology was optimized using binary logistic regression and receiver operating characteristic curve analysis with bootstrapping. The PIRAMD finding was scored from 0 to 10. For each hemisphere, 1 point was assigned for prior infarct, 3 points for reduced CVR, 3 points for a modified Suzuki Score ≥ Grade II, and 3 points for flow impairment in ≥ 2 of 7 predefined vascular territories. Hemispheres were divided into 3 severity grades based on total PIRAMD score, as follows: Grade 1, 0-5 points; Grade 2, 6-9 points; and Grade 3, 10 points.

In 28 of 46 (60.9%) hemispheres the findings met clinical symptomatic criteria. With decreased CVR, the odds ratio of having a symptomatic hemisphere was 13 (95% CI 1.1-22.6, p = 0.002). The area under the curve for individual PIRAMD factors was 0.67-0.72, and for the PIRAMD grade it was 0.845. There were 0/8 (0%), 10/18 (55.6%), and 18/20 (90%) symptomatic PIRAMD Grade 1, 2, and 3 hemispheres, respectively.

A scoring system for total impairment is proposed that uses noninvasive MRI parameters. This scoring system correlates with symptomatology and may provide a measure of hemodynamic severity in moyamoya, which could be used for guiding management decisions and evaluating intervention response 3).


In 2014 Hung et al. proposed a quantitative method using color-coded parametric quantitative DSA (QDSA) to improve prediction of the severity of MMD. The Td significantly correlated with conventional angiographic grading and with the status of hemodynamic impairment in patients with MMD. QDSA and Td measurements can provide a simple and quantitative angiographic grading system for patients with MMD. 4).


1)

Ishikawa M, Terao S, Kagami H, Inaba M, Naritaka H. Intralateral and Perilateral Ventricular Arteries on Original Axial Magnetic Resonance Angiography in Adult Moyamoya Disease. Eur Neurol. 2021 Mar 29:1-5. doi: 10.1159/000514429. Epub ahead of print. PMID: 33780954.
2)

Teo M, Furtado S, Kaneko OF, Azad TD, Madhugiri V, Do HM, Steinberg GK. Validation and Application for the Berlin Grading System of Moyamoya Disease in Adult Patients. Neurosurgery. 2020 Feb 1;86(2):203-212. doi: 10.1093/neuros/nyz025. PMID: 30864668.
3)

Ladner TR, Donahue MJ, Arteaga DF, Faraco CC, Roach BA, Davis LT, Jordan LC, Froehler MT, Strother MK. Prior Infarcts, Reactivity, and Angiography in Moyamoya Disease (PIRAMD): a scoring system for moyamoya severity based on multimodal hemodynamic imaging. J Neurosurg. 2016 Mar 11:1-9. [Epub ahead of print] PubMed PMID: 26967789.
4)

Hung SC, Liang ML, Lin CF, Lin CJ, Guo WY, Chang FC, Wong TT, Chang CY. New grading of moyamoya disease using color-coded parametric quantitative digital subtraction angiography. J Chin Med Assoc. 2014 Aug;77(8):437-42. doi: 10.1016/j.jcma.2014.05.007. Epub 2014 Jul 12. PMID: 25028291.

Craniopharyngioma Classification

An appropriate classification system with which to individualize Craniopharyngioma treatment is absent.


A QST classification system based on tumor origin was used to classify tumors into 3 types as follows: infrasellar/subdiaphragmatic CPs (Q-CPs), subarachnoidal CPs (S-CPs), and pars tuberalis CPs (T-CPs). Within each tumor type, patients were further arranged into two groups: those treated via the TCA and those treated via the EEA. Patient and tumor characteristics, surgical outcomes, and postoperative complications were obtained. All variables were statistically analyzed between surgical groups for each tumor type 1)


Zhou L, You C. Craniopharyngioma classification. J Neurosurg. 2009 Jul;111(1):197-9; author reply 199. doi: 10.3171/2009.2.JNS081430. PMID: 19569961.

Pascual JM, Carrasco R, Prieto R, Gonzalez-Llanos F, Alvarez F, Roda JM. Craniopharyngioma classification. J Neurosurg. 2008 Dec;109(6):1180-2; author reply 1182-3. doi: 10.3171/JNS.2008.109.12.1180. PMID: 19035739.

see Magill ST, Jane JA, Prevedello DM. Editorial. Craniopharyngioma classification. J Neurosurg. 2021 Mar 5:1-3. doi: 10.3171/2020.8.JNS202666. Epub ahead of print. PMID: 33668034. 2).


The objectives of a study were to identify preoperative prognostic factors in patients with craniopharyngiomas and to develop a risk-based treatment algorithm.

The authors reviewed data obtained in a retrospective cohort of 66 children (mean age 7.4 years, mean follow-up period 7 years) who underwent resection between 1984 and 2001. Postoperative recurrence rates, vision status, and endocrine function were consistent with those reported in the literature. The postoperative morbidity was related to hypothalamic dysfunction. The preoperative magnetic resonance imaging grade, clinically assessed hypothalamic function, and the sugeon’s operative experience (p = 0.007, p = 0.047, p = 0.035, respectively) significantly predicted poor outcome. Preoperative hypothalamic grading was used in a prospective cohort of 22 children (mean age 8 years, mean follow-up period 1.2 years) treated between 2002 and 2004 to stratify patients according to whether they underwent gross-total resection (GTR) (20%), complete resection avoiding the hypothalamus (40%), or subtotal resection (STR) (40%). In cases in which residual disease was present, the patient underwent radiotherapy. There have been no new cases of postoperative hyperphagia, morbid obesity, or behavioral dysfunction in this prospective cohort.

For many children with craniopharyngiomas, the cost of resection is hypothalamic dysfunction and a poor QOL. By using a preoperative classification system to grade hypothalamic involvement and stratify treatment, the authors were able to minimize devastating morbidity. This was achieved by identifying subgroups in which complete resection or STR, performed by an experienced craniopharyngioma surgeon and with postoperative radiotherapy when necessary, yielded better overall results than the traditional GTR 3).


To date, however, the Puget system has not been externally validated.

A panel of 6 experts, consisting of pediatric neurosurgeons and pediatric neuroradiologists, graded 30 preoperative and postoperative MRI scans according to the Puget system. Interrater reliability was calculated using Fleiss’ κ and Krippendorff’s α statistics.

Interrater reliability in the preoperative context demonstrated moderate agreement (κ = 0.50, α = 0.51). Interrater reliability in the postoperative context was 0.27 for both methods of statistical evaluation.

Interrater reliability for the system as defined is moderate. Slight refinements of the Puget MRI grading system, such as collapsing the 3 grades into 2, may improve its reliability, making the system more generalizable 4)


Adamantinomatous craniopharyngioma, the most frequent histological variety in children.

Papillary craniopharyngioma.

see Anaplastic Craniopharyngioma.

Localization

Most craniopharyngiomas can be classified as either “prechiasmatic” or “retrochiasmatic” according to their growth patterns.

Retrochiasmatic craniopharyngioma

Subdiaphragmatic craniopharyngioma

Supradiaphragmatic craniopharyngioma

Intraventricular craniopharyngioma

Appearance

Cystic craniopharyngioma


1)

Fan J, Liu Y, Pan J, Peng Y, Peng J, Bao Y, Nie J, Wang C, Qiu B, Qi S. Endoscopic endonasal versus transcranial surgery for primary resection of craniopharyngiomas based on a new QST classification system: a comparative series of 315 patients. J Neurosurg. 2021 Mar 5:1-12. doi: 10.3171/2020.7.JNS20257. Epub ahead of print. PMID: 33668037.
2)

Magill ST, Jane JA, Prevedello DM. Editorial. Craniopharyngioma classification. J Neurosurg. 2021 Mar 5:1-3. doi: 10.3171/2020.8.JNS202666. Epub ahead of print. PMID: 33668034.
3)

Puget S, Garnett M, Wray A, Grill J, Habrand JL, Bodaert N, Zerah M, Bezerra M, Renier D, Pierre-Kahn A, Sainte-Rose C. Pediatric craniopharyngiomas: classification and treatment according to the degree of hypothalamic involvement. J Neurosurg. 2007 Jan;106(1 Suppl):3-12. Review. PubMed PMID: 17233305.
4)

Whelan R, Prince E, Mirsky DM, Naftel R, Bhatia A, Pettorini B, Avula S, Staulcup S, Alexander AL, Meier M, Hankinson TC. Interrater reliability of a method to assess hypothalamic involvement in pediatric adamantinomatous craniopharyngioma. J Neurosurg Pediatr. 2019 Oct 11:1-6. doi: 10.3171/2019.8.PEDS19295. [Epub ahead of print] PubMed PMID: 31604324.
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