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 Table of Contents     
ORIGINAL ARTICLE
Year : 2011  |  Volume : 26  |  Issue : 2  |  Page : 67-77  

Spectrum of neurocognitive dysfunction in Indian population on FDG PET/CT imaging


1 Division of Pet Imaging, Molecular Imaging Research Center, INMAS, Delhi, India
2 Division of Cyclotron and Radiopharmaceutical Sciences, Molecular Imaging Research Center, INMAS, Delhi, India

Date of Web Publication25-Nov-2011

Correspondence Address:
Rajnish Sharma
Division of PET Imaging, Molecular Imaging Research Center, INMAS, Lucknow Road, Timarpur, Delhi-110 054
India
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Source of Support: DRDO Project No. (ST-P1-2008/INM-311), Conflict of Interest: None


DOI: 10.4103/0972-3919.90255

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   Abstract 

Background : A variety of neurodegenerative disorders produce significant abnormal brain function which can be detected using fluorodeoxyglucose positron emission tomography (FDG PET) scan even when structural changes are not detected on CT or MRI Scan. A study was undertaken at our institute to evaluate the FDG PET/CT findings in Indian population suffering from mild cognitive impairment (MCI), Alzheimer's disease (AD), fronto-temporal dementia (FTD), dementia with lewy body disease (DLBD) and other miscellaneous causes of dementia. Materials and Methods : 117 0 subjects having neurocognitive deficits and 36 normals were included in our study. All patients underwent a detailed history and clinical examination. This was followed by a mini mental state examination. Subsequently an FDG brain PET scan and an MRI were done. Results :In the patient population included in our study group 36 were normal, 39 had MCI, 40 had AD, 14 had FTD, and 13 had DLBD and 11 dementia due to other miscellaneous causes. MCI patients showed primarily reduced tracer uptake in the mesio-temporal cortex. AD patients showed reduced tracer concentration in temporo-parietal lobes, while patients with advanced diseases showed frontal lobe disease additionally. In subjects of FTD, reduced radiotracer uptake in the fronto-temporal lobes was noted. In addition, FTD patients also showed basal ganglia defects. In contrast the DLBD patients showed globally reduced FDG uptake including severely affecting the occipital cortices. Conclusion :In the current study the F18-FDG PET scans have been shown to be highly useful in the diagnosis of various neurocognitive disorders of the brain. AD was found to be the most common dementia in the Indian population followed by MCI. Diffuse Lewy body disease, FTD and other miscellaneous categories of dementia had a near similar incidence.

Keywords: Dementia, F18-FDG scan, Indian population


How to cite this article:
Sharma R, Tripathi M, D'Souza MM, Jaimini A, Varshney R, Panwar P, Kaushik A, Saw S, Seher R, Pandey S, Singh D, Solanki Y, Mishra AK, Mondal A, Tripathi R P. Spectrum of neurocognitive dysfunction in Indian population on FDG PET/CT imaging. Indian J Nucl Med 2011;26:67-77

How to cite this URL:
Sharma R, Tripathi M, D'Souza MM, Jaimini A, Varshney R, Panwar P, Kaushik A, Saw S, Seher R, Pandey S, Singh D, Solanki Y, Mishra AK, Mondal A, Tripathi R P. Spectrum of neurocognitive dysfunction in Indian population on FDG PET/CT imaging. Indian J Nucl Med [serial online] 2011 [cited 2019 Dec 13];26:67-77. Available from: http://www.ijnm.in/text.asp?2011/26/2/67/90255


   Introduction Top


One of the most important uses of PET in neurosciences has been in the work up of the patients of various dementing disorders. Criteria for diagnosis of AD were defined by the National institute of neurological and communicative disorders and the Alzheimer's disease and related disorders. [1] These require evidence of progressive, chronic cognitive deficits in middle aged and elderly patients with no identifiable cause. It is very difficult to differentiate between AD and various other causes of dementia. [2],[3] It has been reported that there is 20-30% decrease in the brain FDG uptake values in patients with various dementias when compared with the normal healthy population. [4]

The magnitude and extent of hypometabolism correlates with the severity of dementia symptoms. [5],[6],[7] MCI is used as a diagnostic classification concept for patients with decline in cognitive performance, which is in excess of the expected age related changes but does not completely fit into the diagnosis of dementia. [8] It has been reported that a substantial proportion of MCI patients subsequently may develop dementing disorder of the Alzheimer type (DAT). [9] Hence, it is important to detect patients of MCI as it includes a sizeable number of subjects with pre-dementia of AD. [10],[11] If patients of MCI are diagnosed on the basis of clinical diagnosis only, then there is a very high possibility of including the population suffering from cerebro vascular disease or depression. [12]

FDG PET assessment of cerebral glucose metabolism is a measure of synaptic activity and can identify the presence and localization of a neurodegenerative process in the brain. Different criteria have been laid down for differential diagnosis of dementia. [11],[13],[14],[15],[16],[17],[18]

AD patients typically show hypometabolism in parieto - temporal cortices and in frontal lobe in the advanced stage of the disease. [19] While the FTD patients show hypometabolism in the frontal and temporal cortices, [20],[21],[22] the DLBD patients show primary hypometabolism in the parieto-occipital cortex. [23],[24] The present study was undertaken to evaluate the spectrum of various neurocognitive dysfunction in the Indian population.


   Materials and Methods Top


The study comprised of 117 subjects including 39 MCI, 40 AD, 14 FTD, 13 DLBD patients and 11 belonging to miscellaneous group.

The subjects were referred from a tertiary neurological centre after detailed history (corroborated by a close informant), clinical examination and mini mental state examination (MMSE). All patients were subjected to FDG PET scan and MRI of brain. All participants provided written informed consent. Approval of the local ethics committee was taken. None of the patients had any evidence of organic brain pathology or organic illness affecting the brain, significant head injury, systemic illness, psychosis or history of drug or alcohol intake.

Normal population

The control normal population included in our study had no functional impairment based on detailed neurological examination. These subjects had a clinical dementia rating (CDR) = 0 or global deterioration scale (GDS) ≤ 2. They all had a MMSE score of more than 28. The subjects were matched to the cases on the basis of age, sex and educational status.

MCI

The criteria for MCI were based on clinical examination showing impaired cognitive function, ability to perform normal daily activities, no evidence of dementing disease. They had a CDR = 0.5 or GDS = 3 and they all had normal activity of daily living (ADL). The MMSE score of these patients was equal to or more than 24.

Dementia

All subjects fulfilled the diagnostic and statistical manual of mental disorders (DSM -IV), [25] criteria for dementia. They all had significant ADL defects, and had a CDR ≥ 1 or GDS ≥ 4. Standard clinical criteria were used to characterize the type of dementia. Consensus criteria were used for the diagnosis of DLB [26] and FTD. [27]

F18-FDG PET

All patients were fasting for at least 4 hours before the study and advised adequate hydration for rapid tracer excretion. The studies were done in a resting state with eyes closed. Ear plugs were used to prevent any auditory stimulus. The PET/CT study was performed on a Discovery STE 16 (GE) camera. F18-FDG was injected intravenously in a dose of 370 M Bq and a brain scan was obtained after an interval of 60 minutes with patient in supine position and head immobilized in a head rest. An initial scout of the head with localizer positioning was followed by a low dose CT acquisition at 110mA and 120 KV for attenuation correction. This was followed by a static 20 minute single bed position 3 dimensional emission scan. Data was reconstructed using 3-dimensional VUE algorithm (GE) and images were viewed for interpretation on a Xeleris workstation using volumetrix protocol (GE). Visual image interpretation was independently performed by 3 PET physicians (Dr. MT, Dr. RS and Dr. AJ) for FDG PET brain scans using fused PET/CT images. Any tracer activity which was noted as abnormal by all the 3 physicians was reported as abnormal.

MRI

MRI studies were undertaken for all patients to rule out morphological abnormalities, vascular insults and intracranial space occupying lesions. This was undertaken on a 1.5 T- Magnetom Vision (Seimens) scanner with a standardized protocol consisting of axial T 1 weighted images (TR 665ms, TE 24 ms, NEX 2) axial and sagital, T 2 weighted images (TR - 3800 ms, TE 90 ms, NEX 2) and axial and coronal FLAIR images (TR - 9000 ms, TE 110ms, NEX 2).


   Results Top


Details of the subjects included in the study have been depicted in [Table 1],[Table 2],[Table 3],[Table 4],[Table 5] for the MCI, AD, FTD, DLBD and Miscellaneous Dementia Category respectively. Among MCI patients 17 out of 39 (43.5%) showed cortical hypometabolism indicative of neurodegenerative disease. Mesio-temporal hypometabolism was the most common defect noted in patients of MCI [Figure 1]. The remaining 22 subjects did not show significant cortical hypometabolism. Out of 17 patients found to have abnormal FDG Brain scan 11 were labeled as MCI, 4 AD and 2 had FTD pattern. 2 (18.8%) MCI patients showed bilateral F18-FDG uptake reductions. 6 (54.5%) showed predominantly left and 3 (27.2%) showed a predominant right reductions. The AD group included 17 patients with mild and 23 patients with moderate to severe dementia. Among the AD patients 17/40 (42.5%) showed prominent parieto-temporal hypometabolism [Figure 2]. Symmetric F18-FDG uptake reductions were found in 26/40 (65%) AD, 8/40 (20%) showed severe hypometabolism in left hemisphere and 6/40 (15%) showed more severe hypometabolism in right hemisphere. 23/40 (57.5%) AD patients showed additional frontal cortex hypometabolism. No extension into occipital cortex was noted in AD patients in our series of patients.
Table 1: Clinical and diagnostic characteristics of MCI subjects


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Table 2: Clinical and diagnostic characteristics of AD subjects


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Table 3: Clinical and diagnostic characteristics of FTD subjects


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Table 4: Clinical and diagnostic characteristics of DLBD subjects


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Table 5: Clinical and diagnostic characteristics of miscellaneous subjects


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Figure 1: 71-year-old male presented with the complaints of forgetfulness. His MMSE score was 24. Arrows in F18-FDG PET images show bilateral Mesio-temporal hypometabolism diagnostic of MCI, in this patient

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Figure 2: F18-FDG PET images in late AD. Brain images of a 50-year-old female demonstrate hypometabolism of the frontal, parietal and temporal lobes bilaterally with relative sparing of primary visual cortex, thalamus and basal ganglia

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The DLBD group included 13 patients, out of which 4 were with mild dementia and 9 patients had moderate to severe dementia. Among the DLBD patients, all patients showed hypometabolism in the occipital cortex of the brain besides affecting temporal, parietal or frontal regions of the brain [Figure 3]. F18 FDG uptake reductions were bilateral in (9/13) 69.2% of the patients, more severe in left hemisphere in (1/13) 7.6 % and more severe in right hemisphere in 21% of the patients. (3/13) 23% patients had moderate to severe DLBD pattern.
Figure 3: F18-FDG PET images of  Creutzfeldt-Jakob disease More Details. This patient was 56-year-old female with a history of memory loss, personality changes and hallucinations. The MMSE Score was 24. The typical metabolic pattern of hypometabolism affecting the Fronto- parietal- temporal lobes, basal ganglia and thalamus bilaterally was noted

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The FTD group included 14 subjects, out of which 9 had mild dementia and 5 patients had moderate to severe dementia. These patients showed a prominent frontal and temporal hypometabolism [Figure 4]. F18-FDG uptake reductions were bilateral in 1/14 (7.1%) of patients, more severe in left in 6/14 (42.8%) and more severe in right hemisphere in 7/14 (50%).
Figure 4: F18-FDG PET images of FTD. This patient is a 55-year-old female with an MMSE score of 26. Arrows indicate bilateral hypometabolism of the frontal (a) & temporal (b) cortex

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The miscellaneous group comprised of 7 patients of Parkinson's dementia (PD) [Figure 5], 2 of vascular dementia [Figure 6] and 2 of Creutzfeldt-Jakob disease [Figure 7].
Figure 5: F18-FDG PET Images of Dementia with Lewy body disease. A 75-year-male had a MMSE score of 19 and symptoms of cognitive dysfunction and hallucinations. PET scan shows bilaterally reduced tracer uptake in frontal, parietal and occipital cortices

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Figure 6: 18F-FDOPA images of PD dementia. FDOPA scans shows reduced tracer uptake bilaterally in the basal ganglia (L > R). While the FDG scan shows hypometabolism in the right frontal cortex

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Figure 7: F18-FDG PET images of vascular dementia in 60-year-old female. Patient presented with irritability, violent behavior and visual hallucinations. Hypometabolism is noted in right frontal cortex, right temporal cortex and right thalamus

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   Discussion Top


The importance of PET imaging in the management of the dementia patient is to help in the early diagnosis of the dementia disease process. Early detection of patients of MCI is essential as one third of MCI patients proceed to manifest DAT while more than half do not show progression to dementia. These results confirm that MCI patients even when selected carefully after clear cut inclusion criteria, represent a very heterogeneous patient population with regard to prognosis. Our study group comprised of 39 patients referred to our institute after being diagnosed to have MCI on clinical and MMSE test examination. Out of these MCI patients 13 were found to be normal. This itself highlights the importance of PET examination in patients having a neurocognitive disorder. Mosconi et al, reported that out of 37 patients screened for MCI, 12 were found to be normal on PET study. [28] Our study findings also show that F18- FDG PET can differentiate MCI from normal patients quite efficiently making it an effective tool to distinguish between these two groups which cause a lot of diagnostic issues as clinically it is quite difficult to distinguish age related cognitive deterioration from MCI which is a diagnostic dilemma for the clinician. Various F18-FDG PET profiles have been reported in the MCI group of patients which is due to the spectrum of cognitive deficits reported in this patient group. [29] In the present PET study AD PET pattern was found in 4 subjects and FTD pattern was noted in 2 patients. In previously reported PET studies 22-41% of the MCI patients with an AD PET pattern eventually converted to AD within a time period of 1-3 years. [29],[30],[31],[32],[33],[34]

F18-FDG PET scan has played an important role in the diagnosis of AD. Patients of AD present with parieto-temporal defects in the cortices when compared to their age equivalent healthy subjects. [35] It has already been highlighted that patients of MCI are at high risk of developing AD in future. [36]

Diagnosis can be made in patients of AD when clinical symptoms are not being fully expressed by the patient, in very early stage of AD. There is definitive evidence to show that generalized atrophy of brain is present in elderly patients, years before they actually developed AD. [37],[38],[39],[4]0,[41]

In our study, 42.5% of the patients had a mild AD while the rest had a severe form of the disease. The patient with the milder form of the disease had temporo-parietal defects while those with severe form the disease also had defects in the frontal region. In contrast, the western literature has reported that 99% of the patients had mild form of disease while 1 had severe AD pattern. [42] Thus the Indian population in contrast appears to be affected from a more severe form of the disease. On further analysis it was found that 65% population had bilaterally symmetrical defects, while 15% had right dominant pattern and 20% had a left dominant hypometabolism. None of the AD patients were found to have occipital lesions on FDG PET scans.

FTD is one of the most common forms of cortical dementia, accounting for about 20% of presenile dementia. Diagnosis of FTD is difficult as these groups of patients have a variegated clinical and pathological picture. [43],[44] Patients suffering from this form of dementia have been reported to suffer from forgetfulness and a variety of behavior disorders and hence are difficult to separate out from patients of AD, vascular dementia and psychiatric illnesses. It has been reported earlier that FTD results in finding of cerebral atrophy on CT and MR studies and hypo-perfusion in PET studies in frontal and temporal regions of the brain. [45],[46] We found additional hypometabolism in the basal ganglia region which are known to be involved in a variety of brain activities. [47] It has been suggested that asymmetric hemispheric degeneration is common in patients with FTD. [48],[49],[50],[51] We found a hemispheric metabolic asymmetry in 92.8% of our FTD patients. Thus it can be inferred that FTD is a disorder that causes asymmetrical degeneration of cerebral hemispheres.

 Lewy body dementia More Details has been described as the second most common senile dementia after AD. [52],[53],[54] Till the advent of PET, the post mortem examination was the only tool available to provide the definitive diagnosis in this disease. [55],[56],[57] The clinical diagnosis is based on certain diagnostic criteria. [54] However these clinical criteria have high specificity (90-97%) and a very low sensitivity of the order of (22-75%). [58] The main clinical complaints noted in DLBD patients include a progressive and a fluctuating cognitive decline with delusion, hallucinations and PD like symptoms. Other symptom includes repeated falls, loss of consciousness and neuroleptic symptoms. In comparison in AD loss of memory and neuropsychiatric features are more common in late stages. [59] Moderate Parkinsonian signs are observed both in AD and DLBD. [60] Thus in such cases where there is overlapping of symptoms such as cognitive decline, psychiatric signs and  Parkinsonism More Details, it is difficult to differentiate AD from DLBD. [55],[61] In our study 64% of the patients were found to have a moderate to severe form of the disease. All these patients had a bilateral form of the disease. Besides 2 patients of DLBD showed hypometabolism in basal gangalia and thalamus region also.

Thus in the majority of AD patients temporo-parietal defects were noted, in FTD patients more prominent hypometabolism in frontal and temporal cortex was noted and in DLBD patients though a global hypo-perfusion in the cortex was noted, the hypometabolism was most profound in the occipital cortex, which corresponds to the results of earlier workers. [52],[62] This characteristic pattern of cortical hypometabolism including the occipital areas could be a result of diaschisis due to disruption of intracortial connections. Diaschisis is defined as depression of regional neuronal metabolism and cerebral blood flow caused by dysfunction in anatomically separate but functionally related neuronal regions. [63] Typically, sparing of primary sensori-motor cortex was noted. All the patients from this group showed prominent hypometabolism in the occipital region as reported in previous reports. [20],[21],[22],[23],[24] Thus, it is concluded that the most common cause of dementia in Indian population is AD followed by MCI. FTD and DLBD had almost same incidence patterns.


   Conclusion Top


The present study illustrates the utility of F18-FDG PET in the diagnosis and characterization of neurocognitive dysfunction. AD has been found to be the most prevalent form of dementia in the Indian subcontinent, which is in conformity with the global trend. A significantly higher proportion of frontal lobe involvement was noted in the Indian population, as compared to that documented in the world-wide literature. These new findings, and epidemio-pathological reasons thereof, would merit further investigation. F18 FDG PET scans provide an objective and sensitive support to the diagnosis of early dementia.

 
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    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]


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